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Racial/ethnic and sexual behavior disparities in rates of sexually transmitted infections, San Francisco, 1999-2008
Racial/ethnic minorities and men who have sex with men (MSM) represent populations with disparate sexually transmitted infection (STI) rates. While race-specific STI rates have been widely reported, STI rates among MSM is often challenging given the absence of MSM population estimates. We evaluated the race-specific rates of chlamydia and gonorrhea among MSM and non-MSM in San Francisco between 1999-2008.
2000 US Census data for San Francisco was used to estimate the number of African-American, Asian/Pacific Islander, Hispanic, and white males. Data from National HIV Behavioral Surveillance (NHBS) MSM 1, conducted in 2004, was used to estimate the total number of MSM in San Francisco and the size of race/ethnic sub-populations of MSM. Non-MSM estimates were calculated by subtracting the number of estimated MSM from the total number of males residing in San Francisco. Rates of MSM and non-MSM gonorrhea and chlamydia reported between 1999 and 2008 were stratified by race/ethnicity. Ratios of MSM and non-MSM rates of morbidity were calculated by race/ethnicity.
Between 1999-2008, MSM accounted for 72% of gonorrhea cases and 51% of chlamydia cases. Throughout the study period, African-American MSM had the highest chlamydia rate with 606 cases per 100,000 in 1999 increasing to 2067 cases per 100,000 in 2008. Asian/Pacific Islander MSM consistently had the lowest rate among MSM with1003 cases per 100,000 in 2008. The ratio of MSM/non-MSM for chlamydia was highest among whites 11.6 (95% CI: 8.8-14.4) and Asian/Pacific Islanders 8.6 (95% CI: 6.2-11), and lowest among African-Americans 1.53 (95% CI: 1.2-1.9) and Hispanics 4.43 (95% CI: 2.8-6.0). Gonorrhea rates were similar for African-American, white, and Hispanic MSM between 2137-2441 cases per 100,000 in 2008. Asian/Pacific Islander MSM had the lowest gonorrhea rate with 865 cases per 100,000 in 2008. The ratio of MSM/non-MSM for gonorrhea was highest among whites 11.6 (95% CI: 8.8-14.4) and Asian/Pacific Islanders 8.6 (95% CI: 6.2-11), and lowest among African-Americans 1.53 (95% CI: 1.2-1.9) and Hispanics 4.43 (95% CI: 2.8-6.0).
For all racial/ethnic groups in San Francisco, MSM carried a substantially higher burden of STIs compared to non-MSM except among African-American men. These racial and sexual behavior disparities warrant further public health attention and resources.
Health disparities among racial and ethnic minorities have been well documented in the literature, particularly among Sexually Transmitted Infections (STIs)
Racial/ethnic and sexual orientation specific prevalence of STIs are essential in determining the excess burden that some racial groups experience but also the increased STI burden that MSM have over other men. These data have broad implications including provision and targeting of prevention and treatment programs to address health and healthcare disparities.
The objectives of this study were to evaluate the race-specific rates of chlamydia and gonorrhea among men in San Francisco.
As per Title 17, California Code of Regulations §2500, §2593, §2641-2643, §2800-2812, lab and provider reporting of chlamydia and gonorrhea to the San Francisco Department of Public Health is mandated. Data on the case's race/ethnicity (Hispanic/Latino, African American/Black, Asian/Pacific Islander (including Asian-Indian, Cambodian, Chinese, Filipino, Guamanian, Hawaiian, Japanese, Korean, Loatian, Samoan, Vietnamese, or "Other"), Native American/Alaskan Native, White, or "Other") and genders of sex partners are collected through routine provider and lab based reporting. In San Francisco, all STI morbidity among males is electronically matched to any prior episode of the patient (STI clinic visit, prior reported STI morbidity) to determine if the patient has documentation of reporting a male partner, a sexual identity of gay, or a diagnosis of rectal gonorrhea or rectal chlamydia. These data date back to the 1970s and we assumed that sexual orientation was fixed; i.e., that any previous report of having a male sex partner, gay sexual identity, or rectal STI was carried forward in time to any subsequent morbidity. Men who reported both male and female partners were included in our definition of MSM. All male reports for gonorrhea or chlamydia with no history of a male partner, gay identity, or a rectal infection were assumed to be non-MSM. All male gonorrhea and chlamydia morbidity at any site (urogenital, rectal or pharyngeal) among San Francisco residents that was separated by more than 30 days reported between 1999 and 2008 were included in the analysis.
Data from National HIV Behavioral Surveillance (NHBS) MSM 1, conducted in 2004, was used to estimate the total number of MSM in San Francisco
Race/ethnicity-specific rates of MSM and non-MSM gonorrhea and chlamydia were estimated by dividing the number of reported cases in each MSM and racial/ethnic group by the estimated San Francisco population for each group. MSM to non-MSM racial/ethnic specific rate ratios were also estimated. As these were de-identified, publically available surveillance data used for public health purposes, this study was considered exempt from human-subjects considerations in accordance with the Code of Federal Regulations, Title 45, and by the Committee on Human Research at University of California, San Francisco.
In total, between 1999 and 2008, there were 15,418 case of gonorrhea and 14,197 cases of chlamydia reported in San Francisco. MSM accounted for 72% of the gonorrhea cases and 51% of the chlamydia cases during that period. In San Francisco, the estimated number of white MSM was 31,788, African-American MSM 4,450, Hispanic MSM 10,808, and Asian/Pacific Islander MSM 10,127. Among non-MSM in San Francisco, an estimated 147,538 were white, 25,511 were African-American, 47,047 are Hispanic, and 104,810 were Asian/Pacific Islander.
In San Francisco, case rates of chlamydia among MSM increased for all racial groups during the study period (Figure
Figure 1
Rates of chlamydia among men in San Francisco, 1999-2008
Rates of chlamydia among men in San Francisco, 1999-2008. (A) Cases of chlamydia among men who have sex with men (MSM) per 100,000. (B) Cases of chlamydia among non-MSM per 100,000.
Figure 2
MSM/non-MSM ratio of chlamydia in San Francsico, 1999-2008
MSM/non-MSM ratio of chlamydia in San Francsico, 1999-2008. MSM to non-MSM racial/ethnic specific rate ratios for chlamydia.
Between 1999 and 2003, 65% to 81% of chlamydia cases in MSM were diagnosed at the San Francisco STI Clinic (City Clinic). However, in 2007 only 55% of cases were diagnosed at City Clinic and 22% were diagnosed by primary care physicians (compared to 7% in 1999). In contrast, non-MSM were diagnosed in similar proportions at various clinic settings including City Clinic, primary care offices, hospital, and outreach settings throughout the study period.
Rates of gonorrhea among MSM increased between 1999 and 2008 (Figure
Figure 3
Rates of gonorrhea among men in San Francisco, 1999-2008
Rates of gonorrhea among men in San Francisco, 1999-2008. (A) Cases of gonorrhea among men who have sex with men (MSM) per 100,000. (B) Cases of chlamydia among non-MSM per 100,000.
Figure 4
MSM/non-MSM ratio ofgonorrhea in San Francisco, 1999-2008
MSM/non-MSM ratio of gonorrhea in San Francisco, 1999-2008. MSM to non-MSM racial/ethnic specific rate ratios for gonorrhea.
Like chlamydia, approximately 70% of gonorrhea cases were diagnosed in City Clinic between 1999 and 2003 and 5% to 10% of cases diagnosed in primary care offices. By 2007, 58% of cases were diagnosed in City Clinic and 24% were diagnosed in primary care offices. Among non-MSM, approximately two thirds of gonorrhea cases were diagnosed at City Clinic and hospital settings between 1999 and 2003. However, by 2007, 38% of cases were diagnosed in primary care offices and 15% diagnosed at either City Clinic or hospital settings.
In measurement of disease burden, rates are superior to case counts as they account for the underlying population at risk and provide a measure of disease intensity in a sub-population. Often MSM specific STI rates are difficult to calculate given that population estimates of MSM are often unavailable. Here we report on MSM and non-MSM racial/ethnic specific rates of STIs in San Francisco. Between 1999 and 2008, rates of MSM chlamydia and gonorrhea increased, while non-MSM rates of these STIs remained largely stable. These increases in STIs are consistent with previous reports in San Francisco and other cities
Reducing racial disparities is a national public health priority. STIs, specifically gonorrhea, represent some of the largest racial/ethnic disparities among reportable conditions
Furthermore, the data presented here suggest that the disparities paradigm be expanded to include sexual behavior. For all racial/ethnic groups, MSM had significantly higher rates of chlamydia and gonorrhea compared to non-MSM. In San Francisco, MSM are significantly burdened with STIs and these disparities warrant public health attention and resources.
San Francisco STD Prevention and Control Services recommends that all sexually active MSM be screened for syphilis, chlamydia, and gonorrhea every three to six months. In San Francisco, routine screening for gonorrhea and chlamydia at the urogenital, pharyngeal, and rectal sites is widely available for MSM and has been shown to lead to significantly higher rates of gonorrhea and chlamydia diagnoses, primarily through diagnosis of asymptomatic infections
Based on lower sexual risk behavior such screening is not routinely indicated in non-MSM and the higher rate of STIs among African-American non-MSM in San Francisco, while previously documented, is not well understood. Although several studies have shown that African-American MSM are less likely compared to other racial groups to self-identify as "gay" or "bisexual" we used data on gender of sex partners and not sexual identity to define MSM
Our analysis has several limitations worth noting. Our STI case rates and MSM/non-MSM ratios are dependent on estimation of population sizes for both MSM and non-MSM in San Francisco. Using the National NHBS and 2000 census data, we calculated a midpoint estimate and assume that the size of each population is relatively stable over the time period of analysis (1999-2008). Comparison of the 2000 census data to the 2006-2008 American Community Survey data for San Francisco County did not reveal any significant demographic shifts
We capitalized on our existing data infrastructure and locally available data to examine population-based estimates of the rates of gonorrhea and chlamydia among men in San Francisco. The rates of STIs among MSM continue to rise, while the rates among non-MSM have been stable. MSM carried a substantially higher burden of STIs compared to non-MSM except among African-American men. The lower MSM/non-MSM ratio among African-Americans was driven primarily by the high rates among African American non-MSM. This study was the first population based estimate of the burden of gonorrhea and chlamydia among men in San Francisco. Utilizing the MSM population estimates of San Francisco and sexual partner gender data acquired at the time of testing, we report racial disparities that mirror those previously documented in the literature. We also suggest that among African-American men the gender of sexual partners is less of a determinant of gonorrhea or chlamydia rates than for other racial groups. This phenomenon warrants further research to establish contributing factors in order to develop effective, appropriate prevention strategies.
Competing interests
HS, KB, HR, RK, and JK declare that they have no competing interests.
Authors' contributions
HS contributed to developing the idea for the study, assisted with data analysis, and developed the manuscript. KB provided advice and guidance for the study, assisted with data analysis, and contributed to the manuscript. HR developed MSM population estimates and contributed to the manuscript. RK assisted with data analysis. JK develop the idea for the study, oversaw all aspects of the study, and contributed to the manuscript. All authors read and approved the final manuscript.
2006 Disease Profile
San Francisco Sexually Transmitted Disease Annual Summary, 2006
San Francisco Sexually Transmitted Disease Annual Summary, 2008
Gonorrhea in the HIV era: a reversal in trends among men who have sex with men
Risk factors for rectal gonococcal infection amidst resurgence in HIV transmission
HIV infection in men who have sex with men, New York City Department of Health sexually transmitted disease clinics, 1990-1999: a decade of serosurveillance finds that racial disparities and associations between HIV and gonorrhea persist
High HIV seroprevalence associated with gonorrhea: New York City Department of Health, sexually transmitted disease clinics, 1990-1997
HIV risk differences between African-American and white men who have sex with men
The effect of partner characteristics on HIV infection among African American men who have sex with men in the Young Men's Survey, Los Angeles, 1999-2000
Trends in sexually transmitted diseases, sexual risk behavior, and HIV infection among Asian/Pacific Islander men who have sex with men, San Francisco, 1999-2005
Methodology for the United States Resident Population Estimates by Age, Sex, Race, and Hispanic Origin (Vintage 2008): April 1, 2000 to July 1, 2008
Estimating the size of populations at risk for HIV: Issues and Methods updated July 2003
Understanding recent increases in the incidence of sexually transmitted infections in men having sex with men: changes in risk behavior from risk avoidance to risk reduction
Prevalence of rectal, urethral, and pharyngeal chlamydia and gonorrhea detected in 2 clinical settings among men who have sex with men: San Francisco, California, 2003
Sentinel Surveillance of Rectal Chlamydia and Gonorrhea Among Males - San Francisco, 2005-2008
Focusing "down low": bisexual black men, HIV risk and heterosexual transmission
Greater risk for HIV infection of black men who have sex with men: a critical literature review
Differences in disclosure of sexuality among African American and White gay/bisexual men: implications for HIV/AIDS prevention
Social context, sexual networks, and racial disparities in rates of sexually transmitted infections
Sexually transmitted diseases in the Southeastern United States: location, race, and social context
Investigating ethnic inequalities in the incidence of sexually transmitted infections: mathematical modelling study
Measuring disparities in the incidence of sexually transmitted diseases
2006-2008 American Community Survey
Concurrent sexual partnerships and racial disparities in HIV infection among men who have sex with men
Health-related characteristics of men who have sex with men: a comparison of those living in "gay ghettos" with those living elsewhere
Comparing internet-based and venue-based methods to sample MSM in the San Francisco Bay Area
Prevalence of seroadaptive behaviours of men who have sex with men, San Francisco, 2004
Locating unrecognized HIV infections among men who have sex with men: San Francisco and Los Angeles
Prevalence of chlamydia and gonorrhoea among a population of men who have sex with men
Differences in demographics and risk factors among men attending public v non-public STD clinics in Baltimore, Maryland
Pre-publication history
The pre-publication history for this paper can be accessed here:


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Baseball is America's current pastime, the previous one being cricket. One guy throws a ball at another guy, but a guy in between those guys tries to hit that ball with a stick. If he does, a bunch of other guys try to catch the ball while the guy with the stick throws the stick away and runs in a circle. Then they do the whole thing over again, at least 55 times over the course of a game.
If the guy who throws the ball hits the guy with the sick in the head too many times, all the guys start punching each other. That's what happens when a bunch of grown men are shooting large quantities of steroids and growth hormone.
Sometimes the Conservatives send all the baseball players to war, and then girls have to play baseball instead. It's true.
In Britain the girls play a much gentler game called rounders that's similar to baseball.

subset: commoncrawl


text:
Doctor insights on:
Does Obesity Cause Other Digestive Problems
Does obesity cause other digestive problems?
Yes: Nonalcoholic steatohepatitis, gallstones and gastroesophageal reflux are all caused by obesity just to name a few things. If the obese patient develops diabetes then you can add gastroparesis into the mix too. ...Read more
Obesity (Definition)
The definition started with Louis Israel Dublin, chief statistician of the Metropolitan life insurance company, in the early 1940s, as a BMI >25 (definitely >30) for people in their 20's based on retrospective observational life insurance data of the age at which people died later in life. This was subsequently adopted by the medical disease industry. However, BMI is ...Read more
Digestive problems causes dizziness?
Sure: There are numerous ways digestive problems cause dizziness . If you vomit and unable to due or eat for a day or two you will be dizzy . If you have severe diarrhea and unable to replenish the loss you will feel dizzy since your blood pressure will be low due to the effective circulating blood volume will be low . There or dozens or reason you might feel dizzy from GI causes. ...Read moreSee 1 more doctor answer
Why do antibiotics cause me digestive problems?
Gut flora: Gets rid of gut flora. Recommend taking probiotics with it. ...Read moreSee 1 more doctor answer
Can stress and thinking too much cause digestive problems?
Absolutely: The digestive system is very sensitive to stress in many people. From top to bottom, symptoms can include nausea, lack of appetite, stomach pains, stomach gurgling, diarrhea or constipation. It's best to manage the stress itself; in the meantime you might try over-the-counter digestive aids like pepto-bismol. See a doctor if symptoms are severe or persist. ...Read moreSee 1 more doctor answer
What causes colitis, Crohn's disease and other digestive problems?
Unknown: While we don't entirely know what causes these, inflammatory bowel disease (ulcerative colitis and crohn's) appears to be caused by an autoimmune mechanism. There is a degree of genetic susceptibility, which seems to be higher in crohn's. However other theories, such as a virus as a cause, may also play a role. There are many other forms of colitis that may mimic these, and only a doctor can tell. ...Read more
Can the nerves from thorasic T11 thru l 2 cause digestive problems?
Nerve: The nerves that you are mentioning do not control the digestive system. The intestines and digestive has its own intrinsic nervous system that controls the motility of the bowels. ...Read more
Can not drinking enough water cause digestive problems? I am 32 yo male, 175lbs. How much should I be drinking?
Yes.: Not drinking enough water causes colon to maximally reabsorb water from stool in distal colon producing constipation. Minimum water intake is driven by obligatory losses which are 1600 ml/day. Minimum fluid intake is therefore 1600 ml per day divided among fluids - 500 cc/day, water in food - 800 cc/day and water derived from metabolism - 300 cc/day. Beating the minimum is a good idea. ...Read more
What digestive problems can anxiety and worry cause?
Anxiety/ worry: Nausea, emesis, constipation, loose stools, cramping ; change in bowel habitus. It can also effect conditions which you already have such as irritable bowel syndrome or ulcer. ...Read more
What could cause both thyroid and digestive problems?
Thyroid: Thyroid disorders are usually autoimmune on nature. Some GI issues are as well. These include gastritis, colitis, and celiac disease. Many can be screened by simple lab tests. See an endocrinologist. ...Read more
Can colitis cause complications with other digestive problems?
Please elaborate: Colitis is a non-specific term. There are many types of colitis. Which one do you have? For example ulcerative colitis is associated to many systemic other medical problems. ...Read moreSee 1 more doctor answer
- Talk to a doctor live online for free
- Does color blindness cause other health problems?
- Does lack of exercise cause problems with the digestive system?
- Does low sodium cause digestive problems?
- Ask a doctor a question free online
- How does the digestive system work with other systems?
- Could herpes cause other problems
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- Can a hernia cause digestive problems?
- Talk to a preventive medicine specialist online for free


text: You know I never thought he would be the choice. I always thought Texas would not go after him with what he wanted. What he wanted, from what I hear, is a life long percentage from the LHN and Texas was unwilling to do that. Had they agreed to that though, I think it would have been a done deal but it doesn't matter now. It's not denial, it's just the rumors that I have heard on what the issues were.


text:
Koolhaas Hat
if you don't mind cables, this is a great hat. You can do them without a cable needle.
if you don't mind cables, this is a great hat. You can do them without a cable needle.
I have seen a number of questions about "What is the best Provisional Cast-on" There is a question on the Ravelry Men Who Knit forum that I have been reading.
I'm a little confused by the terminology. It lists a "knit one front and back" as the same as a bar increase...? I know the bar as the yarn that runs between stitches, and a "make one" as pulling up that bar, twisting and knitting it (R or L as need be).
Hi all,
It's been quite a fall/early winter and I haven't been on much. At the end of September, I moved back to the US after 14 years in Turkey. I have been knitting here and there though,and as life settles down, I've slowly been getting back into old habits. :) Also enjoying some new ones!
After the challenge from michaelpthompson, I thought hard and long about how to do this. The other night, at 1 am when I sat down to watch "The Interview", I decided to do a sample. Doing it in your head is not always the same as actually doing it on the needles!
As soon as my son and his family left to go home to TN I began the scarf. I am making it for myself. The color is pecan from La Jolla "Baah" Original Hand Painted Yarn 100% Super wash Merino - Fingerling Weight 30 sts +4 inches. I am using Lantern Moon 3.5 mm/US4 sized needles. Jeffrey
Hi guys, I just wanted to share with you a little project I finished today. It's an octopus I made using a Hansi Singh pattern. I gotta say I'm kinda smitten with him!
Good Morning Guys,
I hope everyone has a wonderful Christmas and a fantastic New Year. Here's to completing projects, adding to the stash and having a great time with a craft that we all share. Glad for this community of knitting brothers.
Merry Christmas to all,
Evening Guys,
My next project will be the Socks Appeal Boxers by the Skacel Collection. I just cast on the 56 stitches required for the center back panel. I am using leftover yarn in my stash. Should be fun and easy. Mindless TV knitting while sitting with my wife while she is watching her shows. Hope you've all got your shopping done. JRob


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Thursday, January 24, 2013
By Keith M. Phaneufwww.ctmirror.org
For years, ideas such as regionalizing school calendars, reforming special education funding and other proposals to trim the cost of local government were given brief discussions at the state Capitol—though nothing more given to their controversial nature.
But since Connecticut's cities and towns may have to get by with less state funding in the next budget, the time for delicately avoiding politically sticky cost-cutting ideas is over, House Speaker J. Brendan Sharkey pledged today.
Addressing more than 100 state and municipal leaders and social service advocates at a state budget forum at the Capitol, the Hamden Democrat said the days of being able to hold cities and towns completely harmless while dealing with the state's fiscal woes likely are over.
"We have to fundamentally change the system by which we fund our local government," Sharkey told the crowd at the forum sponsored by Connecticut Voices for Children.
Click here for more of story
Posted 01/24/13 at 10:32 PM
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text:
Butler Specialty Masterpiece Bainbridge Olive Ash Burl Accent Table
$ 409.00
This elegant table blends classic Old World styling with today's casual sophistication. Crafted from hardwood solids, wood products and choice veneers, it is distinguished by a top starburst inlay pattern of maple and walnut veneers encompassed by an olive ash burl veneer border. Features beautifully carved fluted legs with a lower display shelf.
- Collection: Masterpiece
- Finish: Olive Ash Burl
- Color: Medium Brown
- Shape: Round
- Style: Traditional
- Material: Rubberwood solids, MDF, resin, Cherry, maple, walnut and/or olive ash burl veneers
- Dimensions: 28" w x 28" d x 28" h
- Cubes: 3.91
- Weight: 32 pounds


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Results from the 2014 AP Statistics Exam. Jessica Utts, University of California, Irvine Chief Reader, AP Statistics
- Lenard Stephens
- 2 years ago
- Views:
1 Results from the 2014 AP Statistics Exam Jessica Utts, University of California, Irvine Chief Reader, AP Statistics
2 The six free-response questions Question #1: Extracurricular activities on and off campus Comparing bar graphs, conclusion from p-value Question #2: Selecting conference attendees Probability, simulating probability Question #3: School attendance and funding Normal probability, probability for independent events Question #4: Alumni incomes Mean vs median, bias in surveys Question #5: Car purchase price for men vs women Paired t-test Question #6 (investigative task): Fuel consumption rate Residuals, choosing a new variable for prediction
3 Plan for each question State question Present solution Describe common student errors Suggest teaching tips Report average score (all at the end)
4 Question 1 Extracurricular activities Comparing bar graphs, conclusion from p-value
5 Question #1 An administrator at a large university is interested in determining whether the residential status of a student is associated with level of participation in extracurricular activities. Residential status is categorized as on campus for students living in university housing and off campus otherwise. A simple random sample of 100 students in the university was taken, and each student was asked the following two questions. Are you an on campus student or an off campus student? In how many extracurricular activities do you participate? The responses of the 100 students are summarized in the frequency table shown [next slide].
6 Question 1, continued Residential Status Level of Participation in Extracurricular Activities On campus Off campus Total No activities One activity Two or more activities Total (a) Calculate the proportion of on campus students in the sample who participate in at least one extracurricular activity and the proportion of off campus students in the sample who participate in at least one extracurricular activity. On campus proportion: Off campus proportion:
7 Question 1, continued The responses of the 100 students are summarized in the segmented bar graph shown. (b) Write a few sentences summarizing what the graph reveals about the association between residential status and level of participation in extracurricular activities among the 100 students in the sample. (c) After verifying that the conditions for inference were satisfied, the administrator performed a chi-square test of the following hypotheses. H 0 : There is no association between residential status and level of participation in extracurricular activities among the students at the university. H a : There is an association between residential status and level of participation in extracurricular activities among the students at the university. The test resulted in a p-value of Based on the p-value, what conclusion should the administrator make?
8 Question 1 Solution a) On campus: ; Off campus: b) The graph reveals that on campus residents in this sample are more likely to participate in extra-curricular activities than off campus residents. The proportions who participate in two or more extra-curricular activities are similar between the two groups although slightly larger for on campus residents (on campus: 0.212, off campus: 0.179). On campus residents have a greater proportion who participate in one activity (on campus: 0.515, off campus 0.373) and a smaller proportion who participate in no activities (on campus: 0.273, off campus: 0.448) than off campus residents.
9 Question 1 Solution, continued c) The p -value of 0.23 is larger than conventional significance levels such as 0.05 or Therefore, the p -value indicates that the sample data do not provide strong enough evidence to conclude that participation in extra-curricular activities differs between on and off campus residents in the population of all students at the university.
10 Question 1 Common Student Errors Part (a): Failure to show work, just giving decimal answer Part (b), errors resulting from poor communication: Lack of comparative language, giving a statement about one or both groups without comparing. Comparative language that doesn t mention both groups larger than or smaller than what? Using language implying counts instead of proportions more students instead of larger proportion of students. Part (c), language equivalent to accepting the null hypothesis: Accepting the null hypothesis as a stated decision. Giving a contextual conclusion equivalent to accepting the null. For example, There is no association between
11 Question 1 Teaching Tips Remind students to always show their work. No bald answers. Provide practice with comparisons based on visual displays. Differentiate between comparison of counts and proportions Teach the conceptual difference between fail to reject and accept the null hypothesis. (Never say accept the null hypothesis or the equivalent in context.) Always state the conclusion in context. Always link the p-value to a value of alpha to make a conclusion. It s not enough to say the p-value is 0.04 and alpha is 0.05 so reject the null hypothesis. Instead, say because the p-value of 0.04 is less than alpha of 0.05
12 Question 2 Selecting conference attendees Probability, simulating probability
13 Question #2, parts (a) and (b) Nine sales representatives, 6 men and 3 women, at a small company wanted to attend a national convention. There were only enough travel funds to send 3 people. The manager selected 3 people to attend and stated that the people were selected at random. The 3 people selected were women. There were concerns that no men were selected to attend the convention. (a) Calculate the probability that randomly selecting 3 people from a group of 6 men and 3 women will result in selecting 3 women. (b) Based on your answer to part (a), is there reason to doubt the manager s claim that the 3 people were selected at random? Explain.
14 Question 2 Solution, part (a) (a) The probability that all 3 people selected are women can be calculated using the multiplication rule, as follows: P(all three selected are women) = P(1 st is a woman) P(2 nd is a woman 1 st is a woman) P(3 rd is a woman 1 st and 2 nd are women) =
15 Question 2 (a) Common Student Errors The correct answer is based on sampling without replacement: = The most common error was computing the probability as if sampling with replacement: = Another common error:
16 Question 2 (a) Teaching Tips Provide students with practice in situations in which the assumption of independent observations is not reasonable. It may be that students are exposed to probability computations primarily in abstract situations (e.g., cards, dice) and do not see the connection to real-world situations. Teaching probability using such situations, even if contrived, may better help them understand how and why probabilities matter in real life.
17 Question 2 Solution, part (b) (b) The probability calculated in part (a) does provide a reason to doubt the manager s claim that the selections were made at random. The calculation shows that there is only about a 1.2% chance that random selection would have resulted in three women being selected. The probability is small enough that it may cast doubt on the manager s claim that the selections were made at random.
18 Question 2 (b) Common Student Errors Computed the wrong probability, and then said it was low because that s what they thought was expected: 0.34 is a very low probability (really?) The probability that he picked the three women at random is very low (wrong event) There is reason to doubt his claim because the probability is ( linkage missing) The probability is very low, so it shows the manager didn t really select them at random. (Too strong a conclusion) The probability is very low, but there s still a chance it could happen, so there s no reason to doubt the manager s claim. (Why do we do statistics?)
19 Question 2 (b) Teaching Tips Students need to understand better the logical structure of event would be unusual under Model X, so event occurrence should make us question Model X. Teach hypothesis testing not as a mechanical process, but as a logical structure. Play hypothesis testing games with them. Students need lots and lots of practice writing coherent logical arguments. This should not be done by having them fill in templates, but by having them write in words what they think they understand. Many, many times!
20 Question 2, part (c) (c) An alternative to calculating the exact probability is to conduct a simulation to estimate the probability. A proposed simulation process is described below. Each trial in the simulation consists of rolling three fair, six-sided dice, one die for each of the convention attendees. For each die, rolling a 1, 2, 3, or 4 represents selecting a man; rolling a 5 or 6 represents selecting a woman. After 1,000 trials, the number of times the dice indicate selecting 3 women is recorded. Does the proposed process correctly simulate the random selection of 3 women from a group of 9 people consisting of 6 men and 3 women? Explain why or why not.
21 Question 2 Solution, part (c) (c) No, the process does not correctly simulate the random selection of 3 women from a group of 9 people of whom three are women and six are men. The selection of three people among nine is done without replacement, but the simulation with dice simulates selecting three people with replacement, since the three dice rolls in any given trial are independent of one another.
22 Question 2 (c) Common Student Errors Failure to recognize dependence structure in the selection of people even when they got part (a) correct. Yes, the simulation works, because 2 6 = 3 9 No, because a die only has six sides and there are nine people. No, because the dice don t take into account sampling without replacement. (Need to be more explicit in their communication; this typically occurred in responses that were strong overall) No, because the trials are independent. You can t select the same person more than once. (Poor communication: what trials are we talking about?)
23 Question 2 (c) Teaching Tips Have students design and conduct their own simulations, and describe them in writing. Be sure students are exposed to simulations involving both dependence (as with sampling from a hat ) and independence (as with dice rolls). Juxtapose them and contrast them explicitly. The so-called 10 percent rule is a mystery for most students. Have them conduct simulations in situations when it is satisfied (so with and without replacement result are similar) and when it is not (so with and without replacement are different).
24 Question 3 School attendance and funding Normal probability, probability for independent events
25 Question #3, Part (a) Schools in a certain state receive funding based on the number of students who attend the school. To determine the number of students who attend a school, one school day is selected at random and the number of students in attendance that day is counted and used for funding purposes. The daily number of absences at High School A in the state is approximately normally distributed with mean of 120 students and standard deviation of 10.5 students. (a) If more than 140 students are absent on the day the attendance count is taken for funding purposes, the school will lose some of its state funding in the subsequent year. Approximately what is the probability that High School A will lose some state funding?
26 Question 3, Part (a) Solution Because the distribution of the daily number of absences is approximately normal with mean 120 students and standard deviation 10.5 students, the z- score for an absence total of 140 students is z = The table of standard normal probabilities or a calculator reveals that the probability that 140 or fewer students are absent is So the probability that more than 140 students are absent and, therefore, the school will lose some state funding is =
27 Question 3 (a) Common Student Errors 1. Lack of Communication o Not identifying that the Normal distribution is being used. o Not identifying the parameter values o Omitting z in a z-score equation o Inadequate sketch to get credit 2. Reversing x and µ in the z-score equation 3. Using Table A incorrectly looking at 1.95 instead of 1.905
28 Question 3 (a) Teaching Tips Remind students to: 1. To identify the type of distribution to list and identify the parameters. 2. Label values when using calculator syntax. 3. Use the formula and show your work in a z-score calculation (include the z ) z = value mean S.D. 4. Sketch a normal curve and shade the area to help estimate the probability being computed.
29 Question 3, Part (b) (b) The principals association in the state suggests that instead of choosing one day at random, the state should choose 3 days at random. With the suggested plan, High School A would lose some of its state funding in the subsequent year if the mean number of students absent for the 3 days is greater than 140. Would High School A be more likely, less likely, or equally likely to lose funding using the suggested plan compared to the plan described in part (a)? Justify your choice.
30 Question 3 Part (b) Solution High School A would be less likely to lose state funding. With a random sample of 3 days, the distribution of the sample mean number of students absent would have less variability than that of a single day. With less variability, the distribution of the sample mean would concentrate more narrowly around the mean of 120 students, resulting in a smaller probability that the mean number of students absent would exceed 140. In particular, the standard deviation of the sample mean number of absences is 12.5 = so the z-score for a sample mean of 140 is z = The probability that High School A loses funding using the suggested plan would be = as determined from the table of standard normal probabilities or from a calculator, which is less than a probability of obtained for the plan described in part (a)
31 Question 3 (b) Common Student Errors 1. Lack of Communication o Not explicitly communicating that the sampling distribution of the mean is appropriate o Did not answer the question AND/OR justify o No comparison of probabilities 2. Answering (.0287) 3, because each day must have more than 140 absences for the mean to be > CLT does not apply for a sample size of n=3.
32 Question 3 (b) Teaching Tips Make sure the question is answered AND justified (explain why) less likely because... Emphasize the difference between the distribution of a population and a sampling distribution Using a well-labeled sketch would be an effective method to communicate the difference in distributions (one day versus mean of 3 days)
33 Question 3, Part (c) (c) A typical school week consists of the days Monday, Tuesday, Wednesday, Thursday, and Friday. The principal at High School A believes that the number of absences tends to be greater on Mondays and Fridays, and there is concern that the school will lose state funding if the attendance count occurs on a Monday or Friday. If one school day is chosen at random from each of 3 typical school weeks, what is the probability that none of the 3 days chosen is a Tuesday, Wednesday, or Thursday?
34 Question 3 Part (c) Solution For any one typical school week, the probability is 2/5 = 0.4 that the day selected is not a Tuesday, Wednesday, or Thursday. Therefore, because the days are selected independently across the three weeks, the probability that none of the three days selected would be a Tuesday or Wednesday or Thursday is (0.4) 3 = This is equivalent to finding a binomial probability of 3 successes in 3 trials (weeks) when the probability of a success (no Tues, Wed, Thurs) is 0.4 on each trial.
35 Question 3 (c) Common Student Errors 1. P(None) = 1 P(All) 2. Used the Binomial with n= 5 or 15.
36 Question 3 (c) Teaching Tips 1. Practice easier probability problems. 2. Recognize independence. Remind students that: 3. Probabilities >1 are not a good thing. 4. Make sure the answer you get makes sense.
37 Question 4 Alumni incomes Mean vs median, bias in surveys
38 Question #4 As part of its twenty-fifth reunion celebration, the class of 1988 (students who graduated in 1988) at a state university held a reception on campus. In an informal survey, the director of alumni development asked 50 of the attendees about their incomes. The director computed the mean income of the 50 attendees to be $189,952. In a news release, the director announced, The members of our class of 1988 enjoyed resounding success. Last year s mean income of its members was $189,952! (a) What would be a statistical advantage of using the median of the reported incomes, rather than the mean, as the estimate of the typical income?
39 Question 4, continued (b) The director felt the members who attended the reception may be different from the class as a whole. A more detailed survey of the class was planned to find a better estimate of the income as well as other facts about the alumni. The staff developed two methods based on the available funds to carry out the survey. Method 1: Send out an to all 6,826 members of the class asking them to complete an online form. The staff estimates that at least 600 members will respond. Method 2: Select a simple random sample of members of the class and contact the selected members directly by phone. Follow up to ensure that all responses are obtained. Because method 2 will require more time than method 1, the staff estimates that only 100 members of the class could be contacted using method 2. Which of the two methods would you select for estimating the average yearly income of all 6,826 members of the class of 1988? Explain your reasoning by comparing the two methods and the effect of each method on the estimate.
40 Question 4 Solution (a) The median would be less affected by skewness and outliers than the mean. With a variable such as income, a small number of very large incomes could dramatically increase the mean but not the median. Therefore, the median would be more likely than the mean to provide a better estimate of a typical income value. (b) Method 2 is better than Method 1. Method 1 could be biased because it seems plausible that class members with larger incomes would be more likely to return the form than class members with smaller incomes. The mean income in this sample is likely to overestimate the mean income of all class members. With Method 2, despite the smaller sample size, the random selection is likely to result in a sample that is more representative of the entire class and also to produce an unbiased estimate of mean yearly income of all class members.
41 Question 4 (a) Common Student Errors Many students provided only a generic statement describing how outliers and skewness affect the mean or don t affect the median without referencing the distribution of incomes. Using the variable name (income) wasn t enough to earn credit. It had to be clear that the student was relating a statement about the effect of skewness or outliers to the fact that the distribution of incomes may be skewed or have outliers. Some students didn t describe the effect of skewness or outliers on the mean/median. Instead, they included statements such as use the median when there are outliers without explaining why they should use the median. Many students are sloppy with their language, saying things such as outliers will skew the mean or means are biased when there is skewness.
42 Question 4 (a) Teaching Tips Responses should address the context of the problem in a meaningful way. Always justify your choice with a reason. Don t use statistical terms (bias, skew, and so on) unless you use them correctly.
43 Question 4 (b) Common Student Errors Using incorrect names for describing the problem with nonresponse in Method 2, such as response bias Naming but not describing the bias was another error. Choosing Method 2 and providing good reasons not to choose Method 1, but never providing any evidence that Method 2 was better. Some students didn t explicitly choose a method Some students chose Method 1, ignoring nonresponse bias, focusing on sample size. Many students discussed possible problems with Method 2, including potential nonresponse. However, the question said that all responses would be obtained in Method 2.
44 Question 4 (b) Common Student Errors (cont.) Many, many students did not address the effect of the bias on the estimated mean, even though this was specifically asked for in the question. When trying to address the effect on the estimate, many students used ambiguous phrases such as the results will be more accurate. It was unclear what students meant by more accurate other than the results will be better. Some students discussed the conditions for inference when choosing Method 1 or Method 2. Although it is reasonable to consider the conditions for inference when choosing a data collection method, many students made incorrect statements in the process, such as large samples mean that the sample data will be normal or a SRS means that we can apply the Central Limit Theorem.
45 Question 4 (b) Teaching Tips Worry less about memorizing labels and more about describing the concept. Always gives reasons why you are choosing what you re choosing, and reasons why you are not choosing what you are not choosing. Answer the question, and always in context. Don t over-think it. Remind students that sample size is important, but it isn t the only concern. Using a biased sampling method with a larger sample size makes it less likely that the parameter value is within the margin of error of the estimate. Also, make sure students understand the difference between accuracy and precision. Don t allow your students to use phrases with statistical meaning in a casual way. Make sure students understand when they should address the conditions for inference and why these conditions need to be checked.
46 Question 5 Car purchase price for men vs women Paired t-test
47 Question #5 A researcher conducted a study to investigate whether local car dealers tend to charge women more than men for the same car model. Using information from the county tax collector s records, the researcher randomly selected one man and one woman from among everyone who had purchased the same model of an identically equipped car from the same dealer. The process was repeated for a total of 8 randomly selected car models. The purchase prices and the differences (woman man) are shown in the table on the next page. Summary statistics are also shown. Do the data provide convincing evidence that, on average, women pay more than men in the county for the same car model?
48 Question 5, continued
49 Question 5 Solution Notice that the data are paired because each car model in the study includes one purchased by a man and one purchased by a woman. Step 1: States a correct pair of hypotheses Let µ Diff represent the population mean difference in purchase price (woman man) for identically equipped cars of the same model, sold to both men and women by the same dealer, in this county. The hypotheses to be tested are H 0 : µ Diff = 0 versus H a : µ Diff > 0. Step 2: Identifies a correct test procedure (by name or by formula) and checks appropriate conditions. Paired t-test Randomly selected sample (explain) Small n, so check dotplot for extreme skew and/or outliers OK
50 Question 5 Solution, continued Step 3: Correct mechanics, including the value of the test statistic and p-value (or rejection region) t = The p-value, based on a t-distribution with df = 8 1 = 7 is Step 4: States a correct conclusion in the context of the study, using the result of the statistical test. Because the p-value is very small (for instance, smaller than α = 0.05), we reject the null hypothesis. The data provide convincing evidence that, on average, women pay more than men in the county for the same car model.
51 Question 5 Common Student Errors Not doing a test at all just doing descriptive analysis Doing a two-sample t-test Defining parameter incorrectly Verifying conditions: It s not clear that students understand what they are trying to verify, or why Using z procedures with unknown σ Incorrect formulas for test statistic; improper notation Accepting or retaining the null; proving the alternative Adding a p-value interpretation to the conclusion and doing it wrong
52 Question 5 Teaching Tips Practice identifying the appropriate inference procedure for a given research question. Stress that design determines analysis. Advice to students: Don t waste time typing data into your calculator when summary statistics are provided Have students use the same inference framework every time Don t teach inference for a mean using z procedures Provide extra information on some questions so that students have practice filtering out what s important/relevant Stress that there are only two decisions one can make about the null hypothesis based on the data: reject H 0 or fail to reject H 0. Insist on a conclusion in context that addresses strength of evidence for H a and that includes the parameter(s) of interest.
53 Question 6 Fuel consumption rate Residuals, choosing a new variable for prediction
54 Question #6, parts (a) and (b) Jamal is researching the characteristics of a car that might be useful in predicting the fuel consumption rate (FCR); that is, the number of gallons of gasoline that the car requires to travel 100 miles under conditions of typical city driving. The length of a car is one explanatory variable that can be used to predict FCR. Graph I is a scatter plot showing the lengths of 66 cars plotted with the corresponding FCR. One point on the graph is labeled A. Jamal examined the scatterplot and determined that a linear model would be a reasonable way to express the relationship between FCR and length. A computer output from a linear regression is shown below. [To the right.]
55 Question 6ab, continued (a) The point on the graph labeled A represents one car of length 175 inches and an FCR of Calculate and interpret the residual for the car relative to the least squares regression line. Jamal knows that it is possible to predict a response variable using more than one explanatory variable. He wants to see if he can improve the original model of predicting FCR from length by including a second explanatory variable in addition to length. He is considering including engine size, in liters, or wheel base (the length between axles), in inches. Graph II is a scatterplot showing the engine size of the 66 cars plotted with the corresponding residuals from the regression of FCR on length. Graph III is a scatterplot showing the wheel base of the 66 cars plotted with the corresponding residuals from the regression of FCR on length.
56 Question #6ab, continued (b) In graph II, the point labeled A corresponds to the same car whose point was labeled A in graph I. The measurements for the car represented by point A are given below. (i) Circle the point on graph III that corresponds to the car represented by point A on graphs I and II. (ii) There is a point on graph III labeled B. It is very close to the horizontal line at 0. What does that indicate about the FCR of the car represented by point B?
57 Question 6ab Solution (a) For a car with length 175 inches, the predicted value for the car s FCR, based on the least squares regression line, is Predicted FCR = (175) 4.92 gallons per 100 miles The actual FCR for the car is 5.88, so the residual is = The residual value means that the car s FCR is 0.96 gallons per 100 miles greater than would be predicted for a car of its length. (b) (i) See circled point. (b) (ii) Point B corresponds to a car with an actual FCR that is very close to the FCR that would be predicted for a car with its length.
58 Question 6ab, Common Student Errors Part (a) Successes and Mistakes: Many students successfully calculated and interpreted the residual value. Context was seldom missing in the interpretation. away from the predicted value was not good enough need direction. Magnitude (.96) was missing in some students interpretation. Part (b) Successes and Mistakes: Almost all students circled the point correctly. It was important that the response described the FCR of the car corresponding to the point B being close the predicted FCR using the regression of FCR based on length (not wheel base a major mistake).
59 Question 6, parts c, d (c) Write a few sentences to compare the association between the variables in graph II with the association between the variables in graph III. (d) Jamal wants to predict FCR using length and one of the other variables, engine size or wheel base. Based on your response to part (c), which variable, engine size or wheel base, should Jamal use in addition to length if he wants to improve the prediction? Explain why you chose that variable.
60 Question 6 Solution, parts c, d (c) Graph II reveals an association that is positive and moderately linear. In contrast, there is a weak positive, or no, linear association in graph III. The association between engine size and residual (from predicting FCR based on length) is stronger than the association between wheel base and residual (from predicting FCR based on length). (d) Engine size is a better choice than wheel base for including with length in a regression model for predicting FCR. The stronger association between engine size and residual (from predicting FCR based on length) indicates that engine size is more useful than wheel base for reducing variability in FCR values that remains unexplained (as indicated by residuals) after predicting FCR based on length.
61 Question 6cd, Common Student Errors Part (c) Successes and Mistakes: Many students misinterpreted the two graphs as residual plots from the regression of FCR based on engine size and wheel base instead of the residuals of FCR based on length plotted against variables engine size and wheel base. This misinterpretation invariably led to the incorrect choice of wheel base in part (d). Scoring on part (c) was focused on the comparisons of the associations in the graphs (as directed by the stem of question). However, an incorrect description of the variables and/or the graphs was unacceptable. For graph II, it was necessary to use the word linear when describing the form. Correlation is not synonymous with linear
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text:
Learn more about WIDNES MASONIC HALL LIMITED(THE). Check the company's details for free and view the Companies House information, company documents and list of directors.
Know about every new company document that is added!
Take advantage of our watch this company feature free of charge and have notifications sent directly to your inbox. Whenever a new document appears on this website, or if their particulars change, you will be immediately informed about such changes. To monitor these changes, all you need to do is click on watch this company.
|Fixed Assets
|£ 3,500,000
|Tangible Fixed Assets
|£ 3,500,000
|Current Assets
|£ 7,011
|£ 1,953
|Shareholder Funds
|£ 3,505,974
|Profit Loss Account Reserve
|£ 3,480,974
|Called Up Share Capital
|£ 25,000
|Net Assets Liabilities Including Pension Asset Liability
|£ 3,505,974
|Total Assets Less Current Liabilities
|£ 3,505,974
|Net Current Assets Liabilities
|£ 5,974
|Creditors Due Within One Year
|£ 1,037
|Cash Bank In Hand
|£ 3,408
|Stocks Inventory
|£ 1,650
|Share Capital Allotted Called Up Paid
|£ 25,000
|Par Value Share
|1.00 1.00
|Number Shares Allotted
|£ 25,000
|Tangible Fixed Assets Cost Or Valuation
|£ 3,500,000
Information about the Private Limited Company WIDNES MASONIC HALL LIMITED(THE) has been prepared for information purposes only. It is not intended to be nor does it constitute legal advice. This is public information provided by the official company register.


text:
|452 sq. ft.
|Property type
|Minimum Stay
|3 nights
The Surf Studios are situated on the Ground Floor with a terrace in front.
There is a full Bathroom and fully kitted kitchenette.
There is a Lounge/Dining room with a full double pull down bed
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Plus New Showers.
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To secure a reservation,a depoist of 20% is reqiured.(non refundable).The remainder being due six weeks prior to arrival.(non refundable)We advise taking out adequate insurance.
Payment can be by Credit Card, Bank Transfer ,PayPal, Cheque or Cash.
For further details on prices and up to date availabilty please contact us by
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or e-mail email@example.com.
Nette und zuverlässige Eigentümer
Schöne und ruhige Umgebung
Strand ist super
Allerdings ist das Bett nicht für jemanden der schlecht schläft: alt, quietscht bei jeder Bewegung, mega harte Matratzen
Praia da Luz is situated on Portugal's Algarve coast.
5 Kms West of Lagos lies the beautiful Beach Resort of Praia da Luz.
Once a thriving fishing village it now hosts visitors from all over the World wanting to enjoy its Beautiful Safe Sandy Beach.
Praia da Luz is a whitewashed village with low rise development.
There are many Shops, Restaurants, Cafes and Bars to suit all tastes and pockets.
Other facilities are a Post Office, Banks, Clinic and a Central Church.
From the Beach many Water-Sports can be enjoyed.
The nearest Golf Course is only 5 Minutes away.
The Historic Town of Lagos, with its bustling Marina, Shops Restaurants, Cafes and Bars is only 5 Kms away.
Other Activities: Jeep Safaris, Dolphin Trips, Various Boat Trips
Golf: The Algarve is a haven for Golfers.
We have five Golf Courses within a 20 Minuite Drive.
The nearest is Boavista only five minuites away.


text:
You purchased your Xterra because its fuel efficiency and economical pricing appealed to your senses; so why would you settle for anything but the best when it comes to the highest quality auto parts? Anyone who owns a Nissan knows that when it comes to maintaining their vehicle only the highest quality replacement parts will do. Auto enthusiasts know that a sporty attitude is built into each Nissan, and understand that only the best repair Xterra parts will suffice when maintenance needs to be done. When your Nissan Xterra rolled off the assembly line, it was destined for a driver who prioritizes long-lasting quality in their automobile.
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