The following scenario is the information necessary to answer questions 1-12.

SCENARIO: 1236 Marine recruits entered training during one week in June. Marine recruits are medically examined and must be injury and illness free before beginning training. 112 refused to participate in a study to follow them during 12 weeks of training for the development of stress fractures. All recruits who consented to participate (everyone but those who refused to participate) were successfully followed for all 12 weeks. During the 12 weeks, 55 recruits developed a stress fracture. Of these 55, 26 subjects suffered stress fractures in the first 6 weeks and each of these 26 were fully recovered within 5 weeks. The shortest recovery time among those suffering stress fractures after week 6 was 7.5 weeks. At the beginning of training it was determined that 20% of participants were classified as being in “poor physical fitness.” The remaining recruits were in “better than poor physical fitness.” The incidence of stress fractures in the poor physical fitness group was 9.8%.

Hint: you may want to “draw” a timeline of the 12 week follow-up period to better understand prevalence and incidence of stress fractures over that time period.

1. What is the size of the study group?
2. What is the stress fracture incidence?
3. What is the stress fractures incidence rate?
4. What is absolute risk of stress fracture during training?
5. What is the prevalence rate of stress fractures at the beginning of training (1st day of training)?
6. What is the prevalence rate of stress fractures at the end of training?
7. Create a 2X2 table for stress fracture given physical fitness group?
8. What is the incidence rate of stress fractures among the better than poor physically fit recruits?
9. What PERCENT of stress fractures in the poor fit group could be reduced by increasing fitness to better than poor?
10. Among all recruits, what percent of stress fractures could be reduced by increasing fitness to better than poor?
11. What is the relative risk for stress fracture if a recruit is in poor fitness?
12. What is the interpretation of this relative risk?

The following scenario is the information necessary to answer questions 13-19.

SCENARIO: In National City they have begun a new initiative to reduce the effects of risky sexual behavior among the 150,000 residents. 33% of the population is between 1-14 years old, 20%, 15-21 years old, 30%, 22-40 years old, and 17% older than 41. Chlamydia is the most common sexually transmitted disease with a duration that can vary from a few days to many months. Before the program began, 145, 15-21 year olds were diagnosed with chlamydia in 1996. 145 people aged 22-40 were also diagnosed with chlamydia in the same year. 16 people aged 15-40 died from chlamydia in 1996. A total of 345 people of all ages were diagnosed with chlamydia during 1996.

In 1997 a sample of 3500 National City residents were recruited into a study . Each subject was asked about their current sexual behavior and each person’s medical record was reviewed for diagnosis of chlamydia at the time of enrollment in 1997. 37 individuals from the sample had documentation of chlamydia of which 35% claimed to never use condoms during the same time period. Condom use in the entire sample was reported by 62% of the subjects.

13. What was the crude prevalence rate for chlamydia for 1996 in National City?

14. What was the age-specific chlamydia rate for 15-21 year olds in National City in 1996? For 22-40 year olds?

15. What age group seems to have the highest problem with chlamydia, 15-21 or 22-40?

16. What is the chlamydia case fatality rate for 15-40 year olds in 1996?

17. Fill in the 2X2 table for chlamydia vs condom use in the sample in 1997?

18. Does condom use appear to be associated with chlamydia diagnosis in the 1997 study? Yes or no.

19. Was there a positive or negative association of condom use with chlamydia diagnosis?

USE THIS DOCUMENT FOR SUBMITTING ANSWERS: (I attached a file for the answers)

Assignment: Assessment

The testing of assumptions, recognition of limitations, and proper use of diagnostics are all necessary elements in the use of multiple linear regression for public health research. All of these elements allow biostatisticians to better assess the results of multiple linear regression models.

For this Assignment, you test that assumptions for multiple linear regression have been met, use SPSS to create a multiple linear regression, evaluate results to determine whether the model is appropriate, and finally interpret the relationships uncovered through this statistical test between the independent and dependent variables. Use the Week 4 Dataset (SPSS document) from the Learning Resources area to complete this assignment.

The Assignment

1. Explain the assumptions of Linearity, Sampling independence, Normality, and Homoscedasticity (or equal variance). (30 points)
   1. How would you test whether these have been met? (Note: for the exam you do not need to test these assumptions)
   2. Using SPSS, test the assumption of Linearity between the independent and dependent variables.
   3. Using SPSS, test the assumption of Normality for the dependent variable.
2. Conduct a multiple linear regression using SPSS. Provide relevant SPSS output and assess the statistical significance of the effects of mother’s Age, BMI, and Coffee (Cups per Day) on Birth weight. (30 points)
3. Explain the practical implications of your finding. Include a reference to the R square of the model in your discussion. (20 points)
4. Discuss whether or not there is interaction (effect modification) first between Age and BMI and second between BMI and Coffee. (20 points)

Find P(Z ≥ 1.8). Round answer to 4 decimal places. Answer:

Question 2 (1 point)

I need help with a Statistics question. All explanations and answers will be used to help me learn.

Tell us about your chosen career (nursing). Identify three variables, one qualitative and two quantitative, that would be vital for your responsibilities in your chosen career. Select two quantitative variables that you believe are related in some way (think correlation).

Please answer these questions for this assignment:

• How you would collect the data?
• What permission(s) you need to conduct the data collection?
• What sample size is appropriate and possible?
• What measures of central tendency and dispersion would be appropriate?
• What tables and graphs could be used to represent the data?
• Why would you choose to collect these variables?
• What relationship do you believe exists between the two quantitative variables? Why?

I’m working on a statistics discussion question and need support to help me understand better.

1. Use google to find a problem for a hypothesis test  for one proportion such as the one below.  (It is the same one as the  introduction)  Make sure you solve your own problem this week… I need the information.

Example-  How cool is Facebook?  In a recent GenX2Z American College Student  Survey, 90% of female college students rated the social network site  Facebook as “cool.”  The other 10% rated it as “lame.”  Assume that the  survey was based on a sample of 500 students.  A marketing executive at  Facebook wants to advertise the site with the slogan “More than 85% of  female college students think Facebook is cool.”  Can he conclude that  the proportion of female college students who think Facebook is cool is  greater than 0.85?

2 .Pick another student’s problem and solve it. Make sure to include  your null and alternative hypothesis, your test statistic, your p-value,  decision, and conclusion in the context in your response. 

Another student problem : Game consoles: A poll taken by the Software Usability Research  Laboratory surveyed 341 video gamers, and 110 of them said that they  prefer playing games on a console, rather than a computer or hand-held  device. An executive at a game console manufacturing company claims that  more than 25% of gamers prefer consoles. Does the poll provide  convincing evidence that the claim is true? Use the ? = 0.01 level of  significance.

Student problem should be this : A nationwide survey of working adults indicates that only 50% of them are satisfied with their jobs. The president of a large company believes that more than 50% of employees at his company are satisfied with their jobs. To test his belief, he surveys a random sample of 100 employees, and 54 of them report that they are satisfied with their jobs. Can he conclude that more than 50% of employees at the company are satisfied with their jobs? Use the ? = 0.05 level of significance.

I’m working on a statistics multi-part question and need an explanation to help me learn.

Hello,

In week’s one and two, we looked at the history of psychological assessment and factors that contribute to a testing being a good test (i.e., reliability, validity, ethics, etc.). In week 3, we explore what makes a test useful and use that to determine methods for test construction. Respond to the following questions in a substantive way integrating information from your text or other scholarly sources (please include citations and references for your work):

1. How would you go about making a judgment regarding the utility of a published test? What factors would you consider? What resources would you use?

2. What factors concerning test utility would you consider as you work through the process of test construction?

3. What are factors that need to be considered early in test construction to insure that the process proceeds accurately and you end up with a useful test?

4. Consider that you are constructing a test on test anxiety, what are some examples of items you would include in an assessment of an individual’s level of test anxiety? How would you determine which items should be included in the assessment? How would you evaluate the appropriateness of your items and each item’s performance in the assessment?

After reading the example above where one can see how probability values can be used in managerial decision-making to establish a product guarantee, post a comment where you think probability could be used to help solve other management-type questions/problems. Think of something at work, past or present, where you could apply the techniques in the example to assist in making the best decision. If you can’t draw on life experience, then think of a product/issue where this process could be applied. Please explain your answer. Remember to cite your resources and use your own words in your explanation.

Step 1: Read

• Review Case Problem 2: Predicting Winnings for NASCAR Drivers
• from Chapter 15 of the ebook.

Step 2: Do

• Run a Regression for the Data File NASCAR (Chapter 15) using the video How to Add Excel’s Data Analysis ToolPak (Links to an external site.) for assistance.

In a managerial report,

• Suppose you wanted to predict Winnings ($) using only the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), or the number of top ten finishes (Top 10). Which of these four variables provides the best single predictor of winnings?
• Develop an estimated regression equation (look at Equation 15.6 in our textbook as an example) that can be used to predict Winnings ($) given the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), and the number of top ten (Top 10) finishes. Test for individual significance, and then discuss your findings and conclusions.

Step 3: Discuss:

• What did you find in your analysis of the data? Were there any surprising results? What recommendations would you make based on your findings? Include details from your managerial report to support your recommendations.

I have a 3-5 question pre-calculus timed homework that is due at 4pm. I
will need help answering them in real time. My questions must be
answered within 30 mins.