Category: statistics assignment

What do you consider to be the difference between independent t-test and dependent t-test?

What non-parametric statistical analysis can you use if the data do not meet the assumptions of parametric analysis.

When do you use ANOVA?

If you cannot identify where the differences occur in groups,  What statistical procedure  can you apply?

The youth risk behaviors reference will still need citrix to open it. have also attached other references and the rubrics. Let me know please, this work is due next week by tuesday

In public health, data are often gathered from separate groups in order to describe health-related behavior for a topic of interest. In practice, a larger sample is often surveyed, and then focus groups or interviews can be conducted with a smaller subset of the sample. The quantitative survey data from a larger group helps to identify health-related trends and patterns within the sample group. The qualitative data collected with the smaller group complements the quantitative survey data and helps to determine why and how a phenomenon exists. The cumulative findings can then help public health professionals form a conclusion about the health issue and inform future public health research, policy, and practice.

The purpose of this assignment is to analyze qualitative and quantitative data from two separate groups, propose a research question, and then disseminate your findings in a mixed-methods manuscript. The survey and focus group are both on the topic of nutrition. The quantitative data is adapted from the Youth Risk Behavior Surveillance System (YRBSS), and the qualitative data is from a focus group transcript in which 9th grade girls discussed healthy eating.

For this assignment, you will use:

1. IBM SPSS Statistics and the “Youth Risk Behavior Surveillance System Dataset” to conduct a basic quantitative statistical analysis.
2. The “9th Grade Girls Healthy Food Focus Group Transcription” to conduct a qualitative analysis and identify key themes.

Part 1: Analyzing Data

Using the resources indicated above, conduct the following analyses and record the results on the “Results and Outputs” template. Attach this document as an Appendix in your paper.

Qualitative Analysis: Read the “9th Grade Girls Healthy Food Focus Group Transcription.” This transcript is from a focus group of 9th grade girls discussing healthy eating with the moderator. Generate codes and summarize the qualitative data.

Quantitative Analysis:

1. Review the “Youth Risk Behavior Surveillance System Dataset.” Identify two or three variables of interest and identify a study topic for your paper. Conduct a literature search for three to five peer-reviewed articles from the last 5 years that have studies supporting your topic. Develop a research question for your study based on the selected variables. The research question should demonstrate support for the focus group results and should be supported by existing literature.
2. Prepare the data to complete the analysis based on your research question.
3. Using SPSS, conduct descriptive statistics to summarize the sample.
4. Using SPSS, select an appropriate quantitative inferential statistical test to analyze the data.

Part 2: Reporting Data

Prepare a 1,250-1,500 word manuscript to disseminate the findings of your proposed study. The study should be based on your proposed research question and supported by the findings from the qualitative and quantitative analyses above, as well as by current literature. Include the following:

Abstract

1. A 150-250 word summary of the manuscript.

Introduction

1. Summarize the purpose of the research, the problem being addressed, and your proposed research question.
2. Support your summary using three to five peer-reviewed articles from the last 5 years that are relevant to your topic and that support why the study is being conducted.

Methods

Qualitative Methods (Focus Group)

1. Describe the focus group sample and data collection process.
2. Describe the process used to analyze the qualitative data.

Quantitative Methods (YRBSS Survey)

1. Discuss how the data were collected.
2. Identify and describe the variables used in the analysis.
3. Describe the descriptive and inferential statistical tests that were conducted.
4. Identify the software that was used to conduct the analysis.

Results

Qualitative Results (Focus Group)

1. Summarize the results of the qualitative analysis from the “9th Grade Girls Healthy Food Focus Group Transcription.”

Quantitative Results (YRBSS Survey)

1. Summarize the sample using the results of the descriptive statistics.
2. Describe the main outcomes of the inferential statistical analysis.
3. Include at least one table or figure to support the results.

Discussion

1. Interpret the study results in relation to the related literature and study purpose.
2. Discuss the study limitations.
3. Based on the interpreted results of the study, provide recommendations for future public health research, policy, or practice.

Appendix

1. “Results and Outputs” analysis document.

General Requirements

You are required to cite to a minimum of three sources to complete this assignment. Sources must be published within the last 5 years and appropriate for the assignment criteria and public health content.

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

Benchmark Information

This benchmark assignment assesses the following programmatic competencies:

Master Public Health

2.2: Select quantitative and qualitative data collection methods appropriate for a given public health context. 

2.3: Analyze quantitative and qualitative data using biostatistics, informatics, computer-based programming, and software, as appropriate. 

2.4: Interpret results of data analysis for public health research, policy, or practice.

MSN Public Health Nursing

6.3: Interpret results of data analysis for public health research, policy, or practice.

 

Complete the following exercises located at the end of each chapter and put them into a Word document to be submitted as directed by the instructor.

Show all relevant work; use the equation editor in Microsoft Word when necessary.

1. Chapter 5, numbers 5.11, 5.13, 5.15, and 5.18

2. Chapter 8, numbers 8.10, 8.14, 8.16, 8.19, and 8.21

 

5.11 Scores on the Wechsler Adult Intelligence Scale (WAIS) approximate a normal curve with a mean of 100 and a standard deviation of 15. What proportion of IQ scores are

(a) above Kristen’s 125?

(b) below 82?

(c) within 9 points of the mean?

(d) more than 40 points from the mean?

 

5.13 IQ scores on the WAIS test approximate a normal curve with a mean of 100 and a standard deviation of 15. What IQ score is identified with

(a) the upper 2 percent, that is, 2 percent to the right (and 98 percent to the left)?

(b) the lower 10 percent?

(c) the upper 60 percent?

(d) the middle 95 percent? [Remember, the middle 95 percent straddles the line perpendicular to the mean (or the 50th percentile), with half of 95 percent, or 47.5 percent, above this line and the remaining 47.5 percent below this line.]

(e) the middle 99 percent?

 

IMPORTANT NOTE: When doing Questions 5.15 and 5.16, remember to decide first whether a proportion or a score is to be found.

*5. 15 An investigator polls common cold sufferers, asking them to estimate the number of hours of physical discomfort caused by their most recent colds. Assume that their estimates approximate a normal curve with a mean of 83 hours and a standard deviation of 20 hours.

(a) What is the estimated number of hours for the shortest-suffering 5 percent?

(b) What proportion of sufferers estimate that their colds lasted longer than 48 hours?

(c) What proportion suffered for fewer than 61 hours?

(d) What is the estimated number of hours suffered by the extreme 1 percent either above or below the mean?

(e) What proportion suffered for between 1 and 3 days, that is, between 24 and 72 hours?

(f) What is the estimated number of hours suffered by the middle 95 percent? [See the comment about “middle 95 percent” in Question 5.13(d).]

(g) What proportion suffered for between 2 and 4 days?

(h) A medical researcher wishes to concentrate on the 20 percent who suffered the most. She will work only with those who estimate that they suffered for more than ——— hours.

(i) Another researcher wishes to compare those who suffered least with those who suffered most. If each group is to consist of only the extreme 3 percent, the mild group will consist of those who suffered for fewer than _____ hours, and the severe group will consist of those who suffered for more than _____ hours.

(j) Another survey found that people with colds who took daily doses of vitamin C suffered, on the average, for 61 hours. What proportion of the original survey (with a mean of 83 hours and a standard deviation of 20 hours) suffered for more than 61 hours?

(k) What proportion of the original survey suffered for exactly 61 hours? (Be careful!)

 

*5.18 The body mass index (BMI) measures body size in people by dividing weight (in pounds) by the square of height (in inches) and then multiplying by a factor of 703. A BMI less than 18.5 is defined as underweight; between 18.5 to 24.9 is normal; between 25 and 29.9 is overweight; and 30 or more is obese. It is well established that Americans have become heavier during the last half century. Assume that the positively skewed distribution of BMIs for adult American males has a mean of 28 with a standard deviation of 4.

(a) Would the median BMI score exceed, equal, or be exceeded by the mean BMI score of 28?

(b) What z score defines overweight

(c) What z score defines obese

 

8.10 Television stations sometimes solicit feedback volunteered by viewers about a tele-vised event. Following a televised debate between Barack Obama and Mitt Romney in the 2012 presidential election campaign, a TV station conducted a telephone poll to determine the “winner.” Callers were given two phone numbers, one for Obama and the other for Romney, to register their opinions automatically.

(a) Comment on whether or not this was a random sample.

(b) How might this poll have been improved?

 

*8.14 The probability of a boy being born equals .50, or 1/2, as does the probability of a girl being born. For a randomly selected family with two children, what’s the probability of

(a) two boys, that is, a boy and a boy? (Reminder: Before using either the addition or multiplication rule, satisfy yourself that the various events are either mutually exclu-sive or independent, respectively.)

(b) two girls?

(c) either two boys or two girls?

 

8.16 A traditional test for extrasensory perception (ESP) involves a set of playing cards, each of which shows a different symbol (circle, square, cross, star, or wavy lines). If C represents a correct guess and I an incorrect guess, what is the probability of

(a) C?

(b) CI (in that order) for two guesses?

(c) CCC for three guesses?

(d) III for three guesses?

 

8.19 A sensor is used to monitor the performance of a nuclear reactor. The sensor accurately reflects the state of the reactor with a probability of .97. But with a probability of .02, it gives a false alarm (by reporting excessive radiation even though the reactor is performing normally), and with a probability of .01, it misses excessive radiation (by failing to report excessive radiation even though the reactor is performing abnormally).

(a) What is the probability that a sensor will give an incorrect report, that is, either a false alarm or a miss?

(b) To reduce costly shutdowns caused by false alarms, management introduces a second completely independent sensor, and the reactor is shut down only when both sensors report excessive radiation. (According to this perspective, solitary reports of excessive radiation should be viewed as false alarms and ignored, since both sensors provide accurate information much of the time.) What is the new probability that the reactor will be shut down because of simultaneous false alarms by both the first and second sensors?

(c) Being more concerned about failures to detect excessive radiation, someone who lives near the nuclear reactor proposes an entirely different strategy: Shut down the reactor whenever either sensor reports excessive radiation. (According to this point of view, even a solitary report of excessive radiation should trigger a shutdown, since a failure to detect excessive radiation is potentially catastrophic.) If this policy were adopted, what is the new probability that excessive radiation will be missed simultaneously by both the first and second sensors?

 

*8.21 Assume that the probability of breast cancer equals .01 for women in the 50–59 age group. Furthermore, if a woman does have breast cancer, the probability of a true positive mammogram (correct detection of breast cancer) equals .80 and the probability of a false negative mammogram (a miss) equals .20. On the other hand, if a woman does not have breast cancer, the probability of a true negative mammogram (correct nondetection) equals .90 and the probability of a false positive mammogram (a false alarm) equals .10. (Hint: Use a frequency analysis to answer questions. To facilitate checking your answers with those in the book, begin with a total of 1,000 women, then branch into the number of women who do or do not have breast cancer, and finally, under each of these numbers, branch into the number of women with positive and negative mammograms.)

(a) What is the probability that a randomly selected woman will have a positive mammogram?

(b) What is the probability of having breast cancer, given a positive mammogram?

(c) What is the probability of not having breast cancer, given a negative mammogram?

You had the chance earlier in the week to perform an article critique on correlation and simple linear regression and obtain peer feedback. Hopefully you are excited about the potential these tests hold; equally important is that you recognize some of their weaknesses. Now, it is once again time to put all of that good brainstorming to use and answer a social research question with the correlation and simple linear regression. As you begin the Assignment, be sure and pay close attention to the assumptions of the test. Specifically, make sure that your variables are metric level variables that can easily be interpreted in these tests.

For this Assignment, you will examine correlation and bivariate regression testing.

To prepare for this Assignment:

· Review this week’s Learning Resources and media program related to regression and correlation.

· Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in the Learning Resources for this week.

· Based on the dataset you chose, construct a research question that can be answered with a Pearson correlation and bivariate regression.

· Once you perform your correlation and bivariate regression analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Assignment:

Write a 2- to 3-paragraph analysis of your correlation and bivariate regression results for each research question. Do not forget to evaluate if the correlation and bivariate regression assumptions are met and report the effect size. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.

Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

Assignment: Testing for Correlation and Bivariate Regression

Lane Chapter 14

 

2. The formula for a regression equation is Y’ = 2X + 9.

a. What would be the predicted score for a person scoring 6 on X?

 

b. If someone’s predicted score was 14, what was this person’s score on X?

 

6. For the X, Y data below, compute:

a. r and determine if it is significantly different from zero.

b. the slope of the regression line and test if it differs significantly from zero.

c. the 95% confidence interval for the slope.

X	Y
4	6
3	7
5	12
11	17
10	9
14	21

 

 

Lane Chapter 17

 

5. At a school pep rally, a group of sophomore students organized a free raffle for prizes. They claim that they put the names of all of the students in the school in the basket and that they randomly drew 36 names out of this basket. Of the prize winners, 6 were freshmen, 14 were sophomores, 9 were juniors, and 7 were seniors. The results do not seem that random to you. You think it is a little fishy that sophomores organized the raffle and also won the most prizes. Your school is composed of 30% freshman, 25% sophomores, 25% juniors, and 20% seniors.

a. What are the expected frequencies of winners from each class?

b. Conduct a significance test to determine whether the winners of the prizes were distributed throughout the classes as would be expected based on the percentage of students in each group. Report your Chi Square and p values.

c. What do you conclude?

 

14. A geologist collects hand-specimen sized pieces of limestone from a particular area. A qualitative assessment of both texture and color is made with the following results. Is there evidence of association between color and texture for these limestones? Explain your answer.

	Colour
Texture	Light	Medium	Dark
Fine Medium Coarse	4 5 21	20 23 23	8 12 4

 

Illowsky Chapter 11

Decide whether the following statements are true or false.

70. The standard deviation of the chi-square distribution is twice the mean.

 

Use the following information to answer the next twelve exercises: Suppose an airline claims that its flights are consistently on time with an average delay of at most 15 minutes. It claims that the average delay is so consistent that the variance is no more than 150 minutes. Doubting the consistency part of the claim, a disgruntled traveler calculates the delays for his next 25 flights. The average delay for those 25 flights is 22 minutes with a standard deviation of 15 minutes.

113. df = ________

 

 

 

Illowsky Chapter 12

12.3 The Regression Equation

66. Can a coefficient of determination be negative? Why or why not?

 

Use the following information to answer the next two exercises. The cost of a leading liquid laundry detergent in different sizes is given in Table 12.31

 

Size (ounces)	Cost ($)	Cost per ounce
16	3.99
32	4.99
64	5.99
200	10.99

 

 

82.

a. Using “size” as the independent variable and “cost” as the dependent variable, draw a scatter plot.

b. Does it appear from inspection that there is a relationship between the variables? Why or why not?

c. Calculate the least-squares line. Put the equation in the form of: ŷ = a + bx

d. Find the correlation coefficient. Is it significant?

e. If the laundry detergent were sold in a 40-ounce size, find the estimated cost.

f. If the laundry detergent were sold in a 90-ounce size, find the estimated cost.

g. Does it appear that a line is the best way to fit the data? Why or why not?

h. Are there any outliers in the given data?

i. Is the least-squares line valid for predicting what a 300-ounce size of the laundry detergent would you cost? Why or why not?

j. What is the slope of the least-squares (best-fit) line? Interpret the slope.

Quiz 3

 

This quiz has more conceptual questions, because I think they’re important. Be sure to understand the 2×2 box dealing with Type I and Type II errors, alpha, beta, and power.

 

Each multiple choice questions is worth 0.50 point. Other questions are worth two points.

 

1. (0.50 point) I hypothesized that girls in my class have the same blood pressure levels as boys. The probability value for my null hypothesis was 0.15. So I conclude that the blood pressures of the girls were higher than boys’. Which kind of mistake did I make?

 

a. Type I error

b. Type II error

c. Type I and Type II error

d. I did not make any mistake

 

2. (0.50 point) If a statistical test result is not significant at the 0.05 level, then we can conclude:

 

a. It is not significant at 0.10 level

b. It must be significant at 0.01 level

c. It must be significant above 0.05 level

d. It is not significant at 0.01 level

 

 

3. (2 points) A researcher posed a null hypothesis that there was no significant difference between boys and girls on a standard memory test. She randomly sampled 100 girls and 100 boys in a community and gave them the standard memory test. The mean score for girls was 70 and the standard deviation of mean was 5.0. The mean score for boys was 65 and the standard deviation of mean was 5.0. What is the standard error of the difference in means?

 

 

 

4. (0.50 point) If power is big, you can assume:

 

a. The significance level set by the researcher must be high

b. We increase the probability of type I error

c. Your study result will be more likely to be inconclusive

d. The difference between the means is more likely to be detected

 

 

5. (0.50 point) If the probability that you will correctly reject a false null hypothesis is 0.80 at 0.05 significance level. Therefore, α is__ and β is__.

 

a. 0.05, 0.80

b. 0.05, 0.20

c. 0.95, 0.20

d. 0.95, 0.80

 

 

 

6. (2 points) The population has a mean of 678 and the population standard deviation is known to be 58.3. Use a 0.05 level of significance to test the claim that the sample scores listed below came from the population. Identify hypotheses, test statistic, P-value or critical value, conclusion about the null, and final conclusion that addresses the original claim.

 

714 751 664 789 818 779 698 836 753 834 693 802

 

 

7. (2 points) I am looking to move to either Mississippi or Arkansas, depending on the cost of housing. Below are the costs (in thousands, hypothetically) of 12 houses in each location based upon a simple random selection:

 

Mississippi: 155 142 149 130 151 163 151 142 156 133 138 161

Arkansas: 133 140 142 131 134 129 128 140 140 140 137 143

 

Use a 0.05 significance level to test the claim that the mean cost of houses in Mississippi is greater than the mean cost in Arkansas. Be sure to give the hypotheses, the test statistic with a p-value, and a conclusion.