Module 8 - Treating Depression Lab Part 1 (discussion 1) - mod 8 group 1 From 2020SU-MATH-160-1774 11 unread reply.55 replies. Learn by Doing In this activity, you will investigate the first question related to the study described below. Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer. Here are the directions and grading rubric for the Learn by Doing discussion board exercises. A list of StatCrunch directions is provided at the bottom of this page. Context Clinical depression is a recurrent illness requiring treatment and often hospitalization. Nearly 50% of people who have an episode of major depression will have a recurrence within 2-3 years. Being able to prevent the recurrence of depression in people who are at risk for the disease would go a long way to alleviate the pain and suffering of patients. During the 1980's the federal government, through the National Institutes of Health (NIH), sponsored a large clinical trial to evaluate two drugs for depression. There were 3 treatment groups. Patients received either Imipramine (Imip), Lithium (Li), or a Placebo (Pl). Researchers randomly assigned patients to one of the 3 treatment groups and followed them for 2-4 years to track any recurrences of depression. (Prien et al., Archives of General Psychiatry, 1984). Variables · Hospt: Which hospital the patient was from: Labeled 1, 2, 3, 5 or 6 · Treat: 0=Lithium; 1=Imipramine; 2=Placebo · Outcome: 0=Success 1=Failure (recurrence of depression) · Time: Number of weeks until a recurrence (if outcome=1) or until study ended (if outcome=0) · AcuteT: How long the patient was depressed before the start of the current study, measured in days · Age: Age in years · Gender: 1=Female 2=Male Data If you have not done so already, download the depression datafile (as always, if a login box opens, just close it and then download the file). Then upload the file in StatCrunch. Prompt We will analyze the data to answer the 1st research question: Which of the drugs (if either) was more successful in preventing the recurrence of depression relative to the placebo? In the previous lab-preparation activity, we determined that we will analyze the data using a two-way table and conditional percentages. 1. Use StatCrunch to produce a two-way contingency table. (directions) Copy the table in your StatCrunch output window and paste it in your initial discussion post. (directions) After you paste the content of the your StatCrunch output window into your discussion post, keep the table titled Contingency table results: and delete the Chi-Square results: table. 2. Analyze the data in your two-way table by finding appropriate conditional percentages. Write each conditional percentage as a ratio (e.g. 25 out of 40) and as a percentage (e.g. 25/40 = 62.5%). Then write a sentence that explains the meaning of the percentage in the context of the research question. 3. Draw a conclusion. Based on this study, which drug was the most effective in preventing the recurrence of depression? Support your conclusion using conditional percentages.

In this Assignment, you will be assessed based on the following outcome: GB513-3: Predict business results by using quantitative methods. This Assignment requires you to use Excel in all three questions. Make sure you explain your answers and provide the regression output tables for Questions 1 and 2. Make sure to use the Unit 4 Assignment template from Course Documents when you turn in your answers. Question 1 Shown below are rental and leasing revenue figures for office machinery and equipment in the United States over a 7-year period according to the U.S. Census Bureau. Use this data and the regression tool in the data analysis tool pack to run a linear regression. Based on the formula you get from the regression output, answer the following questions: a) What is the forecast for the rental and leasing revenue for the year 2011? b) How confident are you in this forecast? Explain your answer by citing the relevant metrics. Year Rental and Leasing ($ millions) 2004 5,860 2005 6,632 2006 6,543 2007 5,952 2008 5,732 2009 5,423 2010 4,589 Question 2 Suppose a researcher gathered survey data from 19 employees and asked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following data represent the results of this survey. Assume that relationship with their supervisor is rated on a scale from 0 to 50 (0 represents a poor relationship and 50 represents an excellent relationship); overall quality of the work environment is rated on a scale from 0 to 100 (0 represents poor work environment and 100 represents an excellent work environment); and opportunities for GB513: Business Analytics 2 of 4 advancement is rated on a scale from 0 to 100 (0 represents no opportunities and 100 represents excellent opportunities). Answer the following questions: a) What is the regression formula based on the results from your regression? b) How reliable do you think the estimates will be based on this formula? Explain your answer by citing the relevant metrics. c) Are there any variables that do not appear to be good predictors of job satisfaction? How can you tell? d) If a new employee reports that her relationship with her supervisor is 40, rates her opportunities for advancement to be at 30, finds the quality of the work environment to be at 75, and works 60 hours per week, what would you expect her job satisfaction score to be? Job satisfaction Relationship with supervisor Opportunities for advancement Overall quality of work environment Total hours worked per week 55 27 42 50 52 20 35 28 60 60 85 40 7 45 42 65 35 48 65 53 45 29 32 40 58 70 42 41 50 48 35 22 18 75 55 60 34 32 40 50 95 40 48 45 40 65 33 11 60 38 85 38 33 55 47 10 5 21 50 62 75 37 42 45 43 80 37 46 40 42 50 31 48 60 46 90 42 30 55 38 75 36 39 70 43 45 20 22 40 42 65 32 12 55 53 Question 3 GB513: Business Analytics 3 of 4 Investment analysts generally believe the interest rate on bonds is related to the prime interest rate for loans. a) Use the following data to construct a scatter graph and then fit a regression line to the data. Report the regression formula and the r-squared values from the chart (right click on the data points, select Add Trend line, and select options to show these metrics). b) Do you think the bond rate can be predicted by the prime interest rate? Justify your answer using the relevant metrics. Prime interest rate Bond rate 5.0% 28.0% 12.0% 48.0% 9.0% 32.0% 1.5% 4.0% 0.4% 7.0% 11.0% 36.0% 6.0% 28.0% 2.0% 10.5% Directions for submitting your Assignment Make sure to use the Unit 4 Assignment template from Course Documents when you turn in your answers. Submit your Assignment to the Unit 4 Dropbox.

The coursework assignment contains three sections. (I included the actual assigment as the first attachment, the second attachment is just to help you do harvard style citations, and the third attachment is the formulas to help solve the problems) You also will need SPSS for third section :)The first section deals with measures of central tendency and dispersion, the standard normal distribution and z-scores, and Pearson’s correlation coefficient. Section 2 covers Ordinary Least Squares regression. For both sections, you should calculate the solutions step-by-step and show your calculations clearly using structured tables as per the tutorials and lectures. In section 3 you are asked to research a question using multiple regression analysis performed via SPSS and to write up your results and conclusions.Please make sure that you cite ALL the sources you’ve used and include them all in your bibliography using the Harvard style. Please read the guidance on plagiarism and how to avoid it and make sure your assignment does not contain any plagiarism. Direct quotations must be placed in quotation marks and the source (author, year of publication, and page number) included in the text. If you paraphrase from a sentence from another source you must cite the source (author, year of publication and page number) at the end of each sentence that contains the paraphrased text.