The project must be typewritten, double spaced and very limited in length (maximum 12 pages).
Part I (25%)
A NP researcher randomly sampled 100 women aged 50-65 years and measured their minutes of exercise in the past week, BMI, and depression. Depression was measured using a Likert type scale consisting of 20 items. The summation score ranged from 20 to 100 and the higher the score, the higher the level of depression. The Pearson correlation coefficients (r’s) are summarized in the following table. For the analyses, statistical significant level was set at α=0.05.
Table 1: correlation among minutes of exercise, BMI and depression
Exercise in past week (minutes)
*p < 0.05
1. Write a research and null hypotheses regarding the relationship between exercise and depression.
2. Based on the test statistics in table 1, what is your conclusion regarding your research hypothesis? (Hint: discuss both the magnitude and direction of the relationship).
3. What proportion of variance is shared by minutes of exercise and depression among women 50-65 years of age?
4. For the relationship between minutes of exercise and BMI,
a. what was the estimated power of the statistical test? (Using the power table on page 202, table 9.1, Polit 2010).
b. What was the risk that a type II error was committed?
5. If -0.20 is a good estimation of population correlation, what sample size would be needed to achieve power of 0.80 at a significance α=0.05?
PART II. (25%)
Using the “N6208 Final Project Data”,
a). select two variables with nominal or ordinal level measurements, and perform the descriptive statistics (frequency and percentage). [Please select only dichotomous variables from the following list: poverty, smoker, PoorHealth].
b). perform the bi-variate descriptive statistics using crosstabulation.
c). Hand calculate the ARs, ARR, RR, and OR. Show all your calculations.
d). Perform a chi-square analysis.
e). Using APA format, write a full report with the following sections:
1. Introduction: Describe your research question and hypothesis. Include the variables, measurement levels, the bivariate research question, and the hypothesis [for example, the event of adverse risk (using your variable name here, for instance, alcohol usage) will be higher/or lower in the risk exposed group (i.e., marijuana use) compare to the non-exposed group (non-users of marijuana)].
2. Method: Include the sample description (sample size, eligibility criteria) and statistical methods used for data analysis. (The sample information can be found in “Polit Dataset Description” in SPSS Data Sets folder).
3. Results: Include frequencies and percentages for the two variables, crosstabulation results, risk indexes (ARs, ARR, RR, and OR), and chi-square test results. Include a summary table for the results and write your interpretation. (Attach SPSS outputs).
4. Discussion: Write a report including summary and interpretation of the findings reported in the previous sections relative to the research questions you posed in your introduction.