Question 1:

1-1. Run Frequencies on the following variables--- nurseed, gender, age, yrsmns, mdsother, mdsself, rankmil, distress, Disturb, and freq30.

1-2. Review the variables for incorrect values and skewness. Use Pearson's skewness statistics. If you find any incorrect values, please exclude them from your analysis.

1-3. Create one table for the nominal/ordinal variables and another table for the interval/ratio variables.

1-4. Write up your observation including the interpretation of skewness statistics and management of incorrect values. Also briefly describe how much missing data there is.

For example, the variable X had Y% missing.

** please do not impute any values for missing data**

• "distress" (total moral distress) ranges from 1 to 12. The higher the more perceived moral distress.
• In "yearmns", a number with one decimal point is valid. For example, 1.4 (years) is a correct value.
• Assume that military nurses retire at age of 65.
• Each "sitdis" is an ordinal variable, ranging from 0 (not at all distressed) to 6 (very frequently distressed).

Question 2: Inferential Statistics

In the following analyses, state what statistical technique was used. State the results in relation to the research questions and explain what the results mean in layman terms. Be sure to check assumptions, and conduct data transformations, where appropriate. Also include appropriate tables in your written report.

2-1. What are the correlations between the following variables: years of completed military nursing service as an officer (yrsmns), total moral distress (distress), and Respondent's Age (age)

2-2. Which of the following variables predict total moral distress score (distress)? Enter the predictor variables in three blocks as follows:

• Block 1: age, gender
• Block 2: nursing education, years of completed military nursing services (yrsmns)
• Block 3: military rank Use Enter method.

Results should include model summary (R-squared, adjusted R-squared, R-squared changes, overall significance test), final regression equation model, results of significance test and Interpretation of coefficient (b-weight) for each predictor.

2-3. Use Q 2-2 and check the assumptions of homoskedasticity, absence of multicollinearity, and linearity and normality using standardized regression residuals.

Price: $27.45

Solution: The downloadable solution consists of 20 pages, 745 words and 1 charts.
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