1. What is a co-variate variable (choose all that apply)?

A variable that may influence the dependent variable

A variable that may confound the dependent variable

A variable that has possible predictive capability of the dependent variable

A variable that has possible explanatory capacity of the dependent variable

2. To run descriptive statistics in SPSS v26 or 27, you need to do the following (choose all that are correct)

Choose the type of descriptive statistics desired

Go to the "analyze" tab

Open a dataset (a .sav file)

Move the variable over that you want to analyze

Select "descriptive"

3. There are three file types that are used with SPSS; they use these extensions.

a. .rtf file (data file), .dat file (output file), .docx file (syntax file)

b. .doc file (data file), .ppt file (output file), .xlsx file (syntax file)

c. .sav file (data file), .spv file (output file), .sps file (syntax file)

4. To determine whether or not a dependent variable is normally distributed, the researcher could (choose all that are correct):

Calculate a test of significance using the Bonferroni correction

Run a distribution with the normal curve superimposed and visualize for the fit

Calculate the ratio of the standard error of the skewness/and kurtosis to its corresponding statistic. (manual calculation using SPSS descriptive statistics output)

Calculate a test of significance, using the Kolomorov-Smirnoff test or the Shapiro-Wilk test in SPSS (using the "explore" function in descriptives)

5. When the data are normally distributed, and you want to determine if there is a difference in the means between more than 2 groups, the appropriate test is:

A parametric test: ANOVA

A Mann Whitney U test: with 2 independent groups

A non-parametric test: Kruskal-Wallis

A t test with 2 independent groups

6. A chi square test may be the correct choice: (choose all that apply)

When the variables are measured at the nominal level

When you have at least two variables to be tested

When you need a parametric test

When you are interested in knowing if there is a difference in the means

7. You are measuring the difference in the means between two administrations of the same 20 question test (a pretest and a posttest) to a group of nurses who have taken a continuing education course to assess baseline and knowledge acquisition after the course is completed. The same nurse takes the pretest and the postest, and the results are a score between 0 and 100%; the data are normally distributed. In SPSS: choose the right option

go to analyze, transform, compute and find the right test

you will need to "recode" using transform, and find the right test

go to analyze, compare means, independent samples t test

go to analyze, compare means, paired samples t test

go to non-parametric tests, legacy dialogs, 2 related samples

8. A scatterplot is: (choose all that apply)

Helpful to determine normality in a dataset

Used to visualize the difference in means

Used to visualize the relationship between variables

Closely aligned with correlation

9. Why are the R² and the adjusted R² two different numbers?

The R² includes all of the variables in the model, even those that don't contribute to the model statistically.

The adjusted R² reduces the effect size to account for the variables that do not enter into the model.

There is no practical difference as the numbers are very close

The R squared has only the variables that entered into the model, but the adjusted R squared only includes those that are significant

One is the coefficient of determination and the other is the significance level

10.

Table 2. Within-Subject Differences in Neurobehavior Scores After High and Low Aspartame Intake (N = 28) Variable M SD Paired t-test p Spatial orientation High-aspartame 14.1 4.2 2.4 03. Low-aspartame 16.6 4.3 Working memory High-aspartame 730.0 152.7 1.5 N.S. Low-aspartame 761.1 201.6 Mood (irritability) High-aspartame 33.4 9.0 3.4 .002.. Low-aspartame 30.5 7.3 Depression High-aspartame 36.8 7.0 3.8 001.. Low-aspartame 34.4 6.2 .p<.05. aways over time key measure values median percent of patients who leave unseen date100 initial extended limits reveal improvement ul="97" cl bo .....mmm average days ll="78.47" mos m n j s revised after _ il i>