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Installing and Registering IBM SPSS Software

IBM SPSS version 27 Installation and Registration (PC/Windows)

IBM SPSS version 27 Installation and Registration (Mac)

Licensing Your IBM SPSS Software

Students may obtain the SPSS license code from this link:https://alaureatena.sharepoint.com/sites/walden-university/student-documents/spss/Pages/default.aspx

The assignment this week requires that you do a repeated measures T test.Please look at the list of variable names.T1 in a variable name means time 1 for that variable. T2 means time 2.

You will also do two other types of tests. Here are some examples of other types of t tests (attached).

The assignment for this week involves three scenarios.Do all three.One paragraph for each is enough.This time you will use spss and your data set to answer the questions.

Do not overthink effect size.You do not have to rely on Cohen’s d.Instead, look at the correlation coefficient. Here are some guidelines for interpreting effect.

•Moderate effects

•Spearman .30-.49

•Pearson .30-.49

•R square .10-.25

•Eta square .10-.25

•Phi and Cramer’s V .20-.60

To prepare for this Assignment:

· Review thettest scenarios (attached) and consider the three different approaches ofttests:

· Independent samplettest

· Paired samplettest

· One samplettest

· Based on each of the three research scenarios provided, open the High School Longitudinal Study dataset or the Afrobarometer dataset using SPSS software, then choose and run the appropriatettest.

· Once you perform yourttest analyses, review the Wagner text to understand how to copy and paste your output into your Word document.

For this Assignment:

Write a 1 -paragraph analysis of your t test results for each research scenario and include the SPSS syntax and output. If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). If you are using the HS Long Survey Dataset, report the mean of X1SES.Do not forget to evaluate if the t test assumptions are met, justify the selection of type of t test, and report the effect size. 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 questions, and output.

In these two examples, Veterans Health Administration (VHA) hospitals in the Midwest and contiguous states were the units of analysis (N=32). Data were taken from here:

https://www.va.gov/health/access-audit.asp

.

Example of a one-sample T test

The first analysis is intended to be a benchmarking test. Our VHA hospital of interest has a mean wait for primary care of 4.09 days. The research question is this: Is the average wait for primary care among the hospitals in the sample significantly different from the wait in Madison?

H0: There is no significant difference between Madison and other VHA hospitals in mean wait times for primary care visits.

H1: There is a significant difference between Madison and other VHA hospitals in mean wait times for primary care visits.

The dependent variable is the mean wait in days for a primary care visit. The independent variable is the VHA hospital.

The overall mean was 5.78 (Table 1). The one-sample test (Table 2) produces a p value of .004 (CI .59-2.79). The mean difference was 1.68 days. We can reject the null of no difference between the test value and the mean. The mean wait in Madison VA hospital is 1.68 days less than in the other VHA hospitals in nearby regions. The effect size (Table 3) is strong (Cohen’s D=.55).

Table 1.

One-Sample Statistics

N

Mean

Std. Deviation

Std. Error Mean

PCAvgWaitTimeinDays13

32

5.78

3.06

.54

Table 2.

One-Sample Test

Test Value = 4.09

t

df

Sig. (2-tailed)

Mean Difference

95% Confidence Interval of the Difference

Lower

PCAvgWaitTimeinDays13

3.122

31

.004

1.68

.59

One-Sample Test

Test Value = 4.09

95% Confidence Interval of the Difference

Upper

PCAvgWaitTimeinDays13

2.79

Table 3.

One-Sample Effect Sizes

Standardizera

Point Estimate

95% Confidence Interval

Lower

PCAvgWaitTimeinDays13

Cohen’s d

3.06

.552

.176

Hedges’ correction

3.13

.538

.171

One-Sample Effect Sizes

95% Confidence Intervala

Upper

PCAvgWaitTimeinDays13

Cohen’s d

.921

Hedges’ correction

.898

a. The denominator used in estimating the effect sizes.

Cohen’s d uses the sample standard deviation.

Hedges’ correction uses the sample standard deviation, plus a correction factor.

T-TEST GROUPS=ResearchPeers(1 0)

/MISSING=ANALYSIS

/VARIABLES=PCAvgWaitTimeinDays13

/ES DISPLAY(TRUE)

/CRITERIA=CI(.95).

Example of an Independent Sample T test

In this two-sample t test, the units of analysis were the 32 VHA hospitals. The hospitals were scored as 1 if they were research institutions and 0 if not. The research question was this: Is the average wait time in days for primary care visits significantly different between research and non-research hospitals?

H0: There is no significant difference in mean wait times for primary care visits between research and non-research hospitals.

H1: There is a significant difference in mean wait times for primary care visits between research and non-research hospitals.

The dependent variable is mean wait time in days for primary care visits. The independent variable was research status (yes vs no).

Eleven hospitals were classified as research institutions and 21 were not. The mean number of days wait for primary care visits was 6.06 in research hospitals and 5.63 in other hospitals (Table 4). The Levene’s test was not significant, so we can assume the variances are equal. The p value for the t test was .710, indicating no significant difference between the groups (Table 5). We can accept the null hypothesis. The mean wait time in days is not different in research hospitals and non-research hospitals in this sample. Effect size (Table 6) is not relevant since there is no significant difference between the means.

Table 4

Group Statistics

ResearchPeers

N

Mean

Std. Deviation

PCAvgWaitTimeinDays13

1

11

6.06

2.98

0

21

5.63

3.16

Group Statistics

ResearchPeers

Std. Error Mean

PCAvgWaitTimeinDays13

1

.90

0

.69

Table 5

Independent Samples Test

Levene’s Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

PCAvgWaitTimeinDays13

Equal variances assumed

.027

.871

.376

Equal variances not assumed

.383

Independent Samples Test

t-test for Equality of Means

df

Sig. (2-tailed)

Mean Difference

PCAvgWaitTimeinDays13

Equal variances assumed

30

.710

.434

Equal variances not assumed

21.487

.706

.434

Independent Samples Test

t-test for Equality of Means

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

PCAvgWaitTimeinDays13

Equal variances assumed

1.153839015224656

-1.922730696075869

2.790176583521755

Equal variances not assumed

1.132796661318518

-1.918810326453821

2.786256213899707

Table 6.

Independent Samples Effect Sizes

Standardizera

Point Estimate

95% Confidence Interval

Lower

PCAvgWaitTimeinDays13

Cohen’s d

3.10

.140

-.592

Hedges’ correction

3.18

.136

-.577

Glass’s delta

3.16

.137

-.595

Independent Samples Effect Sizes

95% Confidence Intervala

Upper

PCAvgWaitTimeinDays13

Cohen’s d

.869

Hedges’ correction

.847

Glass’s delta

.866

a. The denominator used in estimating the effect sizes.

Cohen’s d uses the pooled standard deviation.

Hedges’ correction uses the pooled standard deviation, plus a correction factor.

Glass’s delta uses the sample standard deviation of the control group.

© 2016 Laureate Education, Inc. Page 1 of 1

Week 6

Scenarios

1. As an international development researcher, you would like to know African Citizen’s

perceptions about current levels of democracy. Your working hypothesis is that a

series of reforms have increased African views of the level of democracy today. You

do not have a good research design to compare attitudes before and after the

reforms, but know that leaders and development experts would like to see a value of

6, on the scale of 1–10. Using the data from the 2015 Afrobarometer, determine

whether perceptions about current levels of democracy statistically differ from a

value of 6. Please provide: a 1–2 APA style paragraph statement that furnishes an

answer to this question, note the relevant statistics, comment on meaningfulness

and include your relevant SPSS output.

2. As an international development researcher, you have already tested whether

perceptions about the current levels of democracy differ from a value of 6. Given

recent social change movements in North Africa, you now want to determine

whether there is a statistical difference in these perceptions between North Africa

and Southern Africa. Using the data from the 2015 Afrobarometer, please provide: a

1–2 APA style paragraph statement that furnishes an answer to this question, note

the relevant statistics, comment on meaningfulness, and include your relevant SPSS

output.

3. As an educational researcher, would like to know whether high school student’s

perceptions about mathematical utility changed between their freshman and senior

year. Each respondent is asked the same series of questions about the utility of

mathematics in their future during their freshman and senior year. These questions

are combined to form one variable of mathematical utility; higher values indicate

higher levels of mathematical utility. Using the High School Longitudinal Survey,

please provide: a 1–2 APA style paragraph statement that furnishes an answer to

this question, note the relevant statistics, comment on meaningfulness, and include

your relevant SPSS output.

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