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Carlton

Statistics in Psychology

Final Exam

NAME:

INSTRUCTIONS: For this exam, you will design and test one of each of the listed hypothesis test types, using the dataset “FinalExamData.sav,” This time, you are in the driver’s seat and will have to decide what research questions YOU want to answer, using the data that is provided for you! This dataset contains randomly generated data from 20 different demographic and college-test related variables from 100 seniors attending different state universities in NJ.

For each test, you should do the following (you must show each numbered and lettered step below).

1. Create a research question that you can answer appropriately using the test and using the available data. Each variable contains labels that describe what was measured, and there are a variety of nominal and scale variables from which you can choose.

2. Identify the appropriate variables for your research questions, their measurement type, and their label (as this information appears in SPSS)

3. Compute descriptive statistics using Analyze Descriptives Explore command and copy your output table. You should also write a few sentence description summarizing your variables.

4. Complete the following three steps of hypothesis testing

a. Step 1: Null/Alternative hypotheses

b. Step 2: Alpha level, degrees of freedom (if appropriate), one/two tailed test type (if appropriate), other information as appropriate

c. Step 3: Appropriate test statistic/table, as a copied and pasted/screenshot of SPSS results

i. Post hoc tests if appropriate

d. Step 4: A full write up for step four, including:

i. A decision about the null hypothesis

ii. A written explanation about the results of the test, including means and standard deviations, and a final answer to your research question

iii. Proper APA style string, including effect size and confidence intervals, if appropriate.

Please conduct one of each of the following hypotheses tests:

1. Paired-Samples t-test (10 points)

2. Independent Samples t-test (20 points)

3. One-Way ANOVA (20 points)

4. Correlation (10 points)

5. Regression (20 points)

6. Two-way Chi Square (20 points)

BONUS: generate an appropriate chart for each test using the Graphs Chart Builder or the Graphs Legacy Dialogue (or, as in ANVOVA, the chart option built into the dialogue box) in SPSS.

EXAMPLE ANSWER for ANOVA

1. Is there a significant difference in freshman GPA between students at the three different schools (Rowan, Rutgers, or TCNJ)?

2. IV: “College.” Label: “College Student is Attending.” Measurement Type: Nominal

DV: “GPA_Freshman.” Label: “GPA at end of Freshman Year.” Measurement Type: Scale

3.

4.

Step 1. H0:

Ha: Not all are equal.

Step 2. = .05

Step 3.

Test of Homogeneity of Variances

Levene Statistic

df1

df2

Sig.

GPA at end of Freshman Year

Based on Mean

1.166

2

97

0.316

Based on Median

0.878

2

97

0.419

Based on Median and with adjusted df

0.878

2

96.9

0.419

Based on trimmed mean

1.157

2

97

0.319

ANOVA: GPA at end of Freshman Year

SS

df

MS

F

Sig.

Between Groups

0.305

2

0.152

0.252

0.778

Within Groups

58.568

97

0.604

Total

58.873

99

Step 4. Retain H0. Levene’s test showed that the variance was equal between the three groups, F(2, 97) = 1.166, p = .316. There was not a significant difference in GPA at the end of freshman year between students at Rowan (M = 2.34, SD = .82), Rutgers (M = 2.32, SD = .73), or TCNJ (M = 2.16, SD = .77). Students from all three schools had GPAs that were essentially equal at the end of school year, F(2, 97) = 0.252, p = 0.778, = .01.

NOTES on this ANOVA EXAMPLE:

1. You cannot use this example as one of your tests!

2. “My God, man! How did Carlton get those tables so nice?! Curse him and all his descendants!” Here is the trick: I copied the table right from SPSS into Excel. That (usually) keeps everything in the right place, and allows me to add the fancy APA style horizontal line breaks which you’ll learn about in research methods.

3. I’ve not included the descriptive statistics here, but YOU NEED TO. You may use these variables for other analyses, so I didn’t want to provide you the answers.

4. A significant Levene’s test means a different course of action for ANOVA and Independent Samples t-test. (We haven’t used it for ANOVA, so I’m not concerned if you don’t include it. However, you do need to include this information for your independent samples t-test, so I wanted to give you an example). I’ve used APA style to report it here, feel free to copy my example using your numbers. If your Levene’s test is significant, make sure to include that and whatever correction you had to make in your write-up!

5. Because this test was not significant, I did not copy and paste or report the post-hoc tests. If your ANOVA is significant, that table should be included.

LIST of SYMBOLS to COPY:

H0

Ha

±

1

1

rpb2

Statistics in Psychology

Final Exam

NAME:

INSTRUCTIONS: For this exam, you will design and test one of each of the listed hypothesis test types, using the dataset “FinalExamData.sav,” This time, you are in the driver’s seat and will have to decide what research questions YOU want to answer, using the data that is provided for you! This dataset contains randomly generated data from 20 different demographic and college-test related variables from 100 seniors attending different state universities in NJ.

For each test, you should do the following (you must show each numbered and lettered step below).

1. Create a research question that you can answer appropriately using the test and using the available data. Each variable contains labels that describe what was measured, and there are a variety of nominal and scale variables from which you can choose.

2. Identify the appropriate variables for your research questions, their measurement type, and their label (as this information appears in SPSS)

3. Compute descriptive statistics using Analyze Descriptives Explore command and copy your output table. You should also write a few sentence description summarizing your variables.

4. Complete the following three steps of hypothesis testing

a. Step 1: Null/Alternative hypotheses

b. Step 2: Alpha level, degrees of freedom (if appropriate), one/two tailed test type (if appropriate), other information as appropriate

c. Step 3: Appropriate test statistic/table, as a copied and pasted/screenshot of SPSS results

i. Post hoc tests if appropriate

d. Step 4: A full write up for step four, including:

i. A decision about the null hypothesis

ii. A written explanation about the results of the test, including means and standard deviations, and a final answer to your research question

iii. Proper APA style string, including effect size and confidence intervals, if appropriate.

Please conduct one of each of the following hypotheses tests:

1. Paired-Samples t-test (10 points)

2. Independent Samples t-test (20 points)

3. One-Way ANOVA (20 points)

4. Correlation (10 points)

5. Regression (20 points)

6. Two-way Chi Square (20 points)

BONUS: generate an appropriate chart for each test using the Graphs Chart Builder or the Graphs Legacy Dialogue (or, as in ANVOVA, the chart option built into the dialogue box) in SPSS.

EXAMPLE ANSWER for ANOVA

1. Is there a significant difference in freshman GPA between students at the three different schools (Rowan, Rutgers, or TCNJ)?

2. IV: “College.” Label: “College Student is Attending.” Measurement Type: Nominal

DV: “GPA_Freshman.” Label: “GPA at end of Freshman Year.” Measurement Type: Scale

3.

4.

Step 1. H0:

Ha: Not all are equal.

Step 2. = .05

Step 3.

Test of Homogeneity of Variances

Levene Statistic

df1

df2

Sig.

GPA at end of Freshman Year

Based on Mean

1.166

2

97

0.316

Based on Median

0.878

2

97

0.419

Based on Median and with adjusted df

0.878

2

96.9

0.419

Based on trimmed mean

1.157

2

97

0.319

ANOVA: GPA at end of Freshman Year

SS

df

MS

F

Sig.

Between Groups

0.305

2

0.152

0.252

0.778

Within Groups

58.568

97

0.604

Total

58.873

99

Step 4. Retain H0. Levene’s test showed that the variance was equal between the three groups, F(2, 97) = 1.166, p = .316. There was not a significant difference in GPA at the end of freshman year between students at Rowan (M = 2.34, SD = .82), Rutgers (M = 2.32, SD = .73), or TCNJ (M = 2.16, SD = .77). Students from all three schools had GPAs that were essentially equal at the end of school year, F(2, 97) = 0.252, p = 0.778, = .01.

NOTES on this ANOVA EXAMPLE:

1. You cannot use this example as one of your tests!

2. “My God, man! How did Carlton get those tables so nice?! Curse him and all his descendants!” Here is the trick: I copied the table right from SPSS into Excel. That (usually) keeps everything in the right place, and allows me to add the fancy APA style horizontal line breaks which you’ll learn about in research methods.

3. I’ve not included the descriptive statistics here, but YOU NEED TO. You may use these variables for other analyses, so I didn’t want to provide you the answers.

4. A significant Levene’s test means a different course of action for ANOVA and Independent Samples t-test. (We haven’t used it for ANOVA, so I’m not concerned if you don’t include it. However, you do need to include this information for your independent samples t-test, so I wanted to give you an example). I’ve used APA style to report it here, feel free to copy my example using your numbers. If your Levene’s test is significant, make sure to include that and whatever correction you had to make in your write-up!

5. Because this test was not significant, I did not copy and paste or report the post-hoc tests. If your ANOVA is significant, that table should be included.

LIST of SYMBOLS to COPY:

H0

Ha

±

1

1

rpb2

Answered Same DayMay 05, 2021

Question 1: We want to test that whether the GPA of the freshman and GPA of the senior has a significant difference or not. The level of significance is 0.05.

The variable names are GPA_Freshman...

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