Psychology week 7 assignment

RSM801 Final Project

· Please be sure to create a cover page so I can keep track of who submitted the document (include name, course number and instructor)

· Read each question FULLY and CAREFULLY before answering.

· Use your time well – look over the assignment before starting and develop a plan. If you are stuck on a problem, move on and come back to it later.

· If completely stuck, you may ask me for guidance. I will provide hints or steps for certain parts of the question, but no credit will be given for those steps. Use this option sparingly.

· Refer to course materials such as your textbook from Quant I or the e-book in the classroom for review of statistical concepts (e.g., t-tests, ANOVAs, correlation, regression) and descriptive statistics. The software guides and instructional videos in the resources folder can help with technical execution.

· Ask questions if you are unsure. While I cannot give direct answers, I may provide useful clarifications.

Instructions

Open “Week7_RSM801” data.

About these data: Roy Baumeister and his colleagues studied self-regulation. In other words, they ask why don't we eat all of the tasty tidbits we encounter, attend parties when we should be studying, and have sex with every attractive potential partner who crosses our path? In short, how do we manage to forgo temptation? An exploration of (fictitious) data regarding these questions will comprise the bulk of the final lab exam.

The data set you opened represents scores of 800 recent college graduates who participated in a study. First, participants were asked to control their emotions while watching a very sad movie and then completed challenging set of brain teasers. One week later, participants returned to the lab and again watched a sad movie. This time, they were not asked to control their emotions and completed a different (but equally challenging) set of brain teasers. In both cases, the researchers measured how much participants persisted at the difficult brain teasers. The variables in this data set are:

SUBJECT	Unique subject identifier from 1-800
PERSONALITY	Personality Type (0 = Introvert; 1 = Extrovert)
CTRL_PER	Persistence after watching a sad movie and being asked to control emotions (1-10 scale; higher numbers indicate greater persistence).
NO_CTRL_PER	Persistence after watching a sad movie and NOT being asked to control emotions (1-10 scale; higher numbers indicate greater persistence).
NEED_CTRL	Self-report of need for control in the environment, measured two months before participating in the study (1-5 scale; higher numbers indicate greater need for control over one's environment)
JOB	First job or activity following college graduation (0 = Public service job; 1 = Graduate school; 2 = Travel; 3 = Private sector job)

1. Outliers (6 points)

Create a new variable in SPSS or Jamovi that represents the z-score of persistence on brain teasers after being asked to control emotions (CTRL_PER). Analyze the data for outliers. Write up your conclusion including:

· Identify potential outliers, including relevant output and writing a brief justification for whether or not these are true outliers. Be sure to include a figure. [4 points]

· Justify whether any potential outliers should be kept, removed, or transformed. Be sure not to remove or transform outliers, simply report what you would do based on this analysis. [2 points]

2. Inferential Statistics (8 points) Is self-reported need to control one’s environment (NEED_CTRL) associated with persistence scores after watching a sad movie without emotion control (NO_CTRL_PER)?

· What statistical test would you conduct? Explain your reasoning. [2 points]

· Run the test in SPSS or Jamovi. Paste your output into the document. [2 points]

· Write up your findings as if reporting them in a journal article, following APA guidelines. [4 points]

3. Inferential Statistics (9 points)

Do introverts and extroverts differ in their need to control their environment?

· What statistical test would you conduct? Explain your reasoning. [2 points]

· Run the test in SPSS or Jamovi. Paste your output into the document. [2 points]

· Write up your findings as if reporting them in a journal article, following APA guidelines. [5 points]

4. Job Plans and Percentages (4 points)

· Create a frequency table in SPSS or Jamovi showing how many participants pursue each job/activity after graduation. Paste the table into your Word document. [2 points]

· Calculate and report the percentage of participants who plan to travel after graduation. [2 points]

5. Inferential Statistics (14 points)

Does persistence after watching a sad movie and being asked to control emotions vary by job plans?

· What statistical test would you conduct? Explain your reasoning. [2 points]

· Run the test in SPSS or Jamovi. Paste your output into the document. [2 points]

· Include a figure to illustrate the results. Describe the trends observed. [3 points]

· Write up your findings as if reporting them in a journal article, following APA guidelines. [7 points]

6. Distribution of Need for Control (7 points)

Determine whether Need for Control is approximately normally distributed. [3 points]

· Provide statistical evidence.

· Include a figure as visual evidence and describe what you see.

· Based on the evidence, provide your conclusion about whether need for control can be treated as a normally distributed variable.

Report the following descriptive statistics for Need for Control [4 points]

· Mean

· Median

· Mode

· Variance

· Sample size (n)

7. Interpreting Inferential Statistics (9 points)

A group of psychologists was interested in what kind of humor people find funny. They randomly assigned people to read about different types of humor (knock knock jokes, puns, sarcasm, or practical jokes) and rate how funny each joke, comment, or situation was. Ratings were made on 1 (not at all funny) to 10 (extremely funny) scales. They then conducted a one-way ANOVA with a Tukey post-hoc test to see if there were differences in average ratings of humor across the four different groups. SPSS output is below.

Interpret the SPSS one-way ANOVA results comparing humor ratings across four groups (knock-knock jokes, puns, sarcasm, and practical jokes).

· Describe the results reporting all relevant statistics, using APA guidelines, about the humor differences among the groups.

8. Interpreting Inferential Statistics (9 points)

An industrial psychologist was hired by a company to determine whether gender and work location impacted confidence. The results of this study are presented in the figure below.

Analyze a figure presenting the effects of gender and work location on confidence.

A. Identify the statistical test performed. You should base your answer on the study description as well as the figure above. [2 points] B. Label and number the figure per APA guidelines. [2 points] C. Write hypotheses about gender and work location effects on confidence. [3 points] D. Describe the results, using evidence from the figure. [2 points]

9. Interpreting Inferential Statistics (16 points)

A researcher is interested in whether age, years of experience, or confidence predict certification exam scores. Using the t

· Identify the recommended statistical test and provide justification. [2 points]

· Determine the best predictor of exam scores and justify with statistics. [2 points]

· Identify other variables (age, years of experience, or confidence) that improve prediction accuracy. Back up with statistics. [2 points]

· Identify variables (age, years of experience, or confidence) that do not predict exam performance. Back up your answer. [2 points]

· Write up the best model in APA format. [4 points]

· Using the coefficients table, write the regression equation and explain its meaning. [3 points]

· Suggest a figure that you would want to see to help interpret the data. [1 point]

Descriptive Statistics
	Mean	Std. Deviation	N
Certification Exam	69.65	10.667	60
Age	37.38	8.988	60
Years of Experience	5.87	4.436	60
Confidence	21.43	5.518	60

Correlations
		Certification Exam	Age	Years of Experience	Confidence
Pearson Correlation	Certification Exam	1.000	.610	.444	.596
	Age	.610	1.000	.639	.426
	Years of Experience	.444	.639	1.000	.448
	Confidence	.596	.426	.448	1.000
Sig. (1-tailed)	Certification Exam	.	.000	.000	.000
	Age	.000	.	.000	.000
	Years of Experience	.000	.000	.	.000
	Confidence	.000	.000	.000	.
N	Certification Exam	60	60	60	60
	Age	60	60	60	60
	Years of Experience	60	60	60	60
	Confidence	60	60	60	60

Variables Entered/Removeda
Model	Variables Entered	Variables Removed	Method
1	Age	.	Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
2	Confidence	.	Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
a. Dependent Variable: Certification Exam

Model Summaryc
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.610a	.372	.361	8.525
2	.714b	.510	.493	7.595
a. Predictors: (Constant), Age
b. Predictors: (Constant), Age, Confidence
c. Dependent Variable: Certification Exam

ANOVAc
Model	Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	2498.802	1	2498.802	34.386	.000a
	Residual	4214.848	58	72.670
	Total	6713.650	59
2	Regression	3426.044	2	1713.022	29.700	.000b
	Residual	3287.606	57	57.677
	Total	6713.650	59
a. Predictors: (Constant), Age
b. Predictors: (Constant), Age, Confidence
c. Dependent Variable: Certification Exam

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients
	B	Std. Error	Beta	t	Sig.
1	(Constant)	42.582	4.745		8.973	.000
	Age	.724	.123	.610	5.864	.000
2	(Constant)	33.324	4.817		6.918	.000
	Age	.517	.122	.435	4.248	.000
	Confidence	.794	.198	.411	4.010	.000
a. Dependent Variable: Certification Exam

Excluded Variablesc
Model		Collinearity Statistics
	Beta In	t	Sig.	Partial Correlation	Tolerance
1	Years of Experience	.092a	.677	.501	.089	.592
	Confidence	.411a	4.010	.000	.469	.819
2	Years of Experience	-.032b	-.254	.800	-.034	.554
a. Predictors in the Model: (Constant), Age
b. Predictors in the Model: (Constant), Age, Confidence
c. Dependent Variable: Certification Exam 10. Moderators (5 points) How is a moderation effect tested and expressed statistically? Answer in 3 parts: · Identify the statistical test or method commonly used to evaluate moderation effects. · Explain the role of a moderator in influencing the relationship between an independent variable and a dependent variable. · Provide an example of a moderator impacting the relationship between an IV and DV. 11. Partial Mediation (5 points)
· Explain the statistical steps used to identify partial mediation (e.g., examining the reduction in the effect of the independent variable on the dependent variable after adding the mediator to the model). · How does partial mediation differ from full mediation? · Include a brief description or example to distinguish between the two concepts.