Part A - Multiple Regression and SPSS: - This part requires Andy Field's resource page, Interact: Discover SPSS. Use the data file labeled album_sales.sav. The data file can also be found in the Research Application: Regression, Intervening Variables Resources. The name is .sav file labeled album_sales.sav and calculate the data for the scenario below in SPSS using that data, but with different labels and variables as shown below. The work will be check against what is in the textbook, but applied to a different topic, demonstrating the ability to analyze and interpret the data.

The analysis, open the album_sales.sav file in SPSS, and save it on the computer as "sugar and happiness" or something similar so that can distinguish it from the original file.The new labels will fit the sugar and happiness scenario as shown below. Be sure to change both the "name" and the "label" columns in SPSS.

Scenario: This is a study for a health and wellness organization related to the consumption of sugar. They know that people often report feeling happy or euphoric after eating sugar (until they crash). But, they want to if happiness can be predicted by any or all of the amount of sugar eaten, the endorphin levels that result in part from the sugar, and their belief regarding how healthy/unhealthy sugar is for the body (measured as a scale). Use this scenario information to analyze and interpret the data.

FIELD LABEL		YOUR LABEL
Album ID	To	Participant ID
Album Sales	To	Happiness Score
Advertising Budget	To	Grams of Sugar
No. of plays on radio	To	Endorphin Level
Band Image Rating	To	Health Perspective Rating

Then, perform a multi-linear regression analysis following the procedures in the textbook and the Watch items from this Module: Week Learn items. Use all of the variables that is relabeled. Identify the dependent variable separate from the predictor variables, as well as Do not use the participant ID as a variable.

For the analyses, use a=.05 (95% c.i.) and two-tails. Then include all of the following clearly identified and presented in a summary.

.

• Original research question for the "study".
• OriginalNull and Alternative hypotheses accurately reflecting the research question (labeled Ho: and Ha:).
• A histogram with appropriate options.
• A scatter plot including the "add fit line at total" feature and other appropriate options.
• The applicable P-P charts.
• Run the regression analysis in SPSS and present the applicable charts in the paper.
• A brief narrative describing what each aspect of the analysis that tells how it would interpret it in light of the hypotheses.

Part B - Intervening Variables:

• For this part, you will not be required to calculate any data (though you are encouraged to use the information in Interact: Discover SPSSfound in the Learnsection of this Module: Week), to be familiar with the concept and analysis. The "sugar and happiness" variables in Part A for research design that would consider mediating variables, and one considering moderating variables.
• A brief (no more than one paragraph) explanation of the concepts and differences of mediating and moderating variables, and how each would be used in research designs. All sources highlighted

Moderating:

• Original research question for the"study" if there are moderating variables, using the variables used in part A.
• Original Null and Alternative hypotheses accurately reflecting the research question (labeled Ho: and Ha:).

Mediating:

• Original research question for the "study" if considering mediatingvariables, using the variables used in part A. Consider "Health Perspective Rating" as a mediating variable.
• Original Null and Alternative hypotheses accurately reflecting your research question (labeled Ho: and Ha:).