Part A. SPSS AssignmentIn this exercise, you are playing the role of a researcher that is testing new medication designed to improve cholesterol levels. When examining cholesterol in clinical settings

Part A. SPSS AssignmentIn this exercise, you are playing the role of a researcher that is testing new medication designed to improve cholesterol levels. When examining cholesterol in clinical settings, we look at two numbers: low-density lipoprotein (LDL) and high-density lipoprotein (HDL). You may have heard these called “good” (HDL) and “bad” (LDL) cholesterol. For LDL, lower numbers are better (below 100 is considered optimal. For HDL, 60 or higher is optimal. 

In this experiment, the researcher is testing three different versions of the new medication. In data file “Activity 12.sav” you will find the following variables: group (0=control, 1=Drug A, 2=Drug B, 3=Drug C), LDL, and HDL (cholesterol numbers of participants after 12 weeks). 

Using a MANOVA, try to ascertain which version of the drug (A, B or C) shows the most promise. Perform the following analyses, and paste the SPSS output into your document.

1. Exploratory Data Analysis.
   1. Perform exploratory data analysis on the relevant variables in the dataset. When possible, include appropriate graphs to help illustrate the dataset.
   2. Give a one to two paragraph write up of the data once you have done this.
   3. Create an APA style table that presents descriptive statistics for the sample.
2. Perform a MANOVA. Using the “Activity 12.sav” data set perform a MANOVA. “Group” is your fixed factor, and LDL and HDL are your dependent variables. Be sure to include simple contrasts to distinguish between the drugs (group variable). In the same analysis, include descriptive statistics, and parameter estimates. Finally, be certain to inform SPSS that you want post-hoc test to help you determine which drug works best.
   1. Is there any statistically significant difference in how the drugs perform? If so, explain the effect. Use the post hoc tests as needed.
   2. Write up the results using APA style and interpret them.

Data set has been attached to post.

Due : June 1, 2019 by 12pm EST