This assignment uses SSPS and since I'm not proficient in the software usage I'm looking for answers...

Question

This assignment uses SSPS and since I'm not proficient in the software usage I'm looking for answers to the questions and a Main Task: Activity #8
You will submit one Word document for this activity. You will create this Word document by cutting and pasting SPSS output into Word.
Part A. SPSS Activity
In 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, you will be testing three different versions of the new medication. In data file “Activity 8.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 Word document.
1. Exploratory Data Analysis.
a. Perform exploratory data analysis on the relevant variables in the dataset. When possible, include appropriate graphs to help illustrate the dataset.
b. Compose a one to two paragraph write up of the data.
c. Create an APA style table that presents descriptive statistics for the sample.
2. Perform a MANOVA. Using the “Activity 8.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 a post-hoc test to help you determine which drug works best.
a. Is there any statistically significant difference in how the drugs perform? If so, explain the effect. Use the post hoc tests as needed.
b. Write up the results using APA style and interpret them.

David · Accepted Answer

MANOVA: is multivariate form of ANOVA. Here we have two or more dependent variables 
instead of just one as in ANOVA. MANOVA is a good option when we want to look for effect 
of one or more IVs on several DVs at the same time.  We have Group” as IV and LDL and HDL 
are your dependent variables. 
null hypothesis- the mean on the composite variable of dependent varable is the same across 
groups.    
Assumptions 
 One independent variable consists of two or more categorical independent groups. 
 Two or more dependent variables that are either interval or ratio (continuous) 
 Multivariate Normality:   This means that each of the dependent variables is normally 
distributed within groups of independent variable. 
 Equality of variances between the independent groups. 
  The homogeneity of population covariance matrices or sphericity 
 Independence of cases. 
 Small samples can have low power, but if the multivariate normality assumption is met, 
the MANOVA is generally more powerful than separate univariate tests. 
1) There EDA means we have to explore data to test whether it follow the assumption of 
Analysis we are going to perform. 
a) EDA for the given MANOVA is given as following 
 
Table no-1 
Between-Subjects Factors 
 Value Label N 
group 
0 Control 10 
1 Drug A 10 
2 Drug  B 10 
3 Drug C 10 
This table shows how many data points are there in each groups.
Table no-2
Descriptive Statistics 
 group Mean Std. Deviation N 
Low-density Lipoprotein 
Control 101.10 9.848 10 
Drug A 86.20 6.795 10 
Drug  B 121.40 9.834 10 
Drug C 83.20 4.442 10 
Total 97.98 17.165 40 
High-density Lipoprotein 
Control 58.70 6.075 10 
Drug A 53.70 3.466 10 
Drug  B 68.60 3.134 10 
Drug C 64.70 4.029 10 
Total 61.43 7.103 40
Table no-3 
Tests of Normality 
 group Kolmogorov-Smirnova Shapiro-Wilk 
 Statistic df Sig. Statistic df Sig. 
Low-density Lipoprotein 
Control .224 10 .170 .939 10 .540 
Drug A .204 10 .200* .886 10 .154 
Drug  B .116 10 .200* .958 10 .758 
Drug C .229 10 .148 .835 10 .038 
High-density Lipoprotein 
Control .154 10 .200* .946 10 .618 
Drug A .188 10 .200* .925 10 .404 
Drug  B .224 10 .168 .959 10 .769 
Drug C .131 10 .200* .944 10 .602 
*. This is a lower bound of the true significance. 
a. Lilliefors Significance Correction 
This shows that all groups are normal under Kolomogorov-Smirnov test. As p-value is 
more than .05 or .01 
Graph no-1 
 
All groups have different variability which we can see by varying length of the boxes. 
Central line shows the central values of the sample. There are outliers two shown by dots 
with number of sample value attached to it.  
b) We have three different versions of the new medication under test. We have 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). An EDA of data shows that each group (LDL/HDL with 
control or drug A B or C) have 10 participants in it. In LDL lowest mean is of drug C (M=83.20, 
SD= 4.442) and in HDL highest mean is of drug B(M=68.60 , SD=3.134) .
c) Following table shows descriptive statistics for the study 
Table no-4 
 group Mean Std. Deviation N 
Low-density Lipoprotein 
Control 101.10 9.848 10 
Drug A 86.20 6.795 10 
Drug  B 121.40 9.834 10 
Drug C 83.20 4.442 10 
Total 97.98 17.165 40 
High-density Lipoprotein 
Control 58.70 6.075 10 
Drug A 53.70 3.466 10 
Drug  B 68.60 3.134 10 
Drug C 64.70 4.029 10 
Total 61.43 7.103 40
2) Result of MANOVA is shown below: 
Table no-5 
Box's Test of Equality of 
Covariance Matricesa 
Box's M 15.168 
F 1.515 
df1 9 
df2 14851.910 
Sig. .136 
Tests the null hypothesis that 
the observed covariance 
matrices of the dependent 
variables are equal across 
groups. 
a. Design: Intercept + Group 
Here p-value is more than .05 so we accept the null hypothesis. The assumption of equality of 
covariance is met.
Table no-6 
Multivariate Testsa 
Effect Value F Hypothesis df Error df Sig. Noncent.

This assignment uses SSPS and since I'm not proficient in the software usage I'm looking for answers to the questions and a Main Task: Activity #8 You will submit one Word document for this activity....

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