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BTM8107-8 Week 8 Apply MANOVA

  • From Mathematics, Statistics
  • Due on 06 Sep, 2015 11:37:00
  • Asked On 04 Sep, 2015 10:39:40
  • Due date has already passed, but you can still post solutions.
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I will upload Activity 8.sav once I select tutor. I would like to received the SPSS output. Thanks


Instructions:You will submit one Word document. You will create this Word document by cutting and pasting SPSS output into Word.

Part A. SPSS Assignment
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.
    1. Perform exploratory data analysis on the relevant variables in the dataset. When possible, include appropriate graphs to help illustrate the dataset.
    2. Compose a one to two paragraph write up of the data.
    3. 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.
    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.
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  • Submitted On 04 Sep, 2015 01:27:26
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Part A. SPSS Activity Between-Subjects Factors N Group .00 10 1.00 10 2.00 10 3.00 10 Descriptive Statistics Group Mean Std. Deviation N HDL dimension1 .00 101.1000 9.84829 10 1.00 86.2000 6.79542 10 2.00 121.4000 9.83418 10 3.00 83.2000 4.44222 10 Total 97.9750 17.16509 40 LDL dimension1 .00 58.7000 6.07454 10 1.00 53.7000 3.46570 10 2.00 68.6000 3.13404 10 3.00 64.7000 4.02906 10 Total 61.4250 7.10322 40 This table displays all the descriptive statistics by variable HDL and LDL with 4 levels. It shows the descriptive statistics of all other variables by taking these 4 categories. Multivariate Testsc Effect Value F Hypothesis df Error df Sig. Intercept Pillai's Trace .997 6049.563a 2.000 35.000 .000 Wilks' Lambda .003 6049.563a 2.000 35.000 .000 Hotelling's Trace 345.689 6049.563a 2.000 35.000 .000 Roy's Largest Root 345.689 6049.563a 2.000 35.000 .000 Group Pillai's Trace 1.347 24.749 6.000 72.000 .000 Wilks' Lambda .087 27.921a 6.000 70.000 .000 Hotelling's Trace 5.520 31.277 6.000 68.000 .000 Roy's Largest Root 4.379 52.548b 3.000 36.000 .000 a. Exact statistic b. The statistic is an upper bound on F that yields a lower bound on the significance level. c. Design: Intercept + Group The "multivariate tests" section consecutively checks each factor influence on the dependent groups. This is the vital table in this output. Each feature and each covariate has a key influence, as well as the intercept. Here these effects are verified by four tests. Hotelling's Trace is usually used for two dependent groups and Wilks' Lambda if there are more than two groups, as there are in this example. The significance of the F tests displays if that effect is important as the P-value is less than .05 in this case. Tests of Between-Subjects Effects Source Dependent Variable Type III Sum of Squares df Mean Square F Sig. Corrected Model dimension1 HDL 9154.475a 3 3051.492 47.016 .000 LDL 1293.075b 3 431.025 22.998 .000 Intercept dimension1 HDL 383964.025 1 383964.025 5915.988 .000 LDL 150921.225 1 150921.225 8052.711 .000 Group dimension1 HDL 9154.475 3 3051.492 47.016 .0...
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