# M7 Assignment Fall A 2020

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User Generated
Subject
Statistics
School
Arizona State University
Type
Homework
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Fall A 2020
M7 Assignment (30 points)
INSTRUCTION:
Use this Word document to fill in the answers to the questions. The answers must be supported
either by typing out the calculation process or by pasting SPSS output or data as instructed.
When prompted to paste something from the SPSS data or output file, you may use the
copy/paste function or take a screen shot of the relevant part to paste in as a picture.
Research Scenario:
This data set was also adapted from the longitudinal project examining cognitive functions of
the elderly, which has appeared in a few previous assignments. But this time there are
Q1. Prepare the data for analysis (16 points)
A. Importing data into SPSS
Import the Excel data set into SPSS and configure each variable based on the information in the
Codebook worksheet in the Excel file. Nominal variables should have the “Values” specified
under “Variable View”. Each variable should be correctly categorized in the “Measure” column
under “Variable View.” Submit the SPSS data file to earn the points. (1 point: deduct .5 for each
error up to 1 point total)
B. Checking for missing data
1. EXPLORE all the variables in the data file and report each variable that contains missing data:
The variable that contains the missing data for the data file includes Mini-Mental Status Exam,
Verbal IQ score, Age at 1st test session, Executive function at 1st test session, and Memory
function at 1st test session as described in the table below.
How many data points are missing?
The missing data points for each of the variables are 18.
What is the percentage of missing data?
Similarly, the percentage of the missing data from each variable is 36.0%.
the information in the output table(s) to indicate your answers to the questions above.

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Fall A 2020
Table 1
Case Processing Summary
Cases
Valid
Missing
Total
N
N
Percent
N
Percent
Mini Mental Status Exam
32
18
36.0%
50
100.0%
Verbal IQ score
32
18
36.0%
50
100.0%
Age at 1st test session
32
18
36.0%
50
100.0%
Executive function at 1st test session
32
18
36.0%
50
100.0%
Memory function at 1st test session
32
18
36.0%
50
100.0%
Hint 1: There are different routes to get the answers for these questions. After using SPSS to
explore missing data, take a look at the data points in the data sheet to double-check for
accuracy.
Hint 2: When we explore data from the whole sample, the variables are considered dependent
variables and there is no need to specify any “factor” (independent variable) because we don’t
want to separate the data points into separate groups according to any factor.
2. In your statistical analysis, will you adopt the approach of list-wise exclusion or pair-wise
exclusion for the missing data? Why? (1 point: .5 for the answer and .5 for the rationale)
During the statistical analysis, I will use list-wise exclusion for the missing data. The list-wise
exclusion approach drops the cased with the missing value in a selected specified variable,
allowing the analysis of the cases containing complete data points. Although pair-wise exclusion
may allow utilization of more data during a statistical exploration, the approach may cause
problems during the study because each model uses a different dataset. In this case, the use of
the list-wise method is to avert possible undue influence on the analysis, leading to skewed
reporting of the analysis results.
Hint: Either approach is acceptable with a logical rationale that demonstrates your
understanding of the two methods. In this scenario, be sure to consider how many data points
or subjects would be excluded with each method of exclusion.
C. Checking for outliers
1. For each scale variable, report whether there are outliers or not and, if so, how many? Paste
the outlier list and box plot for each scale variable here to support your answer.

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Fall A 2020 M7 Assignment (30 points) INSTRUCTION: Use this Word document to fill in the answers to the questions. The answers must be supported either by typing out the calculation process or by pasting SPSS output or data as instructed. When prompted to paste something from the SPSS data or output file, you may use the copy/paste function or take a screen shot of the relevant part to paste in as a picture. Research Scenario: This data set was also adapted from the longitudinal project examining cognitive functions of the elderly, which has appeared in a few previous assignments. But this time there are additional variables to analyze. Q1. Prepare the data for analysis (16 points) A. Importing data into SPSS Import the Excel data set into SPSS and configure each variable based on the information in the Codebook worksheet in the Excel file. Nominal variables should have the “Values” specified under “Variable View”. Each variable should be correctly categorized in the “Measure” column under “Variable View.” Submit the SPSS data file to earn the points. (1 point: deduct .5 for each error up to 1 point total) B. Checking for missing data 1. EXPLORE all the variables in the data file and report each variable that contains missing data: The variable that contains the missing data for the data file includes Mini-Mental Status Exam, Verbal IQ score, Age at 1st test session, Executive function at 1st test session, and Memory function at 1st test session as described ...
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