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Quant Design And Analysis Report

   

Added on  2022-08-24

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Running head: Quant Design And Analysis
Quant Design And Analysis
Learner Name
Capella University
Quant Design And Analysis Report_1

Quant Design And Analysis2
Introduction
Information regarding the performance of students are given in the spss file. The objective of the
assignment is to conduct statistical tests to test a research question and also test the assumptions
underlying the test. The main variables to be tested are GPA and how it relates to gender, The
descriptives for the two variables are shown below.
Section 1: Data File Description
The dataset consists of 21 variables and the
test to be done here consists of analyzing
the properties of two variables. The
properties of all the variables in the dataset
are listed below:
Id - Qualitative, Nominal
Lastname - Qualitative, Nominal
Firstname - Qualitative, Nominal
Gender - Qualitative, Nominal
Ethnicity - Qualitative, Nominal
Year- Quantitative, Scale
Lowup – Quantitative, Ordinal
Section - Qualitative, Nominal
Gpa- Quantitative, Scale
Extcr - Qualitative, Nominal
Descriptives
Statistic
Std.
Error
gender Mean 1.39 0.048
95%
Confidence
Interval for
Mean
Lower
Bound 1.3
Upper
Bound 1.49
5% Trimmed Mean 1.38
Median 1
Variance 0.24
Std. Deviation 0.49
Minimum 1
Maximum 2
Range 1
Interquartile Range 1
Skewness 0.456 0.236
Kurtosis -1.828 0.467
gpa Mean 2.8622 0.06955
95%
Confidence
Interval for
Mean
Lower
Bound 2.7243
Upper
Bound 3.0001
5% Trimmed Mean 2.8873
Median 2.84
Variance 0.508
Std. Deviation 0.71266
Minimum 1.08
Maximum 4
Range 2.92
Interquartile Range 1.19
Skewness -0.22 0.236
Kurtosis -0.688 0.467
Quant Design And Analysis Report_2

Quant Design And Analysis3
Review- Qualitative, Nominal
quiz1- Quantitative, Scale
quiz2 - Quantitative, Scale
quiz3 - Quantitative, Scale
quiz4 - Quantitative, Scale
quiz5 - Quantitative, Scale
final - Quantitative, Scale
total - Quantitative, Scale
percent - Quantitative, Scale
grade - Nominal
passfail – Nominal
The sample size for the data is 105.
Section 2: Testing Assumptions
The t test done here works as it should under a few assumptions. They are:
1. The scale of measurement for the variables that are to be tested should be continuous or
ordinal
2. The data that is collected should be from a random sample.
3. The variables should have a normal distribution.
4. The last assumption is that of homogeneity of variance. Equal variance happens when
both the samples have equal variance.
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
gender .397 105 .000 .619 105 .000
Quant Design And Analysis Report_3

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