Assignment 6: Non-Parametrics. Accounting, Finance, SPSS Term Paper

Assignment 6 – Non-parametrics
Your Name
Course Code
Professor
1st August 2018
Statistical Methods
Nova University
Assignment 6: Non-Parametrics
The first part of the non-parametric assignment entails determination of the Chi-Square Test of Association (Independence) to ascertain the cause of low high school graduation whereas the second part establishes the Chi-square goodness-of-fit-test. The first part determines Chi-Square among high school students and is based on assign_6_prob_1_data.sav dataset while the second part investigates the relationship between ethnicity and the general county population with regards to HIV aids and is based on the assign_6_prob_2_data.sav dataset.
Chi-Square Test of Association (Independence)
The Chi-Square test of association was used to determine the relationship between two study variables. The test is also used to establish whether or not the correlation between two variables: High School Diploma and Guidance Intervention Plan. The Chi-Square test is used to determine whether or not the two variables are statistically significant based on frequencies (Huck,2008, p. 417-420). In the determination of statistical significance, a 2x2 correlational cross-tabulation was used. Furthermore, contingency tables were used in the tabulation and presentation of the output results where rows and columns were used todistinctly represent the two variables respectively. First and foremost, the null hypothesis was stipulated as follows:
Null hypothesis (H0):There exists no association between the two depended variablesnamely High School Diploma and Guidance Intervention Plan.Chi-Square Test of Association was performed on the assign_6_prob_1_data.sav dataset using a confidence level of 95%. Frequency tables were generated using the two variables. The resulting frequency output table is depicted in the Table 1 as shown below.
Table 1: A Chi-square test of association frequency output
[DataSet1] 6_prob_1_data.sav
Statistics


High School Diploma

Guidance Intervention Plan

N

Valid

1496

1496


Missing

0

0

Frequency Table
High School Diploma


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

No

623

41.6

41.6

41.6


Yes

873

58.4

58.4

100.0


Total

1496

100.0

100.0


Guidance Intervention Plan


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

No

958

64.0

64.0

64.0


Yes

538

36.0

36.0

100.0


Total

1496

100.0

100.0


The case processing summary output was also capturedfrom assign_6_prob_1_data.sav dataset analysis as shown in table 2 below.
Table 2: SPSS V21 Case Processing Summary for a Chi-square test of association
Case Processing Summary


Cases


Valid

Missing

Total


N

Percent

N

Percent

N

Percent

High School Diploma * Guidance Intervention Plan

1496

100.0%

0

0.0%

1496

100.0%

SPSS V21 was used to analyze the assign_6_prob_1_data.sav dataset where cross-tabulation output results were captured. The cross-tabulation Chi-square test of association results are depicted in Table 3 as shown below.
Table 3:Chi-square test of association cross-tabulation Output Results
High School Diploma * Guidance Intervention Plan Cross tabulation


Guidance Intervention Plan

Total


No

Yes


High School Diploma

No

Count

577

46

623



Expected Count

399.0

224.0

623.0


Yes

Count

381

492

873



Expected Count

559.0

314.0

873.0

Total

Count

958

538

1496


Expected Count

958.0

538.0

1496.0

Chi-Square Test was also used to perform analysis on the assign_6_prob_1_data.sav dataset. The output results are shown in Table 4 as shown below.
Table 4: Chi-square test of association output results
Chi-Square Tests


Value

df

Asymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Pearson Chi-Square

378.628a

1

.000



Continuity Correctionb

376.505

1

.000



Likelihood Ratio

430.039

1

.000



Fisher's Exact Te...