CHI SQUARE REPORT ASSIGNMENT

Chi Square Report Assignment



Chi Square Report Assignment

Section I - Data File Description

In this assignment, we will calculate a Chi Square and provide interpretations for it using the terminology we have learned in this course. we will also examine two independent variables and whether those variables are independent of one another. Since this involves the determination if the distribution of one variable is contingent on the second variable, this assignment requires an analysis of a contingency table. Specifically, we will be examining if the presence of social problems is related to whether or not a student dropped out of school. Additionally, we will be examining the two test assumptions for Chi Square.

We also calculate a Pearson Chi Square for the two independent variables of social problems (SOCPROB) and dropping out of high school (DROPOUT).

Data

Variables code

•SOCPROB - communal difficulties in ninth degree: 1 = yes; 0 = no.

•DROPOUT - 1 = dropped out during high school; 0 = did not drop out.

Sample size

A number of 88 people participated in this study and there is not any missing value in the final data.

Section II - Assumptions, Data Screening, and Verification of Assumptions

The Chi rectangle Test of self-reliance checks the association between 2 categorical variables.

Pearson's chi-square (?2,  spoke  ki) check is the best-known of  some  chi-square checks - statistical  methods  whose  outcomes  are  assessed  by  quotation  to the chi-square distribution. Its properties were first  enquired  by Karl Pearson in 1900.[1] In contexts where it is  significant  to make a distinction between the ascertain statistic and its  circulation,   titles   alike  to Pearson X-squared  check  or statistic are used.

It tests a null hypothesis claiming that the frequency circulation of certain happenings discerned in a experiment is dependable with a exact theoretical distribution. The happenings suggested should be mutually exclusive and have total prospect 1. A prevalent case for this is where the happenings each cover an deduction of a categorical variable. A clear-cut demonstration is the hypothesis that an commonplace six-sided pass away is "fair", i.e., all six deductions are equally likely to occur.

Pearson's chi-square is  utilised  to  consider  two  kinds  of comparison:  checks  of goodness of fit and  checks  of independence. A  check  of goodness of fit  sets up   if  or not an  discerned  frequency distribution  disagrees  from a theoretical distribution. A  check  of  self-reliance  assesses  if  paired  facts  on two variables,  conveyed  in a contingency table, are  ...