Chi-Square
Chi Square Assignment
Introduction
In this assignment, we will calculate a Chi Square and provide interpretations for it using the terminology we have learned in this course. 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. It is a statistical test to determine the significance of the difference in the observed frequencies.
Test of independence (Chi-square)
The independence test Chi-square allows us to determine whether there is a relationship between two categorical variables. It should be stressed that this test tells us whether there is a relationship between variables, but does not indicate the degree or type of relationship, that is, does not indicate the percentage of influence of one variable on another variable or causing influence (Plackett, 2008). A chi-square test is used with you have variables that are categorical rather than continuous.
The data I created is on the basis of questions ask by 54 respondents that how they enjoy the sports of tennis. Either by watching on TV, watching at the stadium or by playing themselves. After collecting the data, I used SPSS and run Chi-Square test. The result is as follows along with the questions of Exercise 1-4.
NPar Tests
Notes
Output Created
04-Nov-2011 11:57:17
Comments
Input
Data
E:\chi square 1.sav
Active Dataset
DataSet1
Filter
Weight
Number who preferred mode of enjoying tennis
Split File
N of Rows in Working Data File
3
Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics for each test are based on all cases with valid data for the variable(s) used in that test.
Syntax
NPAR TEST
/CHISQUARE=number
/EXPECTED=EQUAL
/MISSING ANALYSIS.
Resources
Processor Timea
00:00:00.000
Elapsed Time
00:00:00.000
Number of Cases Allowed
196608
a. Based on availability of workspace memory.
[DataSet1] E:\ chi square 1.sav
Chi-Square Test
Frequencies
Number who preferred mode of enjoying tennis
Observed N
Expected N
Residual
Play
13
18.0
-5.0
Watch on TV
17
18.0
-1.0
Watch at stadium
24
18.0
6.0
Total
54
Test Statistics
Number who preferred mode of enjoying tennis
Chi-Square
3.444a
df
2
Asymp. Sig.
.179
a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected ...