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# Presented By: ang ling poh ong mei yean soo pei zhi - PowerPoint PPT Presentation

QIM 511 SPSS : Chi-Square Test. Presented By : ang ling poh ong mei yean soo pei zhi. Nonparametric Techniques. Is used when having serious violations of distribution assumptions or not normal Appropriate for data measured on scales that are not interval or ratio.

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SPSS: Chi-Square Test

### Presented By:ang ling pohongmei yeansoopeizhi

• Is used when having serious violations of distribution assumptions or not normal

• Appropriate for data measured on scales that are not interval or ratio.

• Selection of nonparametric techniques are:

• Chi-square tests

• Mann-Whitney test

• Wilcoxon signed-rank test

• Kruskal-Wallis test

• Friedman test

• Spearman’s rank-order correlation

• 2 Main types

• 3 assumptions to deal before conducting chi-square tests:

• Random sampling

• Independence of observations

• Size of expected frequencies

• used to compare observed and expected frequencies in each category.

• sample size is usually small

• Steps to conduct chi-square test for goodness of fit:

• Click on Weight Cases to open the dialogue box

• Click on the Weight cases by radio button

• Select the relevant variable and move to Frequency Variable

• Click on Nonparametric Tests and then Chi Square

• Select the required variable to move into Test Variable List box

• You can see from the output that the chi-square value is no significant (p > .05).

Example

Color preference of 150 people, p < 0.05

Color preference of 150 people

Calculate chi-square percentage or ratios.

2 = Chi-square

O = Observed frequency

E = Expected frequency

k = number of categories, groupings, or possible outcomes

Calculate chi-square percentage or ratios.

2 = 26.95

Calculate Degrees of freedom ( percentage or ratios.df)

• Refers to the number of values that are free to vary after restriction has been placed on data.

• Defined as N- 1, the number in the group minus one restriction.

df = N – 1

= 5 – 1

= 4

Critical percentage or ratios.2 values

2 = 26.95 , df = 4 , p < 0.05

• If chi-square value is bigger than critical value, reject null hypothesis.

• If chi-square value is smaller than critical value, fail to reject null hypothesis.

Critical 2

Chi-square Test for Relatedness or Independence percentage or ratios.

• Used to evaluate group differences when the test variable is nominal, dichotomous, ordinal, or grouped interval.

• A test of the influence or impact that a subject’s value on one variable has on the same subject’s value for a second variable.

Chi-square Test for Relatedness or Independence percentage or ratios.

• Steps to conduct chi-square test for goodness of fit:

• Click on Descriptive Statistics and then Crosstabs

• Select a row and column variable to move into the respective box

• Click on Statistics command pushbutton to open Crosstabs: Statistics subdialogue box

• Click on the Chi-square check box then Continue

• Click on the Cells subdialogue box

• In the Counts box, click on the Observed and Expected check boxes

• In the Percentages box, click on the Row, Column andTotal check boxes

• Click on Continue and then OK.

Interpreting Chi square test for Relatedness or Independence percentage or ratios.

Example

Incidence of three types of malaria in three tropical regions.

H0 : The two categorical variables are independent.

H1. : The two categorical variables are related.

Calculate expected frequency percentage or ratios.

e = expected frequency

c = frequency for that column

r = frequency for that row

n = total number of subjects in study

Calculate expected frequency percentage or ratios.

90 x 86

e =

250

= 30.96

Calculate chi-square percentage or ratios.

2 = 125.516

Calculate Degrees of freedom ( percentage or ratios.df)

df = (r-1)(c-1)

= (3-1)(3-1)

= (2)(2)

= 4

r = number of categories in the row variable

c = number of categories in the column variable

Find critical percentage or ratios.2 values

2 = 125.516 , df = 4 , p < 0.05

Critical 2

Chi-square value is bigger than critical chi-square value, reject null hypothesis.

REFERENCES percentage or ratios.

• Green, S. B., Salkind, N. J., & Akey, T. M. (2000). Using SPSS for Windows: Analyzing and understanding data (2nd ed.). New Jersey: Prentice Hall.

• Coakes, S. J., Steed, L., & Ong, C. (2010). SPSS:analysis without anguish: version 17.0 for Windows (Version 17.0 ed.). McDougall Street, Milton, Qld: John Wiley & Sons Australia, Ltd.

• Hinkle, Wiersma, & Jurs. Chi-square test for goodness of fit. Retrieved from http://www.phy.ilstu.edu/slh/chi-square.pdf

• Penn State Lehigh Valley. Chi-square test. Retrieved 9 March, 2011, from http://www2.lv.psu.edu/jxm57/irp/chisquar.html