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8/12/2019 Non Paramarketingmetric Test

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NON PARAMETRIC TESTS

Dr. Vipul Patel

Non parametric Tests2

Chi Square Analysis

Mann Whitney U Test

KruskalWallis Test for Several Independent

Samples

Wilcoxon Signed Ranks Test for Two Related

Samples

Friedman Test


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Chi Square Test3

Chi Square test is used to explore the relationship

between two categorical data.

Consider the case of cola brand preferences of

college students in Ahmedabad.

Null Hypothesis:

There is no association between sex of respondents

and preference of three cola brands.

Open the SPSS file named: cola.sav

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We have two categorical variable

Sex: Male and Female

Cola brands: Brand A, Brand B and Brand C


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Narration of the result6

The Pearson Chi-Square statistic is used to determinewhether there is an association between preference forthe three brands of cola and the gender of thestudents. The Pearson Chi-Square value is statisticallysignificant, 2 (df = 2) = 17.51, p < 0.05. So it can beconcluded that that there is an association betweenpreference for the three brands of cola and the genderof the students. Looking at the Cross-Tabulation table, itcan be seen that the majority of the male subjects

prefer Brand C (Count = 15) over Brand A (Count = 4)and Brand B (Count = 2). For female subjects, theirpreference was for Brand B (Count = 11), followed byBrand A (Count = 8) and Brand C (Count = 2).


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Mann Whitney U Test7

It is a non parametric test for independent sample t

test.

It is used to compare the difference between two

independent groups.

Two variables are required.

One Independent variable categorical having two

category

One Dependent variable continuous.

Case:8

Open the SPSS file: teacher_income.sav

Null hypothesis:

There is no difference in income of teachers in two B

schools.

Here we have two variables:

Independent categorical variable: School A and School

B

Dependent continuous variable: income


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Mann Whitney U Test was performed to determine

the deference in the income of teachers in two B

Schools. Mann Whitney U statistic is 15 and is

significant, p


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KruskalWallis Test11

The KruskalWallis test is a nonparametric test that

is used with an independent groups design

comprising of more than two groups.

It is a nonparametric version of the one-way

ANOVA.

Two variables are required.

One Independent variable having more than two

categories.One Dependent variable continuous.

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Open the SPSS file: instruction.sav

Null hypothesis:

There is no difference in the effectiveness of three

different methods of instruction.

Here we have two variables:

Independent categorical variable: Methods of

Instruction: A, B and C

Dependent continuous variable: effectiveness score


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Narration of Result14

KruskalWallis test was performed to determine the

difference in effectiveness of three methods of

instructions. Kruskal Wallis chi square statistic is

9.896 and is significant, p


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Wilcoxon Signed Ranks Test15

Wilcoxon Signed Ranks Test is a non parametric

version of the paired sample t test.

It is used to compare the difference between two

set of data obtained from same people.

We required two set of continuous data on the

same subject or entity paired in some manner.

Case16

Open the SPSS file: drug.sav

Null Hypothesis

There in no difference in problem solving skills (i.e.,

no. of correct responses) before and after taking

the drug.

We have two variables

Correct responses before taking the drug.

Correct responses after taking the drug.


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Narration of Result18

Wilcoxon Signed Ranks Test is performed to test the

null hypothesis that the drug does not improve

problem-solving skills, i.e., it has no effect. Wilcoxon

Singed Rank statistic, Z is -1.103 and is not

significant, p>0.05. Null hypothesis can not be

rejected. It can be concluded that the drug has no

effect.


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Friedman Test19

Friedman test is used to analyze more than two sets

of scores obtained from the same individuals.

It is used to compare the difference among more

than two sets of data obtained from same people.

We required more than two sets of continuous data

on the same subject or entity paired in some

manner.

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Open the SPSS file: problem_solving.sav

Null Hypothesis

There in no difference in problem solving ability at

three different times of day (i.e, morning, afternoon

and evening).

We have three variables:

Correct responses in the morning.

Correct responses in the afternoon.

Correct responses in the evening.


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Narration of the result22

The Friedman test was performed to test the null

hypothesis that the time of the day makes no

difference to the subjects problem-solving ability

(number of correct responses obtained). The results

indicated that the Friedman Chi square statistic is

10.364 and significant, p < .05. Thus, it can be

concluded that the time of the day did have a

significant effect on subjects problem-solving

ability.


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Thank You!!!

Dr. Vipul Patel

[email protected]

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