APPLYING ANOVA AND NONPARAMETRIC TESTS SIMULATION

Applying ANOVA and Nonparametric Tests Simulation



Applying ANOVA and Nonparametric Tests Simulation

The data set

the data set that we are going to use in this research paper is based on a survey of 116 'young' people that smoke and considers variables related to their intention to stop smoking. The total number of variables in this study are 28.

These variables have information regarding demographic factors, ratings on visual analogues scales (perceived risk, self efficacy, subjective norms and intentions to stop smoking), information on previous smoking related illnesses, health value ratings and 18 items from a reliable and valid questionnaire.

ANOVA

annual income and amount spent on car

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

4.574E9

9

5.082E8

.

.

Within Groups

.000

0

.

Total

4.574E9

9

Mean and st.dev of smoking related illness is mean=.49 and st.dev=.502. we run a t test for examine the association among the two variables (smoking related illness and age group) value of t calculated is = 10.540 and 56.612 df = 115 and 115 simultaneousely.

=> "smoking related illness ever" in "no of cigarettes"

One-Sample Statistics for the data set

N

Mean

Std. Deviation

Std. Error Mean

Smoking related illness ever

116

.49

.502

.047

Reported number of cigarettes before midday

116

2.63

3.412

.317

One-Sample Test

Test Value = 0

t

df

Sig. (2-tailed)

Mean Difference for the data set

95% Confidence Interval of the Difference for the data set

Lower

Upper

Smoking related illness ever

10.540

115

.000

.491

.40

.58

Reported number of cigarettes before midday

8.299

115

.000

2.629

2.00

3.26

Mean and st.dev of smoking related illness is mean=.49 and st.dev=.502 and for no. of cigrattes mean= 2.63 and st.dev=3.412. we run a t test for examine the association among the two variables (smoking related illness and no. of cigrattes) value of t calculated is = 10.540 and 8.299 df = 115 and 115 simultaneousely.

=> health value ratings

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference for the data set

Lower

Upper

Health value

Hypothesis: Equal variances assumed

2.692

.104

.039

114

.969

.034

.875

-1.698

1.767

Hypothesis: Equal variances not ...