How to interpret the result according to the table below? Chi-Square Tests Asymptotic Significance (2-sided) Value df Pearson Chi-Square 2 ,034 Likelihood Ratio ,033 Linear-by-Linear Association 1 380 N of Valid Cases

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How to interpret the result according to the table below?
Chi-Square Tests
Asymptotic
Significance
(2-sided)
30 -
Value
df
Pearson Chi-Square
,034
Likelihood Ratio
033
Linear-by-Linear
Association
380
N of Valid Cases
a) Since 0.034<0.05, the Ho hypothesis is rejected
B) Since 0.033<0.05, the Ho hypothesis is rejected
NS) Since 0.034<0.5, the Ho hypothesis is rejected
O D) Since 0.380>0.05, the Ho hypothesis is accepted.
O TO) Since 0.033<0.5, the Ho hypothesis is rejected
2.
2.
Transcribed Image Text:How to interpret the result according to the table below? Chi-Square Tests Asymptotic Significance (2-sided) 30 - Value df Pearson Chi-Square ,034 Likelihood Ratio 033 Linear-by-Linear Association 380 N of Valid Cases a) Since 0.034<0.05, the Ho hypothesis is rejected B) Since 0.033<0.05, the Ho hypothesis is rejected NS) Since 0.034<0.5, the Ho hypothesis is rejected O D) Since 0.380>0.05, the Ho hypothesis is accepted. O TO) Since 0.033<0.5, the Ho hypothesis is rejected 2. 2.
Expert Solution
Step 1

Hypothesis testing 

Hypothesis testing is conducted for the parameters of the population like population mean, population standard deviation, and so on. It is to check whether the sample values conform to the pre-stated parameter values of the original distribution or not. The hypothesis for the single population mean is conducted using the z- or t-test. The selection of the test depends upon the value of the standard deviation.

There are three types of chi-square tests:

Chi-square test of independence
Chi-square test of homogeneity
Chi-square goodness of fit test

 

 

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