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chi-square test statistic is statistically significant.
What is Test Statistic?
A statistic employed in statistical hypothesis testing is known as a test statistic. A test statistic, which can be thought of as a numerical summary of a data set that condenses the data into a single value that can be used to conduct the hypothesis test, is how a hypothesis test is commonly expressed.
To determine whether the amount of television a person watches is related to their liking for bourbon whisky, the researcher could use a chi-square test of independence.
The chi-square test is a statistical test that is used to determine whether there is a significant association between two categorical variables.
In this case, the two variables of interest are television watching (more or less than 2 hours per day) and liking for bourbon whisky (measured using a Likert scale).
The chi-square test statistic is calculated based on the observed frequencies of each combination of television watching and liking for bourbon whisky, and it is used to determine whether the observed frequencies are significantly different from the frequencies that would be expected if the two variables were independent.
If the chi-square test statistic is statistically significant, it indicates that there is a significant association between the two variables, and the researcher can conclude that television watching is related to liking for bourbon whisky.
Hence, chi-square test statistic is statistically significant.
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