Module 12 Practice Questions (2)

Front

What is the conclusion when data provides strong evidence that two variables are linearly related?

Back

The variables have a linear relationship, indicating that changes in one variable are associated with changes in the other in a predictable manner.

Front

How is the Chi-Square test statistic calculated?

Back

The Chi-Square test statistic is calculated using the formula: χ² = Σ((O - E)² / E), where O is the observed count and E is the expected count.

Front

What is the expected count in a Chi-Square test?

Back

The expected count is the frequency that would be expected in a category if there were no association between the variables.

Front

What are the null and alternative hypotheses in hypothesis testing?

Back

The null hypothesis (H₀) states there is no effect or relationship, while the alternative hypothesis (H₁ or Hₐ) states there is an effect or relationship.

Front

What does a p-value indicate in hypothesis testing?

Back

A p-value indicates the probability of observing the data, or something more extreme, if the null hypothesis is true.

Front

What is the significance level in hypothesis testing?

Back

The significance level (α) is the threshold for rejecting the null hypothesis, commonly set at 0.05.

Front

What does it mean if the p-value is less than the significance level?

Back

If the p-value is less than the significance level, it suggests that there is sufficient evidence to reject the null hypothesis.

Front

What is a linear relationship between two variables?

Back

A linear relationship means that as one variable changes, the other variable changes in a consistent, proportional manner.

Front

What is the purpose of the Chi-Square test?

Back

The Chi-Square test is used to determine if there is a significant association between categorical variables.

Front

How do you interpret a Chi-Square test statistic of 2.00?

Back

A Chi-Square test statistic of 2.00 indicates the degree of difference between observed and expected counts, which can be assessed against a critical value to determine significance.