What is the formula for the Chi-Square statistic (χ²)?

χ2=(ObservedExpected)2Expected\chi^2 = \sum \frac{(Observed - Expected)^2}{Expected}

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What is the formula for the Chi-Square statistic (χ²)?

χ2=(ObservedExpected)2Expected\chi^2 = \sum \frac{(Observed - Expected)^2}{Expected}

How do you calculate expected frequencies?

Expected Frequency = (Probability of category) * (Total number of observations)

How to calculate degrees of freedom (df)?

df = Number of categories - 1

What is the Chi-Square Goodness of Fit Test?

A test to determine if an observed frequency distribution matches a theoretical expected distribution.

What is the Null Hypothesis (H₀) in a Chi-Square test?

The observed distribution is the same as the expected distribution.

What is the Alternative Hypothesis (Hₐ) in a Chi-Square test?

The observed and expected distributions are significantly different.

What is the significance level (α)?

The threshold for rejecting the null hypothesis (H₀).

What are degrees of freedom (df) in a Chi-Square test?

Number of categories - 1.

What are the differences between Observed and Expected frequencies?

Observed: Actual counts in the sample. | Expected: Counts predicted by the null hypothesis.

What are the differences between a small and large Chi-Square statistic?

Small χ²: Supports H₀, observed and expected are similar. | Large χ²: Suggests expected counts are inaccurate, leading to rejection of H₀.

What are the differences between rejecting and failing to reject the null hypothesis?

Reject H₀: Concluding there is enough evidence for Hₐ. | Fail to reject H₀: Concluding there is not enough evidence for Hₐ.