Hypothesis Testing and Statistical Tests

These flashcards cover key concepts in hypothesis testing, statistics, and specific tests such as the t-test, correlation, and chi-square tests.

What is the null hypothesis (H₀)?

The assumption that there is no effect or difference (e.g., μ = 75).

What is a Type I error?

Rejecting a true null hypothesis (false positive).

What is a Type II error?

Failing to reject a false null hypothesis (false negative).

What happens when you increase alpha from .01 to .05?

You increase the chance of rejecting H₀ and increase the risk of a Type I error.

What is the critical region?

Values of the test statistic where you reject H₀.

When do you use an independent samples t-test?

To compare the means of two independent groups.

What is the formula for pooled variance?

sp² = (SS1 + SS2) / (df1 + df2), sp² = df1 + df2 / (SS1 + SS2).

What is the null hypothesis for independent t-test?

μ1 − μ2 = 0.

What lowers standard error?

Large sample size and small sample variance.

What does homogeneity of variance mean?

Both groups are assumed to have equal population variances.

What does a positive correlation mean?

As X increases, Y increases.

What does a correlation of -0.85 indicate?

Strong negative relationship.

How do you interpret r² (coefficient of determination)?

The proportion of variance explained by the relationship.

What correlation is used for two categorical variables (yes/no)?

Phi-coefficient.

Pearson’s r is appropriate when…?

Both variables are continuous and normally distributed.

When do you use a chi-square test?

When data is in categories (frequencies).

What is the formula for chi-square?

χ² = ∑(O−E)²/E.

What are expected frequencies in goodness-of-fit with 3 categories and n = 90?

30, 30, 30.

What are valid values for observed frequencies?

Positive whole numbers only.

What does the chi-square test for independence do?

Tests whether two categorical variables are related.