Hypothesis Testing

Front

What is a null hypothesis (H₀)?

Back

The null hypothesis (H₀) is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing.

Front

What is an alternative hypothesis (H₁)?

Back

The alternative hypothesis (H₁) is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.

Front

What does a right-tailed test indicate?

Back

A right-tailed test is used to determine if the sample statistic is significantly greater than the hypothesized parameter value.

Front

What is the level of significance (α)?

Back

The level of significance (α) is the probability of rejecting the null hypothesis when it is actually true, commonly set at 0.05.

Front

What is the difference between one-tailed and two-tailed tests?

Back

A one-tailed test checks for an effect in one direction, while a two-tailed test checks for effects in both directions.

Front

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

Back

If the p-value is less than α, it indicates strong evidence against the null hypothesis, leading to its rejection.

Front

What is a Type I error?

Back

A Type I error occurs when the null hypothesis is rejected when it is actually true.

Front

What is a Type II error?

Back

A Type II error occurs when the null hypothesis is not rejected when it is actually false.

Front

What is the purpose of hypothesis testing?

Back

The purpose of hypothesis testing is to make inferences about population parameters based on sample data.

Front

How do you state the null and alternative hypotheses for 'Less than 4% of high school students take Statistics'?

Back

H₀: X ≥ 4% and H₁: X < 4%.