Hypothesis Testing-Mean (Large Sample)

Front

What is a hypothesis in hypothesis testing?

Back

A hypothesis is a statement or assumption about a population parameter that can be tested using statistical methods.

Front

What is the 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 the alternative hypothesis (Ha)?

Back

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

Front

What does α (alpha) represent in hypothesis testing?

Back

α (alpha) represents the significance level, which is the probability of rejecting the null hypothesis when it is actually true.

Front

What is a Type I error?

Back

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

Front

What is a Type II error?

Back

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

Front

What is a p-value?

Back

A p-value is the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Front

How do you interpret a p-value less than α?

Back

If the p-value is less than α, you reject the null hypothesis, indicating that there is sufficient evidence to support the alternative hypothesis.

Front

What is the formula for the z-test statistic for a sample mean?

Back

The formula is z = (X̄ - μ) / (σ/√n), where X̄ is the sample mean, μ is the population mean, σ is the population standard deviation, and n is the sample size.

Front

What does it mean to 'reject the null hypothesis'?

Back

To reject the null hypothesis means that the evidence suggests that the null hypothesis is not true, and the alternative hypothesis may be true.