Null and Alternative Hypotheses

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What is a null hypothesis?

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The null hypothesis (H0) is a statement that there is no effect or no difference, and it serves as a starting point for statistical testing.

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What is an alternative hypothesis?

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

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What does it mean if a null hypothesis is rejected?

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Rejecting the null hypothesis suggests that there is sufficient evidence to support the alternative hypothesis.

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What is the significance level in hypothesis testing?

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

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What is a one-tailed test?

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A one-tailed test is a hypothesis test that evaluates the direction of the effect, either greater than or less than a certain value.

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What is a two-tailed test?

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A two-tailed test is a hypothesis test that evaluates whether a parameter is significantly different from a specified value, without specifying a direction.

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What does 'p-value' represent in hypothesis testing?

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

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What is the difference between a Type I and Type II error?

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A Type I error occurs when the null hypothesis is rejected when it is true, while a Type II error occurs when the null hypothesis is not rejected when it is false.

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What is the role of sample size in hypothesis testing?

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Larger sample sizes generally provide more reliable estimates and increase the power of a hypothesis test to detect an effect.

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What does 'no more than' imply in hypothesis formulation?

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'No more than' indicates a maximum limit, suggesting that the parameter is less than or equal to a specified value.