1 proportion significance test

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What is a significance test?

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A significance test is a statistical method used to determine if there is enough evidence to reject a null hypothesis in favor of an alternative hypothesis.

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What does the null hypothesis (H0) represent in a proportion significance test?

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The null hypothesis (H0) represents the statement that there is no effect or no difference, often stating that the population proportion is equal to a specified value.

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What is the alternative hypothesis (Ha) in a proportion significance test?

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The alternative hypothesis (Ha) represents the statement that there is an effect or a difference, indicating that the population proportion is not equal to the specified value.

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What is a p-value?

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

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What does a low p-value indicate?

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A low p-value (typically less than 0.05) indicates strong evidence against the null hypothesis, leading to its rejection.

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What is the significance level (α)?

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The significance level (α) is the threshold for determining whether to reject the null hypothesis, commonly set at 0.05.

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What is a z-score in the context of a proportion significance test?

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A z-score measures how many standard deviations an element is from the mean, used to determine the position of the sample proportion relative to the null hypothesis.

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How do you calculate the z-score for a proportion?

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What is the standard error (SE) of a proportion?

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What is a critical value in hypothesis testing?

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A critical value is a point on the scale of the test statistic beyond which we reject the null hypothesis, determined by the significance level.