One proportion z ,chi square gof and t test review

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What is the null hypothesis (H0) in hypothesis testing?

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The null hypothesis (H0) is a statement that there is no effect or no difference, and it serves as the default assumption that a statistical test aims to challenge.

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In the context of hypothesis testing, what does p represent?

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In hypothesis testing, p represents the population proportion, which is the true proportion of a characteristic in the entire population.

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What is the alternative hypothesis (Ha)?

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

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What does a p-value indicate in hypothesis testing?

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A p-value indicates the probability of observing the test results, or something more extreme, assuming that the null hypothesis is true.

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What is the significance level (alpha) in hypothesis testing?

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The significance level (alpha) is the threshold for rejecting the null hypothesis, commonly set at 0.05 or 0.01.

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What is a one proportion z-test used for?

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A one proportion z-test is used to determine if the proportion of a single sample is significantly different from a known population proportion.

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What is a chi-square goodness of fit test?

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A chi-square goodness of fit test is used to determine if a sample distribution matches an expected distribution.

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What is the expected value in a chi-square goodness of fit test?

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The expected value in a chi-square goodness of fit test is the theoretical frequency of each category, calculated based on the null hypothesis.

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What is the formula for calculating the test statistic in a one proportion z-test?

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The test statistic for a one proportion z-test is calculated using the formula: z = (p̂ - p0) / sqrt[(p0(1 - p0)) / n], where p̂ is the sample proportion, p0 is the population proportion, and n is the sample size.

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

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