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A parameter is a fixed value that describes a characteristic of a population, such as the mean or standard deviation. A statistic is a calculated value that describes a characteristic of a sample, such as the sample mean or standard deviation.
A p-value is the probability of obtaining a test statistic as extreme or more extreme than the one observed, assuming the null hypothesis is true. It is used to determine the level of significance of a hypothesis test. A small p-value (typically less than 0.05) indicates strong evidence against the null hypothesis and in favor of the alternative hypothesis.
A confidence interval is a range of values that is likely to contain the true population parameter with a certain level of confidence. It is used to estimate population parameters based on sample data, and it indicates the level of precision of the estimate.
A chi-squared test is a statistical test used to determine if there is a significant difference between the observed frequencies and the expected frequencies in a contingency table. It is used to test hypotheses about categorical variables.
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