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STAT200-2020- Introduction to Statistics-Final Examination-Awnsers 100%

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tification A and Ac ( complement of A) share no common region , and thus P(A AND Ac ) = 0. Therefore the statement is true (b). If the variance of a data set is 0, then all the observations in this data set must be zero. ...

tification A and Ac ( complement of A) share no common region , and thus P(A AND Ac ) = 0. Therefore the statement is true (b). If the variance of a data set is 0, then all the observations in this data set must be zero. Justification Variance is usually the expectation or mean of the squared deviation of a random variable from its mean. If the variance is zero, the squared deviations must be zero and thus the mean must be equal to every value. So , a variance of zero implies the observations are identical (c). If a 95% confidence interval for a population mean contains 1, then the 90% confidence interval for the same parameter must contain 1 Justification Confidence interval z-values: 90% confidence interval Z= 1.645 , For 95% confidence interval , Z= 1,96 To compute the confidence interval , we multiply the z -values with the standard error. Since 90% Confidence interval is smaller than that of 95% confidence interval, the condition will not always be met . Therefore, the statement is false. d) When plotted on the same graph, a distributitification A and Ac ( complement of A) share no common region , and thus P(A AND Ac ) = 0. Therefore the statement is true (b). If the variance of a data set is 0, then all the observations in this data set must be zero. Justification Variance is usually the expectation or mean of the squared deviation of a random variable from its mean. If the variance is zero, the squared deviations must be zero and thus the mean must be equal to every value. So , a variance of zero implies the observations are identical (c). If a 95% confidence interval for a population mean contains 1, then the 90% confidence interval for the same parameter must contain 1 Justification Confidence interval z-values: 90% confidence interval Z= 1.645 , For 95% confidence interval , Z= 1,96 To compute the confidence interval , we multiply the z -values with the standard error. Since 90% Confidence interval is smaller than that of 95% confidence interval, the condition will not always be met . Therefore, the statement is false. d) When plotted on the same graph, a distributi

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