I’ll cover several ways to use prediction intervals in Minitab. Unlike confidence intervals, prediction intervals predict the spread for individual observations rather than the mean. Step 6: State an overall conclusion There is enough evidence in the data, at significance level 5%, to reject the null hypothesis and conclude that the true population proportion of people who approve the president’s performance so far is different than 40%. Like confidence intervals, predictions intervals have a confidence level and can be a two-sided range, or an upper or lower bound. Minitab Express will compute the t test statistic: t b 1 S E ( b 1) where S E ( b 1) ( e 2) n 2 ( x x ) 2. Therefore, we reject the null hypothesis. For a single slope in simple linear regression analysis, a two-sided, 100(1 ) confidence interval is calculated by 1±t1/2,n2sb where b1 is the calculated slope and Password. \begin Step 5: Make a decision The p-value of 0.00156 is less than our significance level, 5%. Since we want to compare the 95% confidence interval, we should use a significance level of 5% Step 3: Calculate the test statistic. \( H_0\colon p=0.40 \) vs \(H_a \colon p\ne0.4 \) Step 2: Decide on the significance level, \(\alpha\). Step 1: Set up the hypotheses and check conditions.
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