Here are summary statistics for randomly selected weights of newborn girls: \( \mathrm{n}=188, \overline{\mathrm{x}}=29.3 \mathrm{hg}, \mathrm{s}=6.7 \mathrm{hg} \). Construct a confidence interval estimate of the mean. Use a \( 95 \% \) confidence level. Are these results very different from th confidence interval \( 27.5 \mathrm{hg}<\mu<30.1 \mathrm{hg} \) with only 15 sample values, \( \bar{x}=28.8 \mathrm{hg} \), and \( s=2.4 \mathrm{hg} \) ? What is the confidence interval for the population mean \( \mu \) ? \( \square \mathrm{hg}<\mu<\square \mathrm{hg} \) (Round to one decimal place as needed.) Are the results between the two confidence intervals very different? A. No, because each confidence interval contains the mean of the other confidence interval. B. Yes, because the confidence interval limits are not similar. C. No, because the confidence interval limits are similar. D. Yes, because one confidence interval does not contain the mean of the other confidence inferval.

2. Use the list of data to make a box plot what is the tgis? \[ 5,8,1,3,5,11,5,8,4 \]

Out of 500 households sampled, 190 had kids under 18 living at home. Assuming the conditions are met, use the theoretical formula to construct a(n) \( 90 \% \) confidence interval for the true population proportion of households with kids under 18 living at home. a. Give your theoretical confidence interval in decimal form. Use 4 decimal places in your calculations and round your answers to four decimal places. ( \( 0.334,0.415 \) ) b. Interpret the confidence interval in context: We are \( 90 \% \) confident that the proportion of households with kids Show your formula and steps on paper or in the add work box (don't skip the between \( 34.43 \% \) and \( 41.57 \% \). interpretation above):

est: Final Jxam (Chapters 6 - 12) Fill in the blank. The \( \quad \) is the multiple coefficient of determination \( R^{2} \) modified to account for the number of variables and the sample size.

Why does it help to organize data in a table? A. It helps you pick a responding variable. B. It helps you determine a relationship between variables. C. It helps you erase the data that do not fit the claim. D. It helps you form a hypothesis.

Based on past experience, a bank believes that \( 9 \% \) of the people who receive loans will not make their payments on time. The bank has recently approved 200 loans. a. Write about and check each of the conditions needed in the context of this situation to use the sampling distribution for the proportion of people who will not make their payments on time (Central Limit Theorem). Conditions: distritution for the proportion of people who make their payment on time based on the cental limit theorem. we can proceeds to analyze the proportion of the sameple that does not make payment on time using normal approximation methods. What are the mean and standard deviation of this model? b. Mean = 18 c. Standard deviation (accurate to 4 decimal places) \( =4.047 \) d. What is the probability that \( 10 \% \) or more of these clients will not make timely payments to 4 decimal places? 0.312 .