The mean weight of a single newborn baby at City Central Hospital is 111.2 ounces with a standard deviation of 16.05 ounces. Let us assume that the weight, X, of any baby born at City Central is independent of the weight of any other baby born at City Central. We will not consider multiple births. City General expects 1111 babies to be born in 2022. Suppose we look at the weight of each newborn baby at City General in 2022. Let M be the random variable representing the mean weight of all the 1111 newborn babies expected. Let T = the random variable representing the total weight of all the 1111 newborn babies expected. d) If TK is the total weight of the 1111 babies measured in pounds, then what is the standard deviation of TK?  e) What is the approximate probability that T is greater than 125000 ounces?  f) What is the standard deviation of M?

What test can be used to test the difference between two means when the population standard deviations are known Ox² Oz Ot OF

Do the mean weights of male college freshmen and male college seniors differ? There are arguments for and against this question. The mean weight, μx of college freshmen will be compared to the mean weight, My of college seniors. The true values of Mx and My are unknown. It is recognized that the true standard deviations are x = 13 for male college freshmen and dy = 24 for male college seniors. We take a random sample of m = 431 college freshmen and a random sample of n=289 college seniors. The mean weights were x = 178 for male college freshmen and y = 185 for male college seniors. Assuming independence between the samples and assuming the weights are normally distributed we would like to estimate My - My. a) What is the standard deviation of the distribution of x?[ b) What is the standard deviation of the distribution of x-y? c) Create a 95% confidence interval for Mx - Hy? d) What is the length of the confidence interval in part c) ? e) If we let n stay at 289 but vary m, what is the…

To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 40 feet. Assume the population standard deviation is 4.9 feet. The mean braking distance for Make B is 44 feet. Assume the population standard deviation is 4.6 feet. At a = 0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e). Click here to view page 1 of the standard normal distribution table. Click here to view page 2 of the standard normal distribution table. (a) Identify the claim and state H, and Ha. What is the claim? A. The mean braking distance is different for the two makes of automobiles. B. The mean braking distance is less for Make A automobiles than Make B…