A quality control specialist at a cake bakery collected a sample of cupcakes with weights (in grams): 101, 122, 111, 99, 97, 89, 131, 95, 109 and 96. a. Assuming the cake weights are normally distributed with known population standard deviation of 15g. construct a 99% confidence interval for the true mean cake weight. b. How large should the sample size be for the 95 % confidence interval length to be raining more than 12g

A quality control specialist at a cake bakery collected a sample of cupcakes with weights (in grams): 101, 122, 111, 99, 97, 89, 131, 95, 109 and 96. a. Assuming the cake weights are normally distributed with known population standard deviation of 15g. construct a 99% confidence interval for the true mean cake weight. b. How large should the sample size be for the 95 % confidence interval length to be raining more than 12g

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.4: Distributions Of Data

Problem 19PFA

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Question

8. A quality control specialist at a cake bakery collected a sample of cupcakes with weights (in grams): 101, 122, 111, 99, 97, 89, 131, 95, 109 and 96. a. Assuming the cake weights are normally distributed with known population standard deviation of 15g. construct a 99% confidence interval for the true mean cake weight. b. How large should the sample size be for the 95 % confidence interval length to be raining more than 12g?

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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