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Name: Six different national brands of chocolate chip cookies were randomly
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Description: Six different national brands of chocolate chip cookies were randomly selected at the supermarket . The grams of fat per serving are as follows : 9; 9; 11; 8; 8. Assume the underlying distribution is approximately normal. NOTE: you are using a Studen

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Six different national brands of chocolate chip cookies were randomly selected at the supermarket . The grams of fat per serving are as follows : 9; 9; 11; 8; 8. Assume the underlying distribution is approximately normal. NOTE: you are using a Student's t- distribution , you may assume that the underlying population is normally distributed . (In general , you must first prove that assumption , though .) (PART A) construct a 90% confidence interval for the population mean grams of fat per serving of chocolate chip cookies sold in supermarkets (ii)Sketch the graph (iii) Calculate the error bound. (Round your answers to two decimal places) (PART B ) If you wanted a smaller error bound while keeping the same level of confidence, what should have changed in the study before it was a done? [a.]determine the population. standard deviation [ b.] increase the sample size [c.] decrease the sample size [d.]nothing can be changed to guarantee a smaller error bound

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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