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Name: A psychologist is studying smokers' self-images, which she measures by
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Description: A psychologist is studying smokers' self-images, which she measures by the self-image (SI) score from a personality inventory. For adults in the U.S., the mean SI score from this inventory is about 150.The psychologist gathers a random sample of 15 S

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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A psychologist is studying smokers' self-images, which she measures by the self-image (SI) score from a personality inventory. For adults in the U.S., the mean SI score from this inventory is about 150.The psychologist gathers a random sample of 15 SI scores of smokers and finds that their mean is 126 and their standard deviation is 37. Assume that the population of SI scores of smokers is normally distributed with mean μ. Based on the sample, can the psychologist conclude that μ is different from 150? Use the 0.05 level of significance. Perform a two-tailed test. Then fill in the table below.Carry your intermediate computations to at least three decimal places and round your answers as specified in the table.


The null hypothesis:	H0:
The alternative hypothesis:	H1:
The type of test statistic:	(Choose one) Z t Chisquare F

The value of the test statistic: (Round to at least three decimal places.)
The p-value: (Round to at least three decimal places.)
At the 0.05 level of significance, can the psychologist conclude that the mean SI score among smokers is different from 150?	Yes	No

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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