Jacklyn created a sampling distribution that looks like a normal distribution. Her lead investigator recommended taking a larger sample. What would the new sampling distribution look like if Jacklyn increased the sample size?(choose the correct answer)-neither, they both will have the same shape-narrower (steeper)-becomes more positively skewed-wider (flatter) Jacklyn created a sampling distribution that looks like a normal distribution. Her lead investigatorrecommended taking a larger sample. What would the new sampling distribution look like ifJacklyn increased the sample size?34.15%34.15%2.15%2.15%0.15%13.55%13.55%0.15%30-20-10102030Neither, they both will have the same shape.narrower (steeper)becomes more positively skewedwider (flatter)

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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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Jacklyn created a sampling distribution that looks like a normal distribution. Her lead investigator recommended taking a larger sample. What would the new sampling distribution look like if Jacklyn increased the sample size?

(choose the correct answer)

-neither, they both will have the same shape

-narrower (steeper)

-becomes more positively skewed

-wider (flatter)

Jacklyn created a sampling distribution that looks like a normal distribution. Her lead investigator
recommended taking a larger sample. What would the new sampling distribution look like if
Jacklyn increased the sample size?
34.15%
34.15%
2.15%
2.15%
0.15%
13.55%
13.55%
0.15%
30
-20
-10
10
20
30
Neither, they both will have the same shape.
narrower (steeper)
becomes more positively skewed
wider (flatter)

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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