The central limit theorem states that as sample size increases, the sampling distribution of the mean becomes-- more normally distributed more normally distributed less normally distributed but more leptokurtic less normally distributed but more leptokurtic more shaped like the population distribution more shaped like the population distribution smaller than the population mean

Consider that x̅ is the sample mean.

Answered: The central limit theorem states that…

Holt Mcdougal Larson Pre-algebra: Student Edition 2012

1st Edition

ISBN:9780547587776

Author:HOLT MCDOUGAL

Publisher:HOLT MCDOUGAL

Chapter11: Data Analysis And Probability

Section11.4: Collecting Data

Problem 5E

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The central limit theorem states that as sample size increases, the sampling distribution of the mean becomes--

more normally distributed

more normally distributed
less normally distributed but more leptokurtic

less normally distributed but more leptokurtic
more shaped like the population distribution

more shaped like the population distribution
smaller than the population mean

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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