The sampling distribution of the mean becomes approximately normally distributed only when which of the following conditions is met? A single random sample is drawn from the population. A single random sample is drawn from the population. The standard deviation of the population is large. The standard deviation of the population is large. The sample size is large. The sample size is large. The population is not normally distributed.

Central Limit Theorem: (CLT): The CLT gives the sum of 'n' independently identically distributed…

Answered: The sampling distribution of the mean…

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter13: Probability And Calculus

Section13.3: Special Probability Density Functions

Problem 40E: Pygmy Height The average height of a member of a certain tribe of pygmies is 3.2ft, with a standard...

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The sampling distribution of the mean becomes approximately normally distributed only when which of the following conditions is met?

A single random sample is drawn from the population.

A single random sample is drawn from the population.
The standard deviation of the population is large.

The standard deviation of the population is large.
The sample size is large.

The sample size is large.
The population is not normally distributed.

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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