What is the connection between regression to the mean and the bell-shaped normal

Question

What is the connection between regression to the mean and the bell-shaped normal curve?

Regression toward the mean does not influence distributions.

Without regression to the mean, distributions would all look bimodal instead of bell-shaped, like the normal curve. The normal curve's center is the mean, which is where most data lie due to regression toward the mean.

Without regression to the mean we would not be able to interpret distributions as it provides understanding of central tendency.

Regression to the mean is connected to the bell-shaped curve because it helps to minimize variance throughout the distribution.

Regression toward the mean does not influence distributions.

Without regression to the mean, distributions would all look bimodal instead of bell-shaped, like the normal curve. The normal curve's center is the mean, which is where most data lie due to regression toward the mean.

Without regression to the mean we would not be able to interpret distributions as it provides understanding of central tendency.

Regression to the mean is connected to the bell-shaped curve because it helps to minimize variance throughout the distribution.

Explanation / Answer

Ans:

Regression to the mean is connected to the bell-shaped curve because it helps to minimize variance throughout the distribution.

Regression to the mean is connected to the bell-shaped curve because it helps to minimize variance throughout the distribution.

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