What statistical rule is associated with normal distribution for 1, 2, and 3 standard deviations from the mean?

What statistical rule is associated with normal distribution for 1, 2, and 3 standard deviations from the mean?

• A. 80%/90%/95% rule
• B. 50%/75%/85% rule
• C. 68%/95%/99% rule
• D. 60%/80%/90% rule

Answer: (C)

The statistical rule associated with normal distribution that describes the percentage of data that falls within one, two, and three standard deviations from the mean is known as the 68-95-99.7 rule. This rule states that approximately 68% of the data points lie within one standard deviation of the mean, about 95% lie within two standard deviations, and approximately 99.7% lie within three standard deviations. This characteristic of the normal distribution allows psychologists and researchers to understand how data is distributed around the mean and to make predictions about likelihoods within defined intervals. The percentages provided in the other options do not align with the established properties of the normal distribution, which is why they are not the correct choice. Understanding this rule is essential for interpreting data and conducting analyses that involve normally distributed variables.

The statistical rule associated with normal distribution that describes the percentage of data that falls within one, two, and three standard deviations from the mean is known as the 68-95-99.7 rule. This rule states that approximately 68% of the data points lie within one standard deviation of the mean, about 95% lie within two standard deviations, and approximately 99.7% lie within three standard deviations. This characteristic of the normal distribution allows psychologists and researchers to understand how data is distributed around the mean and to make predictions about likelihoods within defined intervals.

The percentages provided in the other options do not align with the established properties of the normal distribution, which is why they are not the correct choice. Understanding this rule is essential for interpreting data and conducting analyses that involve normally distributed variables.