Why is the mean the best measure of central tendency for a normal distribution quizlet?

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that if you go out 2 standard deviations on both sides of the mean in a normal distribution, you will find approximately 95% of the cases.

Example 1

The mean for a group equals 35 and the standard deviation equals 6. Two standard deviations equals 12 points (2 x 6 = 12). Thus, if you (a) go up 12 points from the mean (35 + 12 = 47) and (b) go down 12 points from the mean (35 - 12 = 23), you have identified the scores (47 and 23) between which approximately 95% of the cases lie.

The 99% rule says that if we go up and down 3 standard deviations from the mean, we find approximately 99% of the cases.

For the information in Example 1, multiply 3 times the standard deviation (3 x 6 = 18). Going up and down 18 points from the mean yields these scores: 53 and 17.

Example 2

If the mean = 35 and the standard deviation 6, then approximately:

68% of the cases lie between 29 and 41;
95% of the cases lie between 23 and 47; and
99% of the cases lie between 17 and 53.
You can see that almost all cases (99%) in a normal distribution lie within 3 standard deviations of the mean. Thus, for practical purposes we can say that a normal distribution has only six standard deviations - three above the mean and three below the mean.

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Why is the mean the best measure of central tendency for a normal distribution?

What's the best measure of central tendency to use? The mean is the most frequently used measure of central tendency because it uses all values in the data set to give you an average. For data from skewed distributions, the median is better than the mean because it isn't influenced by extremely large values.

What is the best measure of central tendency and why?

Mean is generally considered the best measure of central tendency and the most frequently used one. However, there are some situations where the other measures of central tendency are preferred. There are few extreme scores in the distribution.

What is the best measure of central tendency for a normal distribution that is on the interval or ratio level?

But if the variable is interval/ratio, you'll need to determine if the distribution is symmetrical or skewed. If the distribution is symmetrical, the mean is the best measure of central tendency. If the distribution is skewed either positively or negatively, the median is more accurate.

What is one advantage to the use of the mean as a measure of central tendency?

However, in this situation, the mean is widely preferred as the best measure of central tendency because it is the measure that includes all the values in the data set for its calculation, and any change in any of the scores will affect the value of the mean.

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