Which answer best describes a standard deviation? Read all answers and then choose the answer that is most complete and accurate. The standard deviation is the square root of the corresponding variance. The standard deviation is the average amount that scores in a distribution deviate from the mean of that distribution. The standard deviation is a measure of variability. All of the answers above correctly describe the standard deviation. None of the answers above correctly describe the standard deviation.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
Which answer best describes a standard deviation?
Read all answers and then choose the answer that is most complete and accurate.
The standard deviation is the square root of the corresponding variance.
The standard deviation is the average amount that scores in a distribution deviate from the
The standard deviation is a measure of variability.
All of the answers above correctly describe the standard deviation.
None of the answers above correctly describe the standard deviation.
I think the best answer is "The standard deviation is the average amount that scores in a distribution deviate from the mean of that distribution".
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