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How do you calculate variances in a data set? - Answers

To calculate the variance of a data set, first determine the mean (average) of the data. Then, subtract the mean from each data point to find the deviation of each point, square these deviations, and sum them up. Finally, divide this total by the number of data points (for population variance) or by the number of data points minus one (for sample variance) to obtain the variance. This gives you a measure of how spread out the data points are from the mean.



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How do you calculate variances in a data set? - Answers

https://math.answers.com/math-and-arithmetic/How_do_you_calculate_variances_in_a_data_set

To calculate the variance of a data set, first determine the mean (average) of the data. Then, subtract the mean from each data point to find the deviation of each point, square these deviations, and sum them up. Finally, divide this total by the number of data points (for population variance) or by the number of data points minus one (for sample variance) to obtain the variance. This gives you a measure of how spread out the data points are from the mean.



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https://math.answers.com/math-and-arithmetic/How_do_you_calculate_variances_in_a_data_set

How do you calculate variances in a data set? - Answers

To calculate the variance of a data set, first determine the mean (average) of the data. Then, subtract the mean from each data point to find the deviation of each point, square these deviations, and sum them up. Finally, divide this total by the number of data points (for population variance) or by the number of data points minus one (for sample variance) to obtain the variance. This gives you a measure of how spread out the data points are from the mean.

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      To calculate the variance of a data set, first determine the mean (average) of the data. Then, subtract the mean from each data point to find the deviation of each point, square these deviations, and sum them up. Finally, divide this total by the number of data points (for population variance) or by the number of data points minus one (for sample variance) to obtain the variance. This gives you a measure of how spread out the data points are from the mean.

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