The common measures of variability for quantitative or continuous data are:

1. Variance and standard deviation: Variance is a measure of how spread out a data set is. It is calculated as the average squared deviation of each number from the mean of a data set. Standard deviation is the square root of the variance and provides a measure of the spread of the data around the mean.

2. Skewness and kurtosis: Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable.

3. Quartiles and IQR: Quartiles divide a rank-ordered data set into four equal parts. The values that divide each part are called the first, second, and third quartiles; and they are den

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The common measures of variability for quantitative or continuous data are:

1. Variance and standard deviation: Variance is a measure of how spread out a data set is. It is calculated as the average squared deviation of each number from the mean of a data set. Standard deviation is the square root of the variance and provides a measure of the spread of the data around the mean.

2. Skewness and kurtosis: Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable.

3. Quartiles and IQR: Quartiles divide a rank-ordered data set into four equal parts. The values that divide each part are called the first, second, and third quartiles; and they are den

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The common measures of variability for quantitative or continuous data are:

1. Variance and standard deviation: Variance is a measure of how spread out a data set is. It is calculated as the average squared deviation of each number from the mean of a data set. Standard deviation is the square root of the variance and provides a measure of the spread of the data around the mean.

2. Skewness and kurtosis: Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable.

3. Quartiles and IQR: Quartiles divide a rank-ordered data set into four equal parts. The values that divide each part are called the first, second, and third quartiles; and they are den

Which of the following are common measures of variability for quantitative or continuous data? Select all that apply.Choose at least one answer. Mean and mode Variance and standard deviation Skewness and kurtosis Quartiles and IQR Median and range

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