3 Stats - Variance

Why is the average only "half the story" in data analysis?

• Because it excludes information about central tendency.

• Because it considers only a single value in the dataset.

• Because it does not include information about variability.

• Because it includes outliers as part of its calculation.

What are the two common measures of variability?

• Mean and standard deviation.

• Range and variance.

• Range and standard deviation.

• Interquartile range and variance.

How is the range calculated?

• By subtracting the mean from the highest score in the dataset.

• By adding the lowest and highest scores together.

• By subtracting the lowest score from the highest score in the dataset.

• By dividing the sum of scores by the number of observations.

What are the limitations of the range?

• It accounts for all scores but ignores outliers.

• It considers only the lowest and highest scores, is vulnerable to outliers, and can vary with sample size.

• It fails to capture the distribution curve.

• It underestimates the standard deviation.

What is the interquartile range?

• The difference between the mean and the median.

• The range of all scores after removing outliers.

• The range of the middle 50% of scores after excluding the lowest and highest quartiles.

• The range of values that appear most frequently.

How is the interquartile range calculated?

• Rank scores, exclude the highest and lowest scores, and subtract the smallest from the largest.

• Rank scores, exclude the lowest 25% and highest 25%, then subtract the lowest from the highest of the remaining scores.

• Divide the total range into four equal parts and calculate the mean of each.

• Subtract the mean from the median.

What does variance measure?

• The range of scores in a dataset.

• How spread out data are around the mean.

• The median distance of scores from the mean.

• The steepness of the data distribution.

Why are deviations squared in variance calculations?

• To highlight the outliers.

• To make the calculations more complex.

• To avoid negative values canceling out positive values.

• To ensure the variance is higher than the range.

How is variance calculated?

• Square each score’s deviation from the mean, sum them, and divide by the total number of scores.

• Subtract the smallest score from the largest and square the result.

• Find the average deviation of scores from the median.

• Take the standard deviation and multiply by itself.

What is the standard deviation (SD)?

• A measure of the steepness of the data distribution.

• The square root of variance, representing the average amount by which scores deviate from the mean.

• The range of the middle 50% of the dataset.

• The median distance of scores from the mean.