Descriptive Statistics Summary

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These flashcards cover key concepts from descriptive statistics, including measures of center, variability, and graphical data representation.

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15 Terms

1
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What does 'N' represent in statistics?

'N' represents the population size.

2
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What does 'n' represent in statistics?

'n' represents the sample size.

3
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How do you calculate the mean of a data set?

The mean is calculated by summing all the values and dividing by the number of values, expressed as μ = Σxi / N.

4
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What is the median?

The median is the middle value in a sorted data set.

5
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What is a robust estimator?

A robust estimator is not drastically influenced by outliers.

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What does a symmetric distribution imply about the mean and median?

In a symmetric distribution, the mean and median are the same.

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What happens to the mean and median in a right-skewed distribution?

In a right-skewed distribution, the mean is greater than the median.

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What is the formula for variance in a population?

Variance in a population is calculated as σ² = Σ (X - μ)² / N.

9
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What is the Empirical Rule?

The Empirical Rule states that for a normal distribution, approximately 68% of values fall within one standard deviation, 95% within two, and 99.7% within three standard deviations of the mean.

10
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What are quartiles?

Quartiles are values that divide a data set into four equal parts.

11
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What is the Interquartile Range (IQR)?

The IQR is the difference between the first quartile (Q1) and the third quartile (Q3).

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How is a boxplot structured?

A boxplot displays the distribution of a data set using five summary statistics: minimum, first quartile, median, third quartile, and maximum.

13
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What do Z-scores indicate?

Z-scores indicate how many standard deviations a data point is from the mean.

14
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What should you use if outliers are present in the data set?

If outliers are present, it's better to use the median instead of the mean.

15
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What is the purpose of comparing relative variability?

Comparing relative variability allows assessment of variability across different populations or data sets.