# Summarizing quantitative data

This course is a part of Statistics and probability, a 16-course Topic series from Khan Academy.

This unit covers common measures of center like mean and median. We'll also learn to measure spread or variability with standard deviation and interquartile range, and use these ideas to determine what data can be considered an outlier.

This course contains 8 segments:

Measuring center in quantitative data

We use measures of center like mean and median to summarize an entire set of data with just one number. Let's look at how to calculate mean and median given raw data or a data display.

More on mean and median

Once you know the basics of how to calculate the mean and median, you can start to think deeper about more advanced concepts. This tutorial covers how to find the mean and median from a data display, how new data points impact the mean and median, and how to find missing values given a mean.

Interquartile range (IQR)

Let's learn how to measure spread in a set of data using interquartile range, which is also referred to as IQR for short.

Variance and standard deviation of a population

Variance and standard deviation give us a powerful way to measure spread. Standard deviation gives us an idea of the typical distance between each data point and the mean. Let's learn how to calculate the variance and standard deviation of a population.

Variance and standard deviation of a sample

If our data came from a sample, and we want to use it to represent its larger population, we need to slightly modify our formulas for variance and standard deviation. Let's look at how to calculate variance and standard deviation based on sample data.

More on standard deviation

This collection of videos and simulations is useful if you want to develop a very deep understanding of population vs. sample standard deviation. We'll explore why we divide by n-1 when working with sample data, and look at what it means to be a biased vs. an unbiased estimator.

Box and whisker plots

Box and whisker plots show us the shape, center, spread, and even more features about a set of data. We'll learn how to construct box and whisker plots (often called box plots), and we'll also look at how to read and interpret box plots.

Let's look at how to use range and mean absolute deviation (MAD) to measure the spread or variation in a data set.

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