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Lesson 1: Measuring center in quantitative data. Statistics intro: Mean, median, & mode. Mean, median, & mode example. Mean, median, and mode. Calculating the mean. Calculating the mean. Calculating the median. Choosing the "best" measure of center.
Introduction to mean, median, and mode in statistics with examples and explanations.
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Review of box plots, including how to create and interpret them.
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.
A box and whisker plot is a handy tool to understand the age distribution of students at a party. It helps us identify the minimum, maximum, median, and quartiles of the data. However, it doesn't provide specific details like the exact number of students at certain ages.
"Median" is the middle number in a list of numbers that are ordered from least to greatest. In our example set of numbers, the median would also be 3. "Mode" is the most frequent number.
Range, variance, and standard deviation all measure the spread or variability of a data set in different ways. The range is easy to calculate—it's the difference between the largest and smallest data points in a set. Standard deviation is the square root of the variance. Standard deviation is a measure of how spread out the data is from its mean.
The IQR describes the middle 50% of values when ordered from lowest to highest. To find the interquartile range (IQR), first find the median (middle value) of the lower and upper half of the data. These values are quartile 1 (Q1) and quartile 3 (Q3). The IQR is the difference between Q3 and Q1.
Box and whisker plots seek to explain data by showing a spread of all the data points in a sample. The "whiskers" are the two opposite ends of the data. This video is more fun than a handful of catnip.