Choosing the Best Measure of Center and Variability

This lesson teaches how to choose the best measure of center and variability by comparing each measure to data in real-world contexts. It covers calculating range, IQR, and identifying outliers. Through examples like rainfall data, basketball scores, reading time, and video game spending, the lesson demonstrates when to use mean, median, or mode. It emphasizes the importance of understanding data variability and choosing appropriate measures for accurate representation.

What is the range of a dataset?

• The middle value of the dataset

• The average of all data points

• The most frequently occurring value

• The difference between the maximum and minimum values

Why is the median often a better measure of center than the mean in the presence of outliers?

• The median is not affected by outliers

• The median is always higher than the mean

• The median is easier to calculate

• The mean is always lower than the median

In the context of basketball scores, why might the mean be a better measure of center than the median?

• The mean is less affected by random data

• The median is always higher than the mean

• The mode is more accurate than the mean

• The mean is always lower than the median

What is the IQR and why is it useful?

• The difference between the highest and lowest values

• The range of the middle 50% of the data

• The most frequently occurring value

• The average of all data points

Why is the mean a better choice for Christy's reading time data?

• The data is not varied

• The mode is more accurate

• The data is highly varied

• The median is always higher

In Jacob's video game spending, why might the mean better represent the data than the median?

• The mean accounts for all prices

• The mean is always lower

• The median is always higher

• The mode is more accurate

What does the IQR represent in a dataset?

• The range of the middle 50% of the data

• The difference between the highest and lowest values

• The most frequently occurring value

• The average of all data points