Interpreting Scatterplots and Line of Best Fit

This lesson teaches how to interpret scatter plots by understanding the association of a line of best fit. It covers the concepts of positive and negative associations, using real-world examples like basketball statistics and jeans sizes. The video explains how to read graphs and determine associations based on data trends, emphasizing the importance of understanding both directions of data movement.

What is a key characteristic of a good line of best fit in a scatter plot?

• It should only pass through the highest data point.

• It should be centered between the data points.

• It should only pass through the lowest data point.

• It should be parallel to the horizontal axis.

How can you identify a positive association in a scatter plot?

• The line of best fit is horizontal.

• Both values decrease as you move from left to right.

• One value increases while the other decreases.

• Both values increase as you move from left to right.

In a scatter plot, what does it mean if one value increases while the other decreases?

• There is a negative association.

• There is a positive association.

• There is no association.

• The data is perfectly correlated.

In the basketball scatter plot example, what happens to points scored as minutes played increase?

• Points scored decrease.

• Points scored fluctuate randomly.

• Points scored increase.

• Points scored remain constant.

In the blue jeans scatter plot, what is the association between waist and length measurements?

• There is a positive association.

• There is no association.

• The association is random.

• There is a negative association.