Analyzing Associations in Data

This lesson teaches how to use observed data to predict unobserved data by interpreting scatter plots and identifying the line of best fit. It explains the importance of minimizing the influence of outliers and demonstrates how to use linear models to make predictions. The lesson covers both positive and negative associations in data, using examples like homework assignments and test scores, as well as television watching and test scores. By the end, students will understand how to draw and use the line of best fit to predict unobserved values.

What is the primary purpose of using a line of best fit in scatter plots?

• To eliminate outliers from the data set

• To find the exact values of all data points

• To predict unobserved data based on observed data

• To make the graph look more appealing

How can you determine the value of y for a given x using a graph?

• By drawing a vertical line from x to the x-axis

• By finding x on the x-axis and locating the corresponding y-value on the line

• By calculating the average of all y-values

• By using the midpoint of the graph

What is a common mistake when identifying the line of best fit?

• Drawing the line through the origin

• Ignoring the slope of the line

• Allowing outliers to heavily influence the line

• Using only a few data points to draw the line

Why should outliers not have a large influence on the line of best fit?

• They make the graph more complex

• They are anomalies and do not represent the general trend

• They represent typical data behavior

• They are always incorrect data points

What is the relationship between homework assignments completed and test scores, as observed in the scatter plot?

• Inverse association

• Positive association

• No association

• Negative association

What is the predicted test score for a student who completed four homework assignments?

• 70

• 50

• 60

• 40

What type of association is observed between hours of TV watched and test scores?

• Direct association

• No association

• Negative association

• Positive association

How can the line of best fit be used to predict a test score for a student watching 2.5 hours of TV?

• By finding 2.5 on the y-axis and drawing a horizontal line

• By finding 2.5 on the x-axis and locating the corresponding y-value on the line

• By averaging all test scores

• By using the midpoint of the line

What is the expected test score for a student who watches 2.5 hours of TV?

• 72

• 68

• 70

• 74

What is another name for the line of best fit?

• Linear model

• Scatter line

• Graph line

• Data trend line