 # 1.6 Scatter Plots and Lines of Best Fit

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1.6 Scatter Plots and Lines of Best Fit
Objectives: Interpret data in a scatter plot. Find a line of best fit on a scatter plot by inspection. Standard Addressed: C: Fit a line to a scatter plot of two quantities and describe any correlation of the variables.

Scatter plots provide a picture of the relationship between two sets of data.
Scatter plots and lines of best fit can be used to predict relationships and future occurrences. A scatter plot shows how 2 variables relate to each other by showing how closely the data points cluster to a line. Scatter plots provide a convenient way to determine whether a relationship exists between 2 variables. The relationship is called a correlation. A positive correlation occurs when both variables increase. A negative correlation occurs when one variable increases and the other variable decreases.

Ex. 1

Ex. 2 Think of 2 examples of related data
Ex. 2 Think of 2 examples of related data. Describe the kind of correlation you expect from the data and why. Age color vs. Hair  No Correlation Age Car vs. Value \$  Negative Correlation Study vs. Grade  Positive Correlation

Finding Lines of Best Fit
Scatter plots can be used to show trends in data. When the points in a scatter plot are represented by a trend line or line of best fit, you can study the line to see how the data behave. You may have a basis to predict what the data might be for values not given.

Ex. 3 Calculator and Years!! Y = 15.9x -371.8
1950 1955 1960 1965 1970 1975 1980 1985 1990 # of storms 200 600 620 900 650 920 880 700 1180 Y = 15.9x R = .80 Moderate Positive Correlation

Ex. 4 Y = 5x – 430.6 R = .997 Strong Positive Correlation

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