Linear Best Fit Models Learn to identify patterns in scatter plots, and informally fit and use a linear model to solve problems and make predictions as.

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Presentation transcript:

Linear Best Fit Models Learn to identify patterns in scatter plots, and informally fit and use a linear model to solve problems and make predictions as appropriate.

Linear Best Fit Models Vocabulary clustering

Linear Best Fit Models When data points in a scatter plot are grouped more in one part of the graph than another, it is called clustering. Clustering helps identify possible relationships between data.

Linear Best Fit Models Be sure to consider outliers when making predictions or drawing conclusions from data. One outlier can greatly change some statistical measures. Helpful Hint

Linear Best Fit Models A study is conducted to measure the effect of fatigue on texting speed. Additional Example 1: Observe the Pattern A. Describe the pattern. B. Identify any clustering. C. Identify any possible outliers. The scatter plot appears to have a linear pattern. There appears to be clustering of the data points at x = 10. There appears to be an outlier data point at x = 35.

Linear Best Fit Models The sales of fruit bars are shown in the scatter plot. Check It Out: Example 1 A. Describe the pattern. B. Identify any clustering. C. Identify any possible outliers. The scatter plot appears to have a linear pattern. There appears to be clustering of the data points at x = There appears to be an outlier data point at x = 1.

Linear Best Fit Models Compare the given scatter plots of data and their lines of best fit. Tell which model better fits the data. Explain your answer. Additional Example 2: Assessing the Line of Best Fit The points in Graph A are closer to the line of best fit than in Graph B. The points are closer and more evenly divided both above and below the line of best fit. Both scatter plots show data sets that have a positive correlation.

Linear Best Fit Models Compare the given scatter plots of data and their lines of best fit. Tell which model better fits the data. Explain your answer. Check It Out: Example 2 The points in Graph A are closer to the line of best fit than in Graph B. Graph A has a negative correlation and Graph B has a positive correlation.

Linear Best Fit Models Estimate an equation for the line of best fit, and tell what the slope and y-intercept represent in terms of the data it models. Additional Example 3: Economics Application Players gain about 20 lb/yr and begin at about 130 lb. y = 20x + 130

Linear Best Fit Models Estimate an equation for the line of best fit, and tell what the slope and y-intercept represent in terms of the data it models. Check It Out: Example 3 For every hour a student study, their grade increase about 5%. Without studying, most students would earn a 70%. y =5x + 70