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2-2 Making Predictions

Pages 60-63. 2-2 Making Predictions. Indicators  D1- Read, create, and interpret graphs D2- Analyze how decisions about graphing affect the graphical representation.

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2-2 Making Predictions

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  1. Pages 60-63 2-2 Making Predictions Indicators D1- Read, create, and interpret graphs D2- Analyze how decisions about graphing affect the graphical representation

  2. Line graphs can be used to make predictions. Find the trend in the data and follow it out to a specific time. A trend can be linear (make a straight line) or non-linear (make a curved line) A linear trend shows constant change. A non-linear trend shows irregular or varying change.

  3. Use a Line Graph to Predict Enrique is writing a 600-word paper for class. The table shows the time it has taken Enrique to type the paper so far. Make a line graph and predict the total time it will take him to type his paper. The data values go from 0-700. You want to predict the amount of time it will take him to type 600 words. { Continue the graph with a dotted line in the same direction until you reach the horizontal position of 600 words. Graph the data and connect the points.

  4. Scatter Plots sometimes called scattergrams • A scatter plot displays two sets of data on the same graph. • Like line graphs, scatter plots are useful in making predictions because they show trends in data. • If the points in a scatter plot come close to making a straight line, the 2 sets of data are related.

  5. Use a Scatter plot to Predict The scatter plot shows the number of days that San Bernadino, California, failed to meet air quality standards from 1990 to 1998. Use it to predict the number of days of bad air quality in 2004. The line goes through the middle of the data. The vertical axis represents the # of Days SB, Cal. Failed to meet air quality standards By looking at the pattern in the scatter plot, we can predict that the number of days of bad air quality in 2004 was around 48 days. The horizontal axis represents the year

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