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Understanding Scatter Plots for Data Analysis

liberty-goodman avatar
liberty-goodman
16 diapositives · 281 Views · Nov 19, 2014

Learn to interpret scatter plots, relationships between data sets, and make predictions using lines of best fit. Explore positive, negative, and constant correlations through real-world examples.

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Understanding Scatter Plots for Data Analysis
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  1. Scatter Plots Standard: 806.5.3 Generalize the relationship between two sets of data using scatterplots and lines of best fit.

  2. Scatter Plot • A scatter plot is a graph of a collection of ordered pairs (x,y) to show a relationship between two sets of data. • A correlation describes the relationship between two sets of data. • A line of best fit is a straight line that comes closest to the points on a scatter plot. You can use a line of best fit to help you make predictions from the data.

  3. Positive Correlation • If the x-coordinates and the y-coordinates both increase, then it is POSITIVE CORRELATION. • This means that both are going up, and they are related.

  4. Positive Correlation • If you look at the age of a child and the child’s height, you will find that as the child gets older, the child gets taller. Because both are going up, it is positive correlation.

  5. Negative Correlation • If the x-coordinates and the y-coordinates have one increasing and one decreasing, then it is NEGATIVE CORRELATION. • This means that 1 is going up and 1 is going down, making a downhill graph. This means the two are related as opposites.

  6. Negative Correlation • If you look at the age of your family’s car and its value, you will find as the car gets older, the car is worth less. This is negative correlation.

  7. No Correlation • If there seems to be no pattern, and the points looked scattered, then it is no correlation. • This means the two are not related.

  8. No Correlation • If you look at the size shoe a baseball player wears, and their batting average, you will find that the shoe size does not make the player better or worse, then are not related.

  9. Constant Correlation The relationship is linear, but is neither positive, nor negative. Therefore, there is no correlation between the two.

  10. Scatterplots Which scatterplots below show a linear trend? a) c) e) Negative Correlation Positive Correlation b) d) f) Constant Correlation

  11. Objective - To plot data points in the coordinate plane and interpret scatter plots. y Sport Utility Vehicles (SUVs) Sales in U.S. 5 4 3 2 1 Year Sales (in Millions) 1991 0.9 1992 1.1 Vehicle Sales (Millions) 1993 1.4 1994 1.6 1995 1.7 1996 2.1 1997 2.4 1991 1993 1995 1997 1999 1992 1994 1996 1998 2000 x 1998 2.7 1999 3.2 Year

  12. Scatterplot - a coordinate graph of data points. y Trend appears linear. 5 4 3 2 1 Trend is increasing. Vehicle Sales (Millions) Positive correlation. Predict the sales in 2001. 1991 1993 1995 1997 1999 1992 1994 1996 1998 2000 x Year

  13. Plot the data on the graph such that homework time is on the y-axis and TV time is on the x-axis.. Time Spent Watching TV Time Spent on Homework Student Sam 30 min. 180 min. Jon 45 min. 150 min. Lara 120 min. 90 min. Darren 240 min. 30 min. Megan 90 min. 90 min. Pia 150 min. 90 min. Crystal 180 min. 90 min.

  14. Plot the data on the graph such that homework time is on the y-axis and TV time is on the x-axis. TV Homework 240 210 180 150 120 90 60 30 30 min. 180 min. 45 min. 150 min. Time on Homework 120 min. 90 min. 240 min. 30 min. 90 min. 120 min. 150 min. 120 min. 180 min. 90 min. 30 90 150 210 60 120 180 240 Time Watching TV

  15. Describe the relationship between time spent on homework and time spent watching TV. Trend appears linear. 240 210 180 150 120 90 60 30 Trend is decreasing. Time on Homework 30 90 150 210 60 120 180 240 Negative correlation. Time Watching TV

  16. Now, let’s do pages 506-507 #1-11 for homework!