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Instructions

Instructions. for. creating Scatterplots. You will need to repeatedly click your mouse or space bar to progress through the information. . Created by Del Siegle For EPSY 341. 74. 72. 70. Height. 68. 66. 64. 62. 60. 58. 4. 6. 8. 10. 12. 14. Foot Length.

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Instructions

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  1. Instructions for creating Scatterplots You will need to repeatedly click your mouse or space bar to progress through the information. Created by Del Siegle For EPSY 341

  2. 74 72 70 Height 68 66 64 62 60 58 4 6 8 10 12 14 Foot Length Suppose we wished to graph the relationship between foot length and height of 20 subjects. In order to create the graph, which is called a scatterplot or scattergram, we need the foot length and height for each of our subjects.

  3. 1. Find 12 inches on the x-axis. 2. Find 70 inches on the y-axis. 3. Locate the intersection of 12 and 70. Assume our first subject had a 12 inch foot and was 70 inches tall. 4. Place a dot at the intersection of 12 and 70. Height Foot Length Your next mouse click will display a new screen.

  4. 5. Find 8 inches on the x-axis. 6. Find 62 inches on the y-axis. Assume that our second subject had an 8 inch foot and was 62 inches tall. 7. Locate the intersection of 8 and 62. 8. Place a dot at the intersection of 8 and 62. 9. Continue to plot points for each pair of scores. Your next mouse click will display a new screen.

  5. Notice how the scores cluster to form a pattern. The more closely they cluster to a line that is drawn through them, the stronger the linear relationship between the two variables is (in this case foot length and height). Your next mouse click will display a new screen.

  6. If the points on the scatterplot have an upward movement from left to right, we say the relationship between the variables is positive. If the points on the scatterplot have a downward movement from left to right, we say the relationship between the variables is negative. Your next mouse click will display a new screen.

  7. A positive relationship means that high scores on one variable are associated with high scores on the other variable are associated with low scores on the other variable. It also indicates that low scores on one variable Your next mouse click will display a new screen.

  8. A negative relationship means that high scores on one variable are associated with low scores on the other variable. are associated with high scores on the other variable. It also indicates that low scores on one variable Your next mouse click will display a new screen.

  9. Not only do relationships have direction (positive and negative), they also have strength (from 0.00 to 1.00 and from 0.00 to –1.00). The more closely the points cluster toward a straight line, the stronger the relationship is. r = 0.00 r = 0.10 r = 0.20 r = 0.30 r = 0.40 r = 0.50 r = 0.60 r = 0.70 r = 0.80 r = 0.90 r = 1.00 Your next mouse click will display a new screen.

  10. A set of scores with r= –0.60 has the same strength as a set of scores with r= 0.60 because both sets cluster similarly. Your next mouse click will display a new screen.

  11. NO Pearson r Linear Relationship Curvilinear Relationship For this unit, we use Pearson’s r. This statistical procedure can only be used when BOTH variables are measured on a continuous scale (see your Instructor notes) and you wish to measure a linear relationship. Your next mouse click will display a new screen.

  12. Please consult the Instructor Notes and your textbook for additional information on Correlational Research.

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