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Warm Up

Warm Up. What is a scatterplot? How do I create one? What does it tell me? What 3 things do we discuss when analyzing a scatterplot?. Want a Quicker Way?. Stat Edit L1: Explanatory/independent/x L2: Response/dependent/y 2 nd  StatPlot Plot1 On1 st type Xlist : L1 Ylist : L2

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Warm Up

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  1. Warm Up What is a scatterplot? How do I create one? What does it tell me? What 3 things do we discuss when analyzing a scatterplot?

  2. Want a Quicker Way? • StatEdit • L1: Explanatory/independent/x • L2: Response/dependent/y • 2ndStatPlotPlot1 • On1st type • Xlist: L1 • Ylist: L2 • Zoom9:ZoomStat

  3. Homework Review Scatterplot Worksheet

  4. Response vs. Explanatory In many studies more than one variable is recorded per case or individual. It is often the purpose of the study to determine if and/or how one or more variables affect another. Response Variable—A variable you would be interested in predicting. A result. Often called a dependent variable. Plotted on the y-axis. Explanatory Variable—Any variable that explains the response variable. A cause. Often called an independent variable. Plotted on the x-axis.

  5. Examples Determine which variable is the explanatory variable and which is the response variable. In cases with no relationship write none. Inches of rain in the growing season and the yield of corn in bushels per acre Amount of snow in the Colorado mountains and the volume of water in area rivers Percent of students taking SAT in a state and mean SAT score for that state Weight and gas mileage of a car

  6. Chapter 4 Overview Chapter 4 presents basic data analysis for relationships between two quantitative variables. The most common statistical tools discussed: scatterplots correlation least-squares regression

  7. Today’s Essential Question: What does correlation tell me? How do I find it? S-ID. 8: Compute (using technology) and interpret the correlation coefficient of a linear fit.

  8. Think/Pair/Share • Look at Taller or Shorter data. • Describe the strength of the relationship.

  9. Correlation • Correlation describes the direction and strength of a straight-line relationship between 2 quantitative variables. • The value is called the correlation coefficient. • The symbol is r. • Formula on pg. 158

  10. Correlation Cont’d. • Values range from -1 to 1 • 1 is perfect positive • -1 is perfect negative • 0 means no LINEAR relationship • Strong: r > .8 • Medium: .5 < r < .8 • Weak: r < .5

  11. More Correlation • Pictures on pg. 161 • Cartoon on pg. 160 • Bold items on pg. 160-161 • Pg. 163 # 4.16

  12. Game Time! • http://www.stat.uiuc.edu/courses/stat100/cuwu/Games.html

  13. Today’s Essential Question: What does correlation tell me? How do I find it?

  14. Correlation on the Calc • StatEdit • Enter explanatory variable (x) in L1. • Enter response variable (y) in L2. • 2ndCatalog • DiagnosticOn • StatCalc4:LinReg

  15. Let’s Do This • Find the correlation coefficient of height data. • What does this tell us?

  16. How to Save a Life Create scatterplot on calc. Describe strength. Find the correlation coefficient. What does this tell us?

  17. Tying the Knot • Response variable: • Explanatory variable: • Create scatterplot on calc • Describe strength • Estimate correlation coefficient • Find correlation coefficient

  18. Today’s Essential Question: What does correlation tell me? How do I find it?

  19. Homework • pg. 163 # 4.17, 4.18 • Pg. 164 # 1-6

  20. Take 5 • Draw a quick sketch of a strong, positive correlation. • Draw a quick sketch of a weak, negative correlation. • What was your favorite part of the lesson? • What was your least favorite part of the lesson? • Write one question you have about today’s lesson.

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