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Chapter 3 Correlation. Suppose we found the age and weight of a sample of 10 adults. Create a scatterplot of the data below. Is there any relationship.

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Presentation on theme: "Chapter 3 Correlation. Suppose we found the age and weight of a sample of 10 adults. Create a scatterplot of the data below. Is there any relationship."— Presentation transcript:

1 Chapter 3 Correlation

2 Suppose we found the age and weight of a sample of 10 adults. Create a scatterplot of the data below. Is there any relationship between the age and weight of these adults? Age 24304128504649352039 Wt256124320185158129103196110130

3 Suppose we found the height and weight of a sample of 10 adults. Create a scatterplot of the data below. Is there any relationship between the height and weight of these adults? Ht74657772686062736164 Wt256124320185158129103196110130 Is it positive or negative? Weak or strong?

4 The closer the points in a scatterplot are to a straight line - the stronger the relationship. The farther away from a straight line – the weaker the relationship

5 Identify as having a positive association, a negative association, or no association. 1. Heights of mothers & heights of their adult daughters + 2. Age of a car in years and its current value 3.Weight of a person and calories consumed 4.Height of a person and the person’s birth month 5.Number of hours spent in safety training and the number of accidents that occur - + NO -

6 Correlation Coefficient (r)- quantitative A quantitative assessment of the strength & direction of the linear relationship between bivariate, quantitative data Pearson’s sample correlation is used most parameter - rho) statistic - r

7 Calculate r. Interpret r in context. Speed Limit (mph) 555045403020 Avg. # of accidents (weekly) 28252117116 There is a strong, positive, linear relationship between speed limit and average number of accidents per week.

8 Moderate Correlation Strong correlation Properties of r (correlation coefficient) legitimate values of r is [-1,1] No Correlation Weak correlation

9 value of r does not depend on the unit of measurement for either variablevalue of r does not depend on the unit of measurement for either variable x (in mm) 121521322619 y 4710149812 Find r. Change to cm & find r. The correlations are the same.

10 value of r does not depend on which of the two variables is labeled xvalue of r does not depend on which of the two variables is labeled x x 121521322619 y4710149812 Switch x & y & find r. The correlations are the same.

11 value of r is non-resistantvalue of r is non-resistant x 12152132261924 y4710149822 Find r. Outliers affect the correlation coefficient

12 value of r is a measure of the extent to which x & y are linearly relatedvalue of r is a measure of the extent to which x & y are linearly related A value of r close to zero does not rule out any strong relationship between x and y. definite r = 0, but has a definite relationship!

13 Guessing Correlations http://istics.net/stat/Correlations/

14 Correlation vs. Causation Number of Beers vs. Blood Alcohol Content Number of Ice Creams sold vs. Shark Attacks

15 Correlation does not imply causation

16 Homework 3.1-4, 5, 7, 13- 14 omit part b


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