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Warm-Up Math Social Studies P.E. Women 16 6 8 Men 2 10 8 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes Social Studies? 3. What is the probability that you select a person who likes Math? 8/50 = .16 10/20 = .50 18/50 = .36

1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

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Page 1: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Warm-Up  Math Social

Studies P.E.

Women 16 6 8Men 2 10 8

1. What is the probability that a randomly selected person is a woman who likes P.E.?

2. Given that you select a man, what is the probability that he likes Social Studies?

3. What is the probability that you select a person who likes Math?

8/50 = .16

10/20 = .50

18/50 = .36

Page 2: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Skills CheckCorrelation, Linear Regression, & Exponential

Regression

Page 3: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Residuals

From the Carnegie Foundation math.mtsac.edu/statway/lesson_3.3.1_version1.5A

Page 4: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Residuals

Residual is another word for ERROR

Page 5: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Residuals

To find the residual you take the ACTUAL data and SUBTRACT the PREDICTED data.

Page 6: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Analyzing Residuals

Determines the effectiveness of the regression model

Page 7: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Residual Plots

A residual plot is another type of

SCATTERPLOTthat shows the

relationship of the residual to the x value.

Page 8: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Residual Plots Determine

If it the regression model is appropriate, then the residual plot will have a RANDOM scatter.

If the residual plot creates a pattern then the regression model is NOT A GOOD FIT. Pattern = Problem

Page 9: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Example of Random Scatter

Page 10: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

ExamplesDetermine, just by visual inspection, if

the linear model is appropriate or inappropriate.

Page 11: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Linear model appropriate or inappropriate?

Page 12: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

The only way to know is to see the residual plot.

1. Does their appear to be a pattern in the residual plot?Yes, quadratic.

2. Does this support your original guess?

You must now see that a linear model does NOT fit this data.

Page 13: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Linear model appropriate or inappropriate?

Page 14: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

The only way to know is to see the residual plot.

1. Does their appear to be a pattern in the residual plot?Yes, it fans out as

x increases.2. Does this support your original guess?

You must now see that a linear model does NOT fit this data.

Page 15: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Linear model appropriate or inappropriate?

Page 16: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

The only way to know is to see the residual plot.

1. Does their appear to be a pattern in the residual plot?Yes, it looks quadratic.

2. Does this support your original guess?

This was very tricky. The scale was very small. You must now see that a linear model does NOT fit this data.

Page 17: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Linear model appropriate or inappropriate?

Page 18: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

The only way to know is to see the residual plot.

1. Does their appear to be a pattern in the residual plot?Yes, it seems decrease as x increases.2. Does this

support your original guess?This was tricky. You must now see that a linear model does NOT fit this data.

Page 19: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Example: Calculate Residual

Total Time (minutes)

Total Distance (miles)

Predicted Total Distance

Residuals(observed – predicted)

32 51 54.4 -3.4

19 30 31.9

28 47

36 56

17 27

23 35

41 65

22 41

37 73

28 54

1.73 0.96y x

Page 20: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Example: Calculate Residual

Total Time (minutes)

Total Distance (miles)

Predicted Total Distance

Residuals(observed – predicted)

32 51 54.4 -3.4

19 30 31.9

28 47 47.536 56 61.317 27 28.523 35 38.841 65 70.022 41 37.137 73 63.128 54 47.5

1.73 0.96y x

Page 21: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Example: Calculate Residual

Total Time (minutes)

Total Distance (miles)

Predicted Total Distance

Residuals(observed – predicted)

32 51 54.4 -3.4

19 30 31.9 -1.928 47 47.5 -0.536 56 61.3 -5.317 27 28.5 -1.523 35 38.8 -3.841 65 70.0 -522 41 37.1 3.937 73 63.1 9.928 54 47.5 6.5

1.73 0.96y x

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Good fit or not?

Total Time

Resi

dual

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Good fit or not?

15 20 25 30 35 40 45

-8

-6

-4

-2

0

2

4

6

8

10

12

Total Time

Resi

dual

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Classwork

Residuals Task – Carnival

Page 25: 1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes

Homework

Residuals CW worksheet