scatterplots chapter 7 definition and components describing correlation correlation vs. association

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Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

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Page 1: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Scatterplots

Chapter 7Definition and components

Describing

Correlation

Correlation vs. Association

Page 2: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

I. Scatterplots

• A graph that plots the relationship between two quantitative variables.

• Used to see if a relationship exists between the two variables.

Page 3: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

I. Scatterplots

• Explanatory Variable – x- value– Predictor– Input– Independent

• Response Variable– Y-value– Output– Dependent

Page 4: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

II. Creating a Scatterplot• Enter all x-variables in

L1, and all y-variables in L2.

• Turn on Statplot and go to

• Use ZoomStat to obtain graph.

• Use Trace to get specific points

• Scale and label axes.

• I:\Math Department\TI-84-Emulator\Wabbitemu.exe

Page 5: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Does fast driving waste fuel?

Speed (km/h)

Fuel used (L/100km)

Speed (km/h)

Fuel used (L/100km)

10 21.00 90 7.57

20 13.00 100 8.27

30 10.00 110 9.03

40 8.00 120 9.87

50 7.00 130 10.79

60 5.90 140 11.77

70 6.30 150 12.83

80 6.95

Page 6: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

• Make scatterplot in calculator.• Transfer information onto your paper, make

sure to add labels and scale for x & y-axis.

Page 7: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Now try on your own.

Either by hand or in the calculator, create a scatterplot of the data on Age

at First Word vs. Gesell Score.

A score of 100 is considered to be average.

Page 8: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

III. Describing Scatterplots

• Direction– Positive– Negative

• Form– Linear– Exp. Curve– Quadratic curve– none

Page 9: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

III. Describing Scatterplots

• Strength– Strong– Weak

• Unusual Features– Outliers– Change in form or

strength.

Page 10: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Example 2

• Describe the following Scatterplots (direction, form, strength, unusual features)

Page 11: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Describe the scatterplot you made in the fuel efficiency example.

Page 12: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Now try on your own.

Now describe the relationship between Age at First Word vs. Gesell

Score on your worksheet.

Page 13: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

IV. Correlation coefficient

• Measures the strength of the linear association between two quantitative variables.

• In order to use this number, the data must meet the following conditions.– Quantitative Variables Condition– Straight Enough Condition– Outlier Condition (calculate with & without

outlier)

Page 14: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association
Page 15: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

IV. Correlation Coefficient• To calculate correlation:

– Enter data into L1 & L2

– Go to Catalog (2nd ,0) and choose DiagnosticsON.

– STAT, CALC, LinReg(ax+b).– The correlation number is the last entry r=

• Calculate to correlation coefficient of your speed vs fuel example.

• Is it appropriate to use correlation for this example? Why or Why not?

Page 16: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

IV. Correlation Coefficient• Correlation gives strength and direction.

– Closer to -1 indicates perfect Negative linear association.

– Closer to +1 indicates perfect Positive linear association.

– Closer to 0 indicates NO Linear association.

Page 17: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Now try on your own.

Calculate the correlation coefficient for the relationship between Age at First Word vs. Gesell Score on your

worksheet.

Then answer question # 4 on the worksheet.

Page 18: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Now try on your own.

Calculate the correlation coefficient for the relationship between Age at First Word vs. Gesell Score on your

worksheet.

Page 19: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Pick up SEC Football Worksheet.

This is due at the end of the class.

Page 20: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

What do you think the correlation coefficients are for the

following?

Page 21: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

IV. Correlation Coefficient• Has no units, based on z-scores• Are unaffected by changes in center or

scale. • Can be greatly affected by outliers.

Page 22: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

V. Correlation vs Association

Association• Indicates that there is a

relationship between the two variables (any form).

Correlation• Measures the strength

of a LINEAR association.

Page 23: Scatterplots Chapter 7 Definition and components Describing Correlation Correlation vs. Association

Examples

• Sketch what you think the scatterplot would look like, then describe the association.– Drug dose vs. degree of pain relief.– Calories consumed and weight loss.– Hours of sleep and score on a test.– Shoe size and grade point average– Age of car and money spent on repairs