Lesson 7 Aim: How can we represent bivariate data graphically?
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Lesson 7 Aim: How can we represent bivariate data graphically?
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Transcript of Lesson 7 Aim: How can we represent bivariate data graphically?
Lesson 7
Aim: How can we represent bivariate data graphically?
Aim: How can we represent bivariate data graphically?
Problem of the Day
Aim: How can we represent bivariate data graphically?
Problem of the Day
Aim: How can we represent bivariate data graphically?
Guided Practice
Aim: How can we represent bivariate data graphically?
Guided Practice
Aim: How can we represent bivariate data graphically?
Guided Practice
Aim: How can we represent bivariate data graphically?
Guided Practice
Aim: How can we represent bivariate data graphically?
This is an example of a scatter plot. It shows the relationship between two variables (bivariate)
Guided Practice
Aim: How can we represent bivariate data graphically?
Guided Practice
Aim: How can we represent bivariate data graphically?
Guided Practice
Aim: How can we represent bivariate data graphically?
This is also an example of causation (if a student works more hours, he or she will make more money)
Aim: How can we represent bivariate data graphically?
This is also an example of causation (if a student works more hours, he or she will make more money)
Guided Practice
Aim: How can we represent bivariate data graphically?
Guided Practice
Correlation is not the same as causation!!
For example: There is a positive correlation between the number of televisions owned by a household and the average life expectancy of the family members.
Aim: How can we represent bivariate data graphically?
Guided Practice
Correlation is not the same as causation!!
For example: There is a positive correlation between the number of televisions owned by a household and the average life expectancy of the family members.
Owning more televisions does not really cause you to live longer. What might explain the relationship?
Aim: How can we represent bivariate data graphically?
Guided Practice
Correlation is not the same as causation!!
For example: There is a positive correlation between the number of televisions owned by a household and the average life expectancy of the family members.
Owning more televisions does not really cause you to live longer. What might explain the relationship?
Owning more televisions means you have more money, which you also have to spend on healthcare.
Aim: How can we represent bivariate data graphically?
Independent Practice
Aim: How can we represent bivariate data graphically?
Independent Practice
Aim: How can we represent bivariate data graphically?
Classwork
Homework
p. 33. Examples 1, 2; Quick Check 1, 2p. 35: ex. 1GPS p. 36: ex. 16pp. 748–749: Examples 1, 2, 3; Quick Check 1, 2, 3p. 750: Examples 1, 2, 6p. 749–750: Examples 4, 5; Quick Check 4, 5p. 750: ex. 9, 10
pp. 35–36: ex. 2, 4, 6, 8, 12, 14, 16, 17Challenge: p. 36: ex. 19, 20Test Prep: p. 36–37: ex. 21Mixed Review: p. 37: ex. 26, 27Chapter Test: p. 50: 12, 19pp. 750–751: ex. 3, 4, 6, 11, 12, 13–16Challenge: p. 751: ex. 17Test Prep: p. 751: ex. 18, 19Mixed Review: 21, 25, 26, 28
Aim: How can we represent bivariate data graphically?
Lesson 6 Quiz
