Get out your Residuals Worksheet! You will be able to distinguish between correlation and causation. Today’s Objectives:

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Presentation transcript:

Get out your Residuals Worksheet! You will be able to distinguish between correlation and causation. Today’s Objectives:

Warm Up Does one cause the other? If so, which one? If not, explain the situation? 1.Water and plant growth 2.Coffee consumption and nervousness 3.Increase in people exercising and increase in people committing crimes 4.Money spent on advertising and sales

Homework Check.44 y= x

Homework Check.78 y= x

Causation There is a strong correlation between cigarette smoking and lung cancer. Does smoking cigarettes cause lung cancer? There is strong association between the availability of hand guns in a nation and that nation’s homicide rate from guns. Does easy access to handguns cause more murders?

Examples from the Book Get out your book. Turn to pg. 184 Definitions to notice: Lurking Variable Common Response Confounded Direct cause-and-effect

Possible Relationships 1.Direct cause-and effect 2.Common response 3.Coincidence

Practice State the relationship among the following variables as: direct cause-and-effect, common response, or coincidence. Explain your reasoning. 1.Speed and breaking distance 2.Number of stop signs in a city and the number of families with 3 children 3.High school grades and college grades

Examples There is a positive association between ice cream sales and the number of people who drown. Does that mean eating ice cream causes people to drown? Compose a more plausible explanation that involves common response.

Evidence for Causation The best evidence for causation comes from well-designed experiments. What if we cannot do an experiment? How do we establish causation? Turn to pg. 187

More Examples Turn to pg. 188 Individually work through #4.40, 4.41, and 4.43 Compare your answers with a friend. QUIETLY!

Quiz Review Quiz 2 is scheduled for Friday. It will cover all of Ch. 4. Key concepts are: scatterplots, direction strength, correlation, regression line, slope, y-intercept, residuals, and causation