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CAUSE AND EFFECT

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by

Karen Iida

on 27 November 2014

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Transcript of CAUSE AND EFFECT

Accidental Relationship
VOCABULARY
Cause-and-Effect Relationship
Common-Cause Factor
Definition:
When a change in the independent variable, X, produces a change in the dependent variable, Y
Example:
More hours studied will cause your marks to increase
Definition:
An external variable that causes two variables to change in the same way
Karen Iida
Wednesday, November 26, 2014
Chapter 3 Section 4
Success Criteria
Learning Goal
Reverse Cause-and-Effect Relationship
I will be successful when I can:
Define various types and degrees of casual relationships between variables
Explain the difference between a common-cause factor and an extraneous variable
Definition:
When the dependent and independent variables are reversed in the process of establishing a relationship.
CAUSE AND EFFECT
Explore different types of relationships between two variables
Cause-and-Effect Relationship
Common-Cause Factor
Reverse Cause-and-Effect Relationship
Accidental Relationship
Presumed Relationship
Extraneous variables
Experimental group
Control group
Increasing the temperature on the thermostat will cause the room temperature to increase

Physical activity will cause your heart rate to increase

Increasing the height a ball is dropped will cause an increase with the bounce height
Example:
A town finds the revenue from parking fees at the beach each Summer correlates to the tomato harvest

Common-Cause Factor: Good weather
Increases the tomato crop and the number of people at the beach
The revenue from the aquarium correlates to the ice-cream

Common-Cause Factor: Hot temperature
Increases the number of people going the the aquarium (cool inside = air conditioner) and number of ice-cream bought at the store
Example:
A positive correlation between gun ownership and violent crime; the higher number of gun owned, the higher the rate of violent crime.

Reverse: High rates of violent crime may cause fearful citizens to purchase guns for protection
Define:
A relationship between two variables that has a correlation, but it is entirely by coincidence.
Example:
An increase in the number of students enrolled in Data Management and increase in the number of BMW's on the road
No relationship between the students' course selection and the type of car people choose to drive
Presumed Relationship
Definition:
A correlation does not seem to be accidental even though no cause-and-effect relationship exists
Example:
A number of Centennial and McMaster nursing graduates and the number of job offer from Grace Hospital
Seems logical that with the increase of graduates in nursing, there would be more job offers. However, there is no actual direct relationship between them.
Extraneous variables
Definition:
An external variable that complicates the nature of the cause-and-effect relationship between two variables
In order to reduce the effect of extraneous variables:
Researchers compare an experimental group (the group for which the independent variable is changed) to a control group (the group for which the independent variable is held constant)
The experimental and control group should be as similar as possible, so that the extraneous variables will have the same effect on both groups
Any difference in the dependent variable for the two groups can then be attributed to the changes in the independent variable
Is the Correlation a result of a Cause-and-Effect Relationship?
Techniques that can help determine whether a correlation is the result of a cause-and-effect relationship:
Use sampling methods that hold the extraneous variables constant
Conduct similar investigations with different samples and check for consistency in the results
Remove, or account for, possible common-cause factors
Full transcript