Stats Review 4.2 - Experiments

The response variable is:

• The variable we expect to explain or predict the value of the explanatory variable.

• Sometimes called the independent variable (IV)

• The variable we expect to change in response to the explanatory variable

• Also known as EV

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

We wish to investigate the relationship between the number seeds planted in a garden and the number of fruit grown. The explanatory variable (EV) is

• The number of fruit grown

• The amount of soil in the garden

• The number of hours spent watering the plants

• The number of seeds planted

Tags

CCSS.HSA.CED.A.2

CCSS.HSS.ID.B.6

We wish to investigate the relationship between the time spent shopping and the number of items bought. The response variable (RV) is

• The number of items bought

• The number of items at the shop

• The time spent shopping

• The time spent getting to the shops

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

Which of the following is true?

• We use the response variable to explain changes that might be observed in the explanatory variable.

• The explanatory variable is the variable we expect to be explained by the response variable

• The response variable is also known as the predictor variable

• The explanatory variable is used to explain or predict the value of the response variable

Tags

CCSS.HSS.ID.C.7

We wish to investigate whether a person’s age can be predicted from their IQ score. Which is the explanatory variable (EV)?

• Age

• IQ Score

• Both Age and IQ Score

• None of the Above

Tags

CCSS.HSS.ID.B.6

Studies have shown that the marks received by a student depend on the amount of hours spent studying. Which is the response variable (RV)?

• Hours spent studying

• Marks

• Both Marks and Hours spent studying

• None of the above

The four principles of experimental design are:

• Control, Random Assignment, Repetition, and Comparison

• Hypothesis, Experiment, Results

• Control, Bias, Ethics

• Design , Treatments, Comparison

Tags

CCSS.HSS.IC.B.3

Variable that may not be seen, but is a variable that has an important effect on the relationship between the explanatory & response variables.

• Confounding

• Lurking

• Explanatory

• Response

Tags

CCSS.HSS.ID.C.9

Which word matches the following definition? A correlation between variables that one variable directly effects the other variable

• lurking

• confounding

• causation

• common response

Tags

CCSS.HSS.ID.C.9

There's a positive association between ice cream sales and the number of people who drown. Does that mean eating ice cream causes people to drown?

• Yes, one clearly causes the other

• No, there are other lurking variables causing a common response

• No

• Yes

Tags

CCSS.HSS.ID.C.9