A variable that measures an outcome or result of a study

A variable that we think explains or causes change in the response variable

Individuals studied in an experiment

Any experimental condition applied to the subjects

A variable that has an important effect on the relationship among studied variables, but is NOT an explanatory variable

Lurking variables example

An increase in ice cream sales correlates to higher drowning rates. LV is that it is the hot weather that is driving people to buy ice cream and go swimming

When 2 variables' effects on a response variable cannot be distinguished from each other. Can be explanatory or lurking tbh

Confounded variables examples

A study suggests tutoring increases grades, but if students in the tutoring group are more motivated, than MOTIVATION acts as a confounder

Differences between Lurking and Confounded variables?

Confounding variables are identified during study design (identified) Lurking variables are often discovered later (hidden)

Examples of Lurking and Confounded variables?

CV: In a study on exercise and heart health, age is a known, measured variable that affects both, making it a confounder. LV: The ice cream one again

Experiments that study the effectiveness of medical treatments on actual patients

A dummy treatment with no active ingredients

Neither subject nor physician knows which treatment is recieved

Randomized Comparative Experiment

Where 2 or more treatments use chance to decide which subjects get treated, and use enough subjects so that the effects of chance are small

Randomized Comparative Experiment example

1000 patients are randomly assigned to either receive a new drug or placebo :p

Statistically Significant

Where differences among the effects of the treatment are so large that they would rarely happen by just chance!

TO SUMMARIZE: Statistically Significant

The result is unlikely due to chance

Statistically Significant example

You roll a die 100 times, and it comes out to be 5 or 6 95 times. lolz probz loaded

Combining comparison in creating a control group

A study on a new diet pairs two individuals with identical ages and weights (e.g., 30-year-old, 150 lbs). One person receives the new diet, while the other receives no diet to compare weight loss results.

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STA CHAPTER 5

Question	Answer
Response variable	A variable that measures an outcome or result of a study
Explanatory variable	A variable that we think explains or causes change in the response variable
Subjects	Individuals studied in an experiment
Treatment	Any experimental condition applied to the subjects
Lurking variables	A variable that has an important effect on the relationship among studied variables, but is NOT an explanatory variable
Lurking variables example	An increase in ice cream sales correlates to higher drowning rates. LV is that it is the hot weather that is driving people to buy ice cream and go swimming
Confounded variables	When 2 variables' effects on a response variable cannot be distinguished from each other. Can be explanatory or lurking tbh
Confounded variables examples	A study suggests tutoring increases grades, but if students in the tutoring group are more motivated, than MOTIVATION acts as a confounder
Differences between Lurking and Confounded variables?	Confounding variables are identified during study design (identified) Lurking variables are often discovered later (hidden)
Examples of Lurking and Confounded variables?	CV: In a study on exercise and heart health, age is a known, measured variable that affects both, making it a confounder. LV: The ice cream one again
Clinical trials	Experiments that study the effectiveness of medical treatments on actual patients
Placebo	A dummy treatment with no active ingredients
Double blind	Neither subject nor physician knows which treatment is recieved
Whats the control group?	The placebo! :D
Randomized Comparative Experiment	Where 2 or more treatments use chance to decide which subjects get treated, and use enough subjects so that the effects of chance are small
Randomized Comparative Experiment example	1000 patients are randomly assigned to either receive a new drug or placebo :p
Statistically Significant	Where differences among the effects of the treatment are so large that they would rarely happen by just chance!
TO SUMMARIZE: Statistically Significant	The result is unlikely due to chance
Statistically Significant example	You roll a die 100 times, and it comes out to be 5 or 6 95 times. lolz probz loaded
Matching	Combining comparison in creating a control group
Matching Example	A study on a new diet pairs two individuals with identical ages and weights (e.g., 30-year-old, 150 lbs). One person receives the new diet, while the other receives no diet to compare weight loss results.

Created by: liladdoyle

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