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stats test 1

QuestionAnswer
Simple Random Sampling Every member has an equal chance.
Systematic Sampling Select every kth person.
Stratified Sampling Sample from every group.
Cluster Sampling Select entire groups.
Undercoverage Some members cannot be chosen.
Voluntary Response Bias People choose whether to participate.
Factor Variable manipulated by researcher.
Level Specific value or category of a factor.
Treatment Combination of factor levels.
Response Variable Outcome measured.
Control Limit outside influences.
Randomization Randomly assign treatments.
Replication Use enough subjects or repeat experiment.
Blocking Group similar subjects before random assignment.
Simulation Uses randomness to model a real situation.
Observational Study Observe subjects without imposing treatments.
Experiment Impose treatments and measure response.
Population Entire group being studied.
Sample Subset of the population.
Bias Systematic error that makes results unrepresentative.
Simulation Component A single random outcome representing one observation.
Simulation Trial One complete repetition of a simulation.
Simulation Response Variable Outcome measured during the simulation.
Simple Random Sampling Keyword Equal chance.
Systematic Sampling Keyword Every kth person.
Stratified Sampling Keyword Sample from every group.
Cluster Sampling Keyword Select entire groups.
Undercoverage Keyword Some people cannot be selected.
Voluntary Response Bias Keyword People choose to respond.
Factor vs Response Variable Factor is manipulated; response variable is measured.
Level vs Treatment Level is a category of a factor; treatment is a combination of levels.
Example of Voluntary Response Bias Online newspaper poll where readers choose to participate.
Example of Undercoverage Part of the population cannot be chosen.
Example of Cluster Sampling Randomly selecting communities within a city.
Example of Stratified Sampling Randomly selecting students from every grade level.
Election Simulation Support 75% favorite candidate and 25% underdog.
Election Simulation Component Use two-digit random numbers.
Election Simulation Assignment 00-74 favorite candidate; 75-99 underdog.
Election Simulation Trial Generate 100 random numbers and count votes.
Election Simulation Response Variable Whether the underdog wins.
Discrimination Simulation Scenario 10 men and 10 women apply for 3 positions.
Discrimination Simulation Goal Determine whether hiring all women could happen by chance.
Discrimination Simulation Result All women selected 2 out of 18 trials.
Discrimination Simulation Probability 11.1%.
Discrimination Simulation Conclusion 11.1% is not rare enough to strongly suggest discrimination.
Purpose of Experimental Design Determine cause-and-effect relationships.
Purpose of Simulation Estimate probabilities using random outcomes.
What sampling method selects every kth individual? Systematic Sampling.
What sampling method gives every member an equal chance? Simple Random Sampling.
What sampling method samples from every group? Stratified Sampling.
What sampling method selects entire groups? Cluster Sampling.
What happens when some people cannot be selected? Undercoverage.
What happens when people choose to participate? Voluntary Response Bias.
Created by: user-2050030
 

 



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