Chapter 4 Flashcards
Population
The entire group of people you want information about in a statistical study
Census
Sampling every individual in the population
Sample
Ways to chose a sample from a population
Convenience sample
Choosing individuals from the population who are easy to reach results in
Bias
Consistently overestimate or consistently underestimate the value you want to know
Voluntary response sample
Consist of people who choose themselves by responding to a general invitation
Random sampling
Using a chance process to determine which members of a population are included in the sample
Simple random sample (SRS)
Size n is chosen in such a way that every group of n individuals in the population has an equal chance to be selected as the sample
Sampling badly
Using sampling bias
Stratified random sample
Starts by classifying the population of similar individuals, called strata. Choose a separate SRS in each stratum and combine them to form the sample
Strata
Classifying the population into groups of similar individuals
Cluster sample
Start by classifying the population into groups of individuals that are located near each other, called clusters. Choose an SRS of the clusters. All individuals in cluster are in sample
Cluster
Classifying the population into groups of individuals that are located near each other
Inference
The proves of drawing conclusions about a population on the bias of sample data
Undercoverage
Occurs when some members of the population cannot be chosen in the sample
Nonresponse
Occurs when an individual chosen for the sample can’t be contacted or refuses to participate
Observational study
Observes individuals and measures variables of interest but does not attempt to influence the responses
Experiment
Deliberately imposes some treatment on individuals to measure their respinses
Confounding
Occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other
Treatment
A specific condition applied to individuals in an experiment
Experimental units
The smallest collection of individuals to which treatments are applied
Subjects
Human beings that are experimental units
Factors
Explanatory variables in an experiment
Random assignment
Experimental units are assumed to treatments using a chance process
Completely randomized design
The experimental units are assigned to the treatments completely by chance
Control groups
Provides a baseline for comparing the effects of other treatments
Control
Keep other variables that might effect the response the same for all groups
Replication
Using enough experimental units to distinguish a difference in the effects of treatments from chance variation due to random assignment
Blind
Experiment in which the subjects are unaware of which treatment they are receiving
Double blind
Experiment in which neither the subjects or the people who interact with them and measure their response variable know which treatment a subject has
Statistically significant
An observed effect so large that it would rarely occur by chanve
Block
A group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments
Randomized block design
The random assignment of experimental units to treatments is carried out separately within each block
Matched pairs
A type of randomized block design for comparing two treatments in which the idea is to create blocks by matching pairs of similar experimental units
Causation
When changes in the explanatory variable cause changes in the response variable
3 pillars of an experiment
- Random
- Replication
- Control
What does replication do?
Reduces variability
What does control do?
Controls/eliminates lurking or confounding variables
Completely randomized experiment
SRS of experiments
Block design
Stratified experiment
Random sampling
HOW you choose people to be a part of a study
Random assignment
Occurs AFTER people are selected
Placebo effect
When a fake treatment works
What are the benefits of an experiment?
If all 3 pillars are met, then causation can be made
What do experiments do?
IMPOSE A TREATMENT
Simple random sample (SRS)
Number the population, choose the sample by random
*use in experiments, helps divide groups evenly
Stratified
Split population into similar groups. Then sample from each group
Cluster
Split population into groups. Sample. Then choose ENTIRE groups of people
Systematic
Number the population, randomly choose a PLACE then choose every _th person
Multistage
Divide groups into equal areas and randomly choose areas (geographic)
Convenience (ex of bias)
Individuals easiest to reach
Voluntary (ex of bias)
People volunteer to participate by responding
Nonresponse
Majority of population didn’t answer
