Stats

Extraneous Variables | Variables other than the explanatory variable that may affect the response variable.

Confounding Variable | An extraneous variable associated with both the explanatory and response variables, making cause-and-effect difficult to determine.

Random Sampling | Using a chance process to determine which members of a population are selected for a sample.

Simple Random Sample (SRS) | A sample where every possible group of n individuals has an equal chance of being selected.

Choosing an SRS with a Random Number Generator | Label every member, randomly generate the needed labels, then select the corresponding individuals.

Strata | Groups within a population whose members share characteristics related to the response variable.

Stratified Random Sample | Divide the population into strata, take an SRS from each stratum, and combine the samples.

Clusters | Groups of population members located near each other.

Cluster Random Sample | Randomly select entire clusters and include every individual in the selected clusters.

Systematic Random Sample | Randomly choose a starting point, then select every kth individual after it.

Components of an Investigative Question | Identify the variables, population/parameters, and type of conclusion or inference that can be made.

Control Group | A group that provides a baseline for comparing the effects of other treatments.

Placebo | A treatment with no active ingredient that otherwise resembles the real treatment.

Placebo Effect | When subjects respond to a treatment simply because they believe they are receiving treatment.

Double-Blind Experiment | Neither the subjects nor the people measuring the response know which treatment subjects receive.

Single-Blind Experiment | Either the subjects OR the people measuring responses do not know which treatment subjects receive.

Random Assignment | Using chance to assign experimental units to treatments.

Purpose of Random Assignment | Creates roughly equivalent treatment groups and allows cause-and-effect conclusions.

Bias | A study design is biased when its method systematically tends to overestimate or underestimate a population value.

Convenience Sample | A sample made up of population members who are easiest to reach.

Voluntary Response Sample | A sample of people who choose themselves to participate by responding to an invitation.

Undercoverage | Some members of the population are less likely or unable to be selected.

Nonresponse | A selected individual cannot be contacted or refuses to participate.

Response Bias | Survey responses systematically differ from the truth in the same direction.

Completely Randomized Design | Experimental units are assigned to treatments completely at random.

Matched Pairs Design | Similar units are paired and treatments randomly assigned within pairs, or each unit receives both treatments in random order.

Replication | Assigning multiple experimental units to each treatment.

Scope of Inference: Generalizing to a Larger Population | Results can be generalized to a population when subjects were randomly sampled from that population.

Scope of Inference: Cause-and-Effect | Cause-and-effect conclusions are possible when treatments are randomly assigned and the difference is statistically significant.

Direct Control | Keeping extraneous variables the same for all experimental units.

Block | A group of experimental units known before the experiment to be similar in a way related to the response.

Blocking Variable | The variable used to separate experimental units into blocks.

Randomized Block Design | Divide units into blocks, then randomly assign treatments separately within each block.

Marginal Relative Frequency | The proportion with a specific value of one categorical variable, ignoring the other variable.

Joint Relative Frequency | The proportion with a specific value for BOTH categorical variables.

Conditional Relative Frequency | The proportion with a specific value of one variable among individuals sharing a specified value of another variable.