Collection of Data Jim Bohan
Three Types of Studies 1. Survey A study in which the researcher gathers data by asking for responses from subjects. 2. Observational Study A study in which the researcher observes behaviors of the subjects. 3. Controlled Experiment A study in which the researcher imposes treatments on the subjects.
Methods of Data Collection Census: Studying ALL subjects of the population of interest. Sample: Studying a proper subset of the subjects from the population of interest.
Issues with Sampling The purpose of sampling is to generate a proper subset of the population that is representative of the population. The major concern with sampling is Bias Bias is a systematic effect that skews all of the data values in a sample.
Types of Sampling: INVALID Convenience Sampling Choosing the subjects in the sample by convenience. Voluntary Response Sampling Subjects are included in the sample on the basis of their volunteering to be included.
Valid Types of Sampling: SIMPLE RANDOM SAMPLE
Valid Types of Sampling: STRATIFIED RANDOM SAMPLE
Valid Types of Sampling: SYSTEMATIC SAMPLE
Valid Types of Sampling: CLUSTER SAMPLE
Valid Types of Sampling: TWO STAGE SAMPLE
The Key to VALID SAMPLING Subjects are chosen by the application of a probability rule; that is, based on RANDOM SELECTION
Controlled Experiments: Vocabulary Experiment: A study in which the researcher imposes treatment(s) on the subjects. Controlled Experiment: A study in which groups receive different treatments whose effects are compared. Units: The subjects who participate in the study.
Controlled Experiments: More Vocabulary Subjects: The term applied to human units. Control Group: The group who receives either no treatment or a placebo, a treatment that causes no effect. Treatment Group(s): The group(s) who receives the treatment(s).
Controlled Experiments: More Vocabulary Explanatory Variable: The variable to which the researcher assigns values in the study: the independent variable. Response Variable: The variable that measures the effect of the value of the explanatory variable: the dependent variable.
Three Requirements of Controlled Experiments Comparison Randomization Replication
Confounding: The Problem Two variables are CONFOUNDED when the effects of the explanatory variable cannot be separated among the treatment groups. A LURKING VARIABLE is a variable that is not included in the study but may be effecting the results of the experiment.
Confounding: The Solution The effects of confounding can be minimized by RANDOMIZATION. The effects of a lurking variable should be spread uniformly among randomized groups.
Basic Experimental Designs Completely Randomized Design Randomized Block Design