1.3 Experimental Design

Why is it important to have a control group in an experiment?

• To ensure the treatment has no effect

• To make the experiment more expensive

• To confuse the results

• To provide a baseline for comparison and ensure observed effects are due to the treatment being tested.

Occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other.

• confounding

• response

• explanatory

A fake treatment used a control to reduce psychological effect in humans

• placebo

• response

• explanatory

• stratified

A common type of randomized block design for comparing two treatments in which similar experimental units are paired before randomly assigning them to different treatment groups.

• Matched-Pair Experiment

• Random

  Sampling

• Double-Blind Experiment

• Completely Randomized Experiment

In this type of experiment, neither the subjects nor those who interact with them and/or measure the response variable know which treatment a subject received.

• Matched-Pair Experiment

• Placebo Effect

• Double-Blind Experiment

• Completely Randomized Experiment

A factor that could potentially be influencing the outcome in an experiment or study, but is not officially being tested.

• Explanatory

  Variable

• Experimental

  Units

• Response

  Variable

• Confounding

  Variable

A collection of data from every individual in the population

• survey

• randomized comparative experiment

• census

• observational study

Sampling method is "easy to reach" method by taking a sample without planning which part of the population measured

• undercoverage

• convenience sample

• SRS

• systematic