Source

Confounding variables check

Based on procedures of a study.

Alternative explanations ruling out.

Cause and effect

As a brief summary, you can only assume cause-and-effect when you meet the following three criteria in your study:

  • The cause preceded the effect in terms of time.
  • The cause and effect vary together.
  • There are no other likely explanations for this relationship that you have observed.

Factors that improve internal validity

  • Randomization

  • Random selection

  • Blinding participants

  • Experimental manipulation (cessation to smokers)

  • Same study protocol to both groups

Causation Correlation

Recall that two variables being statistically related does not necessarily mean that one causes the other. “Correlation does not imply causation.” For example, if it were the case that people who exercise regularly are happier than people who do not exercise regularly, this implication would not necessarily mean that exercising increases people’s happiness. It could mean instead that greater happiness causes people to exercise (the directionality problem) or that something like better physical health causes people to exercise and be happier (the third-variable problem).

Checking assumptions

If they use t-distributions then they come with assumptions.

check if the assumptions are valid.

If there are two samples then each sample has different assumptions

Format

Confounding variables?

Random

Randomization

Systematic issues (biases such as )

pertains to lebanon and female population

Skips “uneducated?”

Sample issues (potential other variables)