Data Collection and Experimental Design

The video tutorial discusses two primary methods of data gathering: observation and experiment. It highlights the differences between correlation and causation, using examples like automatic grading in education and hormone therapy studies. The tutorial explains the challenges of establishing causation in observational studies due to confounding variables and emphasizes the importance of experiments in determining causal relationships.

What are the two primary methods of gathering data discussed in the video?

• Experiment and interview

• Observation and survey

• Experiment and observation

• Survey and interview

What is a key limitation of observational studies?

• They are too expensive to conduct

• They cannot establish causation

• They require a large sample size

• They are time-consuming

What is a retrospective observational study?

• A study that looks forward in time

• A study that looks back in history

• A study that involves experiments

• A study that uses surveys

What is a confounding variable?

• A variable that can be easily controlled

• A variable that affects the response variable in a way that cannot be distinguished from other variables

• A variable that is always constant

• A variable that is irrelevant to the study

Why might teachers who use automated grading be different from those who use traditional methods?

• They are less effective

• They are more experimental

• They have more experience

• They have less training

What was the initial belief about hormone replacement therapy and heart attack risk?

• It was unrelated to heart attack risk

• It had no effect on heart attack risk

• It increased the risk of heart attacks

• It reduced heart attack risk by 35 to 50 percent

What was the outcome of the experiments on hormone replacement therapy?

• It was inconclusive

• It confirmed the initial belief

• It showed no reduction in heart attack risk

• It increased heart attack risk

What is the purpose of random assignment in experiments?

• To simplify data analysis

• To ensure a large sample size

• To control for confounding variables

• To reduce the cost of the study

In the context of the video, what is an explanatory variable?

• A variable that explains the response variable

• A variable that is always constant

• A variable that is used to confuse the results

• A variable that is irrelevant to the study

What is a response variable in an experiment?

• A variable that is manipulated

• A variable that is irrelevant to the study

• A variable that is measured to see the effect of treatments

• A variable that is always constant