Experimental Design

Multiple Choice

Which of the following is NOT a key consideration when designing an experiment with statistics in mind?

• Accurately define variables

• Use appropriate controls

• Ignore experiment noise

• Understand the distribution of data

Open Ended

Why is it important to clearly define variables and levels of data when designing an experiment?

Multiple Choice

Which of the following techniques can help increase the signal-to-noise ratio in experimental results?

• Repeating experiments

• Reducing the sample size

• Ignoring randomization

• Using only one measurement

Open Ended

Explain why making repeated measurements is especially helpful when an individual measurement may have a lot of variability.

Fill in the Blanks

Increasing the number of items or people that you are collecting data from increases the probability that what you are observing is indicative of the whole

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Multiple Choice

Which of the following are examples of when randomization of samples is especially critical?

• When the population is very heterogeneous

• When the population is very homogeneous

• When drawing conclusions about a single item

• When only one group is being tested

Open Ended

Describe a scenario where randomization of experiments would be necessary to avoid introducing overlooked variables.

Multiple Choice

What is the main purpose of repeating experiments in scientific research?

• To determine if the data was a fluke or represents the normal case

• To reduce the number of variables

• To save time and resources

• To avoid using control groups

Open Ended

Reflecting on what you learned about experimental design, what is one question you still have or something you would like to know more about?

Multiple Choice

Which of the following is NOT a key aspect of designing a project with statistics in mind?

• Accurately define variables

• Identify the type of experiment

• Ignore experiment noise

• Use appropriate controls