Chapter 4: Designing Studies review

Which of the following is an example of a simple random sample?

• In the hallway, you select every 5th person that you see to survey

• Going around to every classroom and picking the first 5 people closest to the door to survey

• Using a random number generator to pick 15 students to survey

I am collecting data on how much people like Olivia Rodrigo. If I go to her concert and I survey the first 50 people that walk in the doors, would this bias my data by OVER-estimating or UNDER-estimating that true feelings of the population?

• Overestimate

• Underestimate

Bias is best described as:

• when a study systematically favors certain outcomes over others

• when the sample value does not math the population value

• when participants could get hurt in the process, so the data collector does an observational study instead

• when the population value does not match the true value

What best describes a simple random sample of size "n" from a population of size N?

• Everyone is equally likely to be selected

• Groups of size n have the same chance of being chosen

• Individuals are always selected with replacement (putting their name back in the hat)

• Each individual has the probability of n/N to be chosen

There is a study being done on the difference in performance between on-brand Germ-X and off-brand Germ-X. The collector randomly chooses 40 people to try the two germ-X options. He chooses which members are given the on-brand and he chooses which members are given the off-brand. What can they conclude from their results?

• We can not establish a connection for the population of Germ-Xs but we can determine cause and effect between them

• We can determine that the results will match that of any Germ-X user

• We can determine that there is a cause and effect, thus the comparison results were relevant

• Only the people in this sample will have results similar to ours

You are testing the effects of sunlight through a magnifying glass on insects in your yard. What are the experimental units here?

• The sunlight

• The magnifying glass

• The insects

• You, the collector

Increasing the sample size will do all of the following EXCEPT

• decrease variability (spread) in the data

• bring the sample value closer to the true population value

• get rid of bias completely

The most important reason for randomization of data is to:

• reduce variation in the data

• make an experiment "double blind"

• get rid of outliers

• create groups that are similar and unbiased so that we can compare them

Can we conclude cause and effect results from a survey?

• Yes

• No

• I don't know

In order to determine cause and effect, we should use:

• observational study

• experiment