Section 1.4 notes Design of Experiments Statistics Section 1.4 notes Design of Experiments

Definitions: Observational study – we observe and measure but don’t attempt to modify the subjects being studied. The best example is a poll. Just ask a question and record the results. Experiment – apply some treatment and then proceed to observe its effects on the subjects. A good example is testing any new medication.

When conducting an experiment the following techniques may be used: Blinding – the subjects do not know if they are receiving the treatment or a placebo (fake) Double blinding – the subjects don’t know and those giving the treatment don’t know

5 Types of Sampling 1. Random sampling – Each member of the population has an equal chance of being selected. Calculators or computers can be used to randomly generate lists of numbers and/or names.

2. Systematic sampling – select every nth element of the population. Example – When sampling students at RCHS, stand at the front door and ask every 10th student who walks in.

3. Convenience sampling – use elements of the population that are readily available. Example – When sampling students at RCHS, ask students in your 1st hour class, on the volleyball team, near your locker, etc.

4. Stratified sampling – classify the population into at least two groups then draw a sample from each group. Example – When sampling students at RCHS, divide them into four groups, freshmen, sophomores, juniors, seniors, at select a sample from each group.

5. Cluster sampling – divide the population into groups, randomly select a few of those groups, and then survey all members of those chosen groups. Example – When surveying students at RCHS, divide them into groups by their 1st hour class. Randomly select a few of those classes and survey everyone in there.

Extra practice on abuses of statistics: To determine the opinion of the student body, 200 students were asked the following question: “Should the current racist mascot be replaced?” What is the problem?

Three of four persons tested said that Brand A cola was better than Brand B. Is it statistically correct to say that 75% of cola drinkers prefer Brand A over Brand B?

In response to a question on a PBS program called “Saving the Environment”, 1234 of 1400 callers said they would be willing to spend 10% more on energy to reduce pollution. The station followed with an announcement that 88% of Americans are willing to pay more for energy to reduce pollution. What is the problem with this scenario?

A Consumer Reports magazine contained the following statement “The number of Americans who purchased new TVs this year is 8,493,073.” What is the problem here?