Chapter 13: Part II

1. Chapter 13: Part II AP Statistics

2. Statistically Significant How do we know if the results of an experiment really show that there is a difference? Suppose we tested a medication to see if it reduced blood pressure better than on older medication. In our results, we calculated that, on average, the medication reduced blood pressure by about 10% more than the older medication. Is this evidence that the new medication worked better than the new? What if it only reduced it by 3%? 20%

3. Statistically Significant In order to determine if the difference is enough we need to say that the differences are statistically significant. This means that the differences we observed are too big to be explained by chance differences. If they are too big to be explained by chance, then we can attribute the differences to the experiment.

4. Statistically Significant Suppose we flip a coin 100 times and it comes up heads 47 times. Is the coin fair, or is it weighted? We know it should come up heads 50 times (theoretically), but this difference between what we got and what we should get is not large and can be explained by chance differences (it is not unlikely to get those results if the coin was fair). However, if we got 30 heads, we may determine that a difference that big is too large for us to say that it is due to chance differences (it is very unlikely to get those results if the coin was fair). This last result shows that the differences are statistically significant and that the coin is probably not fair.

5. Statistically Significant We will learn how to determine that in later chapters. Always be skeptical of studies and experiments that discuss how much better (or worse) one thing is than another without stating that the results are statistically significant. That is the only way to determine if there really is a difference between two (or more) things.

6. Experiments and Samples(differences, similarities and other info) Similarities • Both use randomization to get unbiased data

7. Experiments and Samples(differences, similarities and other info) Differences • Samples try to estimate the population parameters, so randomizing is an attempt at having the sample be representative of the population • Experiments try to assess the effectiveness of treatments, so randomization is used to assign treatments so as to reduce (eliminate) unwanted problems. Experiments rarely draw their subjects from random samples of the population.

8. Experiments and Samples(differences, similarities and other info) Differences • If our objective is to learn something about a population Sample Survey • If our objective is to see if there is a difference in the effects of two treatments Experiment • If our objective is just to use an existing situation to look for trends and/or contributing factors Observational study

9. Experiments and Samples(differences, similarities and other info) Other • If the subjects in an experiment are not random samples from the population, be cautious about generalizing the results of an experiment until the experiment has been replicated using different subjects, environments, etc. • Experiments typically draw stronger conclusions than surveys (even if experimental subjects are not random samples). • Because, by looking only at the differences across treatment groups, experiments cancel out many of the sources of bias.

10. Control Treatments If we are attempting to see if a medication effectively reduces anxiety, we don’t just want to give all our subjects the medication and record if their anxiety decreased or not. Instead, we want to compare how much their anxiety decreased compared to people who did not take the medication. This comparison group is the control group and that group’s measurement is called the control treatment.

11. Blinding Blinding is when we create an environment where subjects and/or researchers (physicians, technicians, psychologists, etc) do not know who gets treatment and who gets placebo. Who can affect the outcome of an experiment? • Those who could influence the results (the subjects, treatment administrators, or technicians, etc) • Those who evaluate the results (judges, treating physicians, etc)

12. Blinding When individuals in one of those two groups is blinded we say that the experiment is single-blind. When individuals in both of those groups are blinded we say that the experiment is double-blind.

13. Blinding It is important to blind because it is easy for a person’s knowledge about which treatment is given to which people to influence there actions and beliefs. Therefore, blinding will eliminate this form of bias.

14. Placebo A placebo is a “fake” treatment that looks just like the treatments being tested. It many times is used for the control group’s treatment It is the best way to blind subjects

15. Placebo Sometimes groups who are treated with the placebo (control group) will show an improvement. This is not uncommon. This effect (when the control group show an improvement when treated with placebo) is called the placebo effect. It is not uncommon that 20% or more of subjects who are given a placebo report things such as reduction of pain, decreased depression and improved health issues

16. Characteristics of Good Experiments • Randomized • Comparative • Double-Blind • Placebo-controlled