1. Confounding often defeats attempts to show that one variable causes changes i
ID: 3201853 • Letter: 1
Question
1. Confounding often defeats attempts to show that one variable causes changes in another variable. Confounding means that
2. Gastric freezing used to be used as a treatment for stomach ulcers. Physicians justified the use of this treatment based on interviews with patients, pre and post treatment that revealed an improvement, on average, in patient discomfort. The problem with this experimental design was that
3. What do we mean by statistical significance?
4.In this class we relegated all confounding to two possible sources. What were those?
5. In BN1.16 (or on the video version) on Comparison and Randomization we discussed an aids drug (Ribavirin) that the FDA ended up rejecting. What was wrong with the experimental design that the company used?
A. we would get widely varied results if we repeated the study many timesExplanation / Answer
Question 1:
Confounding is a phenomenon where a third variable correlates with both dependent and independent variables. Hence, it explains some of the variation caused in these variable thereby leaving experimenter with difficulty to choose appropriate dependent variable.
(Answer) Option B: the effects of two or more variables are mixed up, so we cannot say which is causing the response
Question 2:
There is a possibility in this experiment that patients "feel" that since they have been treated, there might be improvement. Hence, introduction of a placebo testing will help in gauging the real effect of t
(Answer) Option C: the design did not allow any placebo comparisons
Question 3:
Statistical significance means obtaining a result which can't be an outcome of any random chance.
(Answer) Option B: treatment differences that are sufficiently large that you can say they are unlikely to have happened by chance
Question 4:
Confounding is generally caused by improper sampling with lack of randomization.
(Answer) Option A: Improper comparison and lack of randomization
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