Explain, in one sentence, why it is difficult (impossible?) to infer a causal re

Question

Explain, in one sentence, why it is difficult (impossible?) to infer a causal relationship from an observational study. If we obtain a two-sided p-value of 0.04 for a test of the null hypothesis that the population mean is 20, we would reject the null hypothesis that the population mean is 20 vs. a two-sided alternative at level alpha = 0.05. TRUE FALSE If we obtain a two-sided p-value of 0.04 for a test of the null hypothesis that the population mean is 20, the value 20 will be in the 95% confidence interval for the population mean. TRUE FALSE If we obtain a two-sided p-value of 0.04 for a test of the null hypothesis that the population mean is 20, the value 20 will be in the 90% confidence interval for the population mean. TRUE FALSE

Explanation / Answer

1.

Suppose researchers want to determine if people tend to snack more while they watch TV. One possible design that we considered was to recruit participants for an observational study, and give them journals to record their hourly activities the following day, including TV watched and snacks consumed. Then they could review the journals to determine if snack consumption was higher during TV times.

We identified this as a prospective observational study, carried forward in time. Studying people in the more natural setting of their own homes makes the study more realistic than a contrived experimental setting. Still, when people are obliged to record their behavior as it occurs, they may be too self-conscious to act naturally. They may want to avoid embarrassment and so they may cut back on their TV viewing, or their snack consumption, or the combination of the two.

By now you should have an idea of how difficult — or perhaps even impossible — it is to establish causation in an observational study, especially due to the problem of lurking variables.

The key to establishing causation is to rule out the possibility of any lurking variable, or in other words, to ensure that individuals differ only with respect to the values of the explanatory variable.

In general, this is a goal which we have a much better chance of accomplishing by carrying out a well-designed experiment.

2. a) TRUE because here p-value <alpha=0.05 so we reject null.

b) FALSE. Because Confidence interval is not given

c)FALSE. Because Confidence interval is not given

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