agiicuor You are pertormllig all Ul Prob 14.04 in which you will study whether p

Question

agiicuor You are pertormllig all Ul Prob 14.04 in which you will study whether placing small bits of iron in the soil will increase the yield of barley. Randomly scattered across an enclosure owned by the state's agricultural field of- fice, you have marked off ten plots, each of size 10 meters by 10 meters. You randomly assign five of the plots to be controls, and in the other five you place the iron. A colleague hears of your experiment and asks to join it. She would like to test zinc. Still another colleague wants to test copper and another has two different liquid fertilizers to test. The head of the field office asks you to share the data from your control plots, so that the other researchers won't have to grow additional control plots. This will reduce the overall cost of the set of experiments. He points out that the additional experiments impose absolutely no burden on you since they are being grown in plots that you are not using. All you need to do is provide the yield heasurements for the control plots to your colleagues so that they can use them in the evaluation of their own data. You wonder whether there is a hidden cost. Will you need to adjust the p-value thresholdhold? For instance, a Bon- ferroni correction would reduce the threshold for significance from 0.05 to 0.01, since there are five experiments altogether (iron, zinc, copper, and two fertilizers, each compared to a control). What's the cost of making such an adjustment? A It reduces the significance level of your ex- B It reduces the power of your experiment. D None of the above. What's the argument for making an adjustment to the p-value periment. C It invalidates the comparison to the control threshold?

Explanation / Answer

If here the five plot where researcher is placing iron is not the same where zinc , copper fertilizer is using.

1 Option D) None of the above. Because the iron researcher only sharing the yield of control plots . He is not sharing his own plot.

2A) Doing multiple experiment results type 1 error.

3) The additional experiment have nothing to do with the iron experiment.

4) No, There are still multiple tests being done, even if the data sets don't overlap.

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