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1. A dairy scientist is testing a new feed additive. She chooses 13 cows at random from a large population of cows. She rando

I do not know how make dot plots. I have the plots but do not know the code for R.

Help me with the code please

Graph the data as you see fit. Why did you choose the graph(s) that you did and what doesit (do they) tell you? We might star

The new diet looks a lot higher but also seems to have more spread. To look at spread even closer, we could do a dotplot of d

1. A dairy scientist is testing a new feed additive. She chooses 13 cows at random from a large population of cows. She randomly assigns mold 8 to get the old dict, and nnew-5 to get the new diet including the additive. The cows are housed in 13 separated pens and each gets separate feed, with or without additive as appropriate. After two wecks, she picks a day and milks each cow using standard procedures and rccords the milk produced in pounds. The data are below Old Diet: 43, 51, 44, 47, 38, 46, 40, 35 New Dict: 47, 75, 85, 100, 58 Let μne w and Mid be the population mean milk prductions for the new and old diets, resp(ctively. She wishes to test: VS. 0 using α-0.05 (a) Comment on the assumption that the cows are independent both within and between treatments. (b) Graph the data as you s(x) fit. Why did you choose the graph(s) that you did and what does it (do they) tell you? (c) Choose a test appropriate for the hypotheses above, and justify your choice based on your answers to parts (a) and (b). Then perform the test by computing a p-value, and making a reject or not reject decision. You may use R to compute means and SDs for the groups, but do not use t.test) to perform the test. Show your work. State your conclusion in the context of the problem. If a difference exists could you infer that the additive caused the change?
Graph the data as you see fit. Why did you choose the graph(s) that you did and what doesit (do they) tell you? We might start with a dotplot of the original data so we can get a sense for both location and spread. This is probably better than a histogram or boxplot since the sample sizes are small ew 40 60 80 100 Milk (lbs)
The new diet looks a lot higher but also seems to have more spread. To look at spread even closer, we could do a dotplot of deviations 2017 2017 Old 20 10 20 -10 Deviations
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