555 - smokers and did not manipulate any variable No...

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Joseph So 2c 1. The distributions are very similar. Both are normal, and have similar centers. However the non smoker has a slightly higher mean weight than smokers. However the standard deviations are almost the same. I would say smoking changes the babes weight by about .3, give or take about .2. 2. I would say that the typical difference in medians between the two groups is plus or minus .1. An unusually large difference would be anything more extreme than plus or minus 3. about 3 times. I would say that it rarely happens, because when looking at the graph of median
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differences, the occurrence of a median difference of .25 or higher occurs only about 3 times out of a hundred, which is rare. 4. It rarely occurred that the difference was .25 or bigger, meaning that smoking is most likely statistically significant. 5. Observational, because the researchers took data from people who were already smokers or non
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Unformatted text preview: smokers, and did not manipulate any variable. No because the difference could be caused by lurking or confounding variables. Summary Questions The question being answered is whether the difference seen in birth weights between smokers and nonsmokers, can be attributed to smoking or random variance. The observational study took the birth weights of 999 babies from both smoking mothers and nonsmoking mothers. I analyzed this data by visually displaying the weights of the babies on a bar graph. From the bar graph I calculated the mean and median for both smoking and non smoking mothers. Ultimately I concluded that there was a .25 difference between non smoking and smoking mother birth weights. I concluded that this was statistically significant because of the rarity that such discrepancies occurred. This can be useful in the real world to mothers carrying a child....
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555 - smokers and did not manipulate any variable No...

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