re 4: Normal oo plot of 10 student grades 1.0 1.5 Theoretical Quantiles Since ?2

Question

re 4: Normal oo plot of 10 student grades 1.0 1.5 Theoretical Quantiles Since ?2 is unknown, we need to use the t distribution to compute a confidence interval for the mean grade based on our sample of size n 10 observations. #For the small sample of size 10 mean(y)+c(-1,1) qt.975,9)-sd(y)/sqrt Clength(y)) ## [1] 8.029637 14.570363 qt (.975,9) ## [1] 2.262157 t.test(y, m-10) ## One Sample t-test ##data: y ## t-0.89923, df-9, p-value-0.392 ## alternative hypothesis: true mean is not equal to 10 ## 95 percent confidence interval: ## 8.029637 14.570363 ## sample estimates: ## mean of x

Explanation / Answer

FIGURE 4 is normal QQ plot. This plot is used to check whether the data is normal or not. Normal QQ plot plots the theoretical quantile versus sample quantiles. If the plot is a straight line then we can safely assume the data to be normal in apply our model.

The plot is almost straight line so we can go ahead with our normal assumption and fit our normal model. The closer the data look like straight line the closer that it is to normal distribution.

FIGURE 7 is plot of grades vs categorical weakly alcohol consumption. The grade is plotted corresponding to all levels in data. By looking at the plot we can say that there is no clear sign of effect of level of weakly alcohol consumption on grade. The plot does not show any clear trend of what is the effect of alcohol consumption on grades.

So if we have to draw conclusion based only on plot we will conclude that there is no significant effect of alcohol consumption on grades.

Thanks

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