Question Part Points Submissions Used Question Part Points Submissions Used Ques

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Question Part Points Submissions Used Question Part Points Submissions Used Question Part Points Submissions Used Question Part Points Submissions Used Question Part Points Submissions Used 52.4 43.4 45.1 45.1 48.7 50.3 38.6 41.4 46.1 45.3 39.6 44.3 50.0 46.5 48.3 46.7 49.4 36.2 39.4 45.4 No, it is not appropriate to analyze these data using methods based on Normal distributions. These data are skewed to the left.Yes, it is appropriate to analyze these data using methods based on Normal distributions. There are no outliers and no particular skewness.    No, it is not appropriate to analyze these data using methods based on Normal distributions. These data are skewed to the right.Yes, it is appropriate to analyze these data using methods based on Normal distributions. There are no outliers and the data is skewed to the right.No, it is not appropriate to analyze these data using methods based on Normal distributions. There are extreme outliers. Question Part Points Submissions Used

Explanation / Answer

R commands with output :

n=length(x)
> hist(x)
> boxplot(x)
> mean(x) # mean
[1] 45.11
> y=sd(x) # standard deviation
> y
[1] 4.310929
> Se=(y/sqrt(n)) # standard error
> Se
[1] 0.9639529
> t.test(x)

One Sample t-test

data: x
t = 46.797, df = 19, p-value < 2.2e-16
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
43.09242 47.12758
sample estimates:
mean of x
45.11

we get 95% confidence interval is (43.09242, 47.12758)

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