RGoogleForms

This is a prototype for generating quizzes using R Markdown and using Google Forms to collect the responses. You can try it out by filling this quiz and seeing the responses here. You can find the source R Markdown file generating this quiz here. You can install the package RGoogleForms from github

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Question 3

What can we say about the relationship between the correlation r and the slope b of the least-squares line for the same set of data?

Both r and b always have values between -1 and 1. r is always larger than b. r and b have the same sign (+ or -). the slope b is always equal to the square of the correlation r. b is always larger than r.

Question 4

The distribution of the amount of money spent by students for textbooks in a semester is approximately normal in shape with a mean of 290 and a standard deviation of 17. According to the standard deviation rule, almost 37.2% of the students spent more than

256 273 307 324 341

Question 5

256 273 307 324 341

Question 6

Can a college's acceptance rate be predicted by the Average SAT score of the students in that college? Here are the results from a sample of schools. Consider the problem of predicting Acceptance Rate (Y) from average SAT score (X). What would be the slope of the best fitting line to predict y from x?

	SAT Score (X)	% Accepted (Y)
Mean	1264	38
Stdev.	62	13
Correl.	-0.61

-0.3721 -0.1279 -2.9092 -0.0183

Question 7

The correlation between two scores on tests was found to be exactly 1. Which of the following would not be true, regarding the corresponding scatterplot?

Every point would lie along a perfect straight line, with no deviations at all. The slope of the best fitting line would be 1. The best fitting line would have an uphill (positive slope). All of the above are true.

Question 8

Let us enter the data on tests with:

t1 <- c(75, 85, 78, 82, 65, 85)
t2 <- c(90, 95, 87, 92, 94, 95)

Which command will do a two sample t test with an assumption of equal variances:

t.test(t1, t2) t.test(t1, t2, var.equal=TRUE) two.sample.t.test(t1,t2)