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Question 1

Tailed tailed Test function for proportion?

Answer 1

prop.test(num of successes, n, p0 (hypothesized value), alternative = “less”)

Question 2

Assumptions for prop.test function?

Answer 2

•n*p0 >= 10
•n(1 - p0) >= 10
•SRS (simple random sample)

Question 3

Right tailed test for proportions?

Answer 3

prop.test(num of successes, n, p, alternative = “greater”)

Question 4

Two sided test for proportions?

Answer 4

prop.test(num of successes, n, p, alternative = “two.sided”)

Question 5

Two sided Test for two proportions (testing whether the proportion of successes between two populations are the same)?

Answer 5

prop.test(x = c(success1, success2), n = c(n1, n2), alternative = “two.sided”)

Question 6

Right tailed prop test for two proportions?

Answer 6

prop.test(x = c(success1, success2), n = c(n1, n2), alternative = “greater”)

Question 7

Left tailed test for two proportions?

Answer 7

prop.test(x = c(success1, success2), n = c(n1, n2), alternative = “less”)

Question 8

Two sided test for single mean?

Answer 8

t.test(x = sample, alternative = “two.sided”, mu)

Question 9

Right tailed test for the means of two populations?

Answer 9

t.test(x = sample1, y = sample2, alternative = “greater”, var.equal = TRUE), var.equal determines whether the variances are the same. Two-sample t test

Question 10

Left tailed test to compare the means of two separate populations?

Answer 10

t.test(x = sample1, y = sample2, alternative = “less”, var.equal = TRUE), var.equal determines whether the variances are the same. Two-sample t test

Question 11

Welch two-sample t test?

Answer 11

When comparing two samples without the same variances.