t-test in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a t-test on two numeric vectors x and y.

R Programming

result <- t.test([1], y)

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Ax

Bmean

Ct.test

Dy

Attempts:

3 left

💡 Hint

Common Mistakes

Using the function name instead of a variable.

Passing the wrong variable as the first argument.

The t.test() function compares two numeric vectors. Here, x is the first sample.

2fill in blank

medium

Complete the code to perform a paired t-test on vectors a and b.

R Programming

t.test(a, b, paired = [1])

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ANULL

BTRUE

CNA

DFALSE

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to set paired = TRUE for paired tests.

Using paired = FALSE which runs an unpaired test.

Setting paired = TRUE tells R to perform a paired t-test, comparing matched samples.

3fill in blank

hard

Fix the error in the code to test if the mean of vector data is different from 5.

R Programming

t.test(data, mu = [1])

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A5

BNULL

Cmean(data)

D"5"

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the number as a string with quotes.

Using the sample mean instead of the hypothesized mean.

The mu argument expects a numeric value, not a string. Use 5 without quotes.

4fill in blank

hard

Fill both blanks to perform a one-sided t-test checking if mean of x is greater than 10.

R Programming

t.test(x, mu = [1], alternative = [2])

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A10

B"less"

C"greater"

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong alternative hypothesis string.

Setting mu to a wrong value.

Set mu = 10 as the hypothesized mean and alternative = "greater" to test if the true mean is greater than 10.

5fill in blank

hard

Fill all three blanks to perform a two-sample t-test assuming unequal variances between groups a and b.

R Programming

t.test([1], [2], var.equal = [3])

Drag options to blanks, or click blank then click option'

Aa

Bb

CFALSE

DTRUE

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the sample vectors.

Setting var.equal to TRUE when variances are unequal.

Use vectors a and b as samples, and set var.equal = FALSE to assume unequal variances (Welch's t-test).