Question

Q1.

The following is some R code followed by output.

> set.seed(24); y1 = rnorm(30, 10, 5)
> set.seed(34); y2 = rnorm(25, 11, 5)
> t.test(y1,y2, var.equal = TRUE, mu =0, conf.level = 0.90)

Two Sample t-test

data: y1 and y2
t = ? , df = ?, p-value = ?
alternative hypothesis: true difference in means is not equal to 0
90 percent confidence interval:
-3.6460449 0.2757534
sample estimates:
mean of x mean of y
9.154402 10.839548

What is the value of t (t_calc) in the above code?

A. -1.4387

B. 1.4387

C. 2.4387

D. -2.4387

Q2.

Previously we used

set.seed(24); y1 = rnorm(30, 10, 5)
set.seed(34); y2 = rnorm(25, 11, 5)

t.test(y1,y2, var.equal = TRUE, mu =0, conf.level = 0.90)

If the following code is run will the confidence interval be larger or smaller?

set.seed(24); y1 = rnorm(30, 10, 5)
set.seed(34); y2 = rnorm(25, 11, 5)

t.test(y1,y2, var.equal = TRUE, mu =0, conf.level = 0.95)

A. Smaller

B. Larger

Q3.

When conducting Hypothesis tests there are three errors that you can make (T/F)

Q4.

Paired samples are dependent (T/F)

Q5.

A large sample is often when n>=30 (T/F)

Q6.

The NULL hypothesis determines the tailness of the test (T/F)

Answer 1

What is the value of t (t_calc) in the above code?

A. -1.4387

Q2:

95 per cent confidence interval =( -4.0344842, 0.6641927) which is larger than the previous one.

Q3.

When conducting Hypothesis tests there are three errors that you can make (T/F)

No two errors type I and Type II error.

Q4.

Paired samples are dependent (T/F)

TRUE

Q5.

A large sample is often when n>=30 (T/F)

Yes, its the general concept or we can also say misconception. It depends on the underlying population.

Q6.

The NULL hypothesis determines the tailness of the test (T/F)

What is tailness? Its wrong question.