Statistics Task F

Author

Affiliation

Smit, A. J.

University of the Western Cape

1 Assessment Sheet

2 7. t-Tests

2.1 Question 1

Please report back on Task F.1 presented in the lecture. Write up formal Methods and Results sections. (/15)

2.2 Question 2

Please refer to the two-sided two-sample t-test in the lecture. It is recreated here:

# random normal data
set.seed(666)
r_two <- data.frame(dat = c(rnorm(n = 20, mean = 4, sd = 1),
                            rnorm(n = 20, mean = 5, sd = 1)),
                    sample = c(rep("A", 20), rep("B", 20)))

# perform t-test
# note how we set the `var.equal` argument to TRUE because we know 
# our data has the same SD (they are simulated as such!)
t.test(dat ~ sample, data = r_two, var.equal = TRUE)

R> 
R>  Two Sample t-test
R> 
R> data:  dat by sample
R> t = -1.9544, df = 38, p-value = 0.05805
R> alternative hypothesis: true difference in means between group A and group B is not equal to 0
R> 95 percent confidence interval:
R>  -1.51699175  0.02670136
R> sample estimates:
R> mean in group A mean in group B 
R>        4.001438        4.746584

1. Repeat this analyses using the Welch’s t.test(). (/5)
2. Repeat your analysis, above, using the even more old-fashioned Equation 4 in the lecture. Show the code, talk us through the step you followed to read the p-values off the table of t-statistics. (/10)

2.3 Question 3

Please report back on Task F.3 presented in the lecture. Write up formal Methods and Results sections. (/15)

2.4 Question 4

Please report back the analysis and results for Task F.4. in the lecture. Write up formal Methods and Results sections. (/15)