Session 7a - comparing independent means

Question 1

t-distribution is…

Answer 1

Used to compare a continuous variable in 2 groups (the groups are treated as a binary categorical variable)
A set of normal distributions - for mean group differences
Defined by degrees of freedom

Question 2

df for t-distribution

Answer 2

Total sample size minus number of groups
n-2
(if not independent groups, df=n-1)

Question 3

critical t-score is

Answer 3

Compared to observed t-value
The cut off values for different proportions of the population - can use for 95%, 99% significance etc

Question 4

Standard Error of the Mean is

Answer 4

an estimator of the population standard deviation
measure of uncertainty around the mean

Question 5

Standard Error of the Mean (se) is affected by

Answer 5

Size and Variability of a sample

Question 6

Degrees of freedom for t-distribution calculation

Answer 6

Total sample size minus number of groups

Question 7

Confidence Intervals (CIs)

Answer 7

CI for a statistic - range that is likely to contain the statistic for that population
Standard = 95% CI

Question 8

Calculation of CI

Answer 8

mean ± critical statistic (e.g. critical t) * standard error of the
mean

Question 9

Confidence limits =

Answer 9

Values that state the boundaries of the confidence interval

Question 10

The mean difference can be assumed to be statistically significant

Answer 10

If the interval excludes 0

Question 11

Confidence intervals can be displayed graphically for group differences by…

Answer 11

Whiskers - NOT box-plot
Overlapping CIs suggests non significant test results

Question 12

Independent sample t-test assumptions

Answer 12

Observations are independent
Observations come from normal distributions
Distributions have equal variance (Levene’s)

Question 13

Levene’s test for equality of variance

Answer 13

H0 is that the groups are equal variance
If p<0.05, variances are different and therefore need adjusting for - read from ‘equal variances not assumed’ row