# Test Yourself

## True or False

#### Feedback

**False**

**A CI tells us something about sampl-ING variability, i.e, how much we'd expect the point estimate (eg; sample mean) to vary from sample to sample. It does not tell us about the variability of values in the sample, the sample standard deviation tells us this.**

#### Feedback

**False**

**The 97.5 ^{th} centile refers to individuals in the observed sample or the observed distribution of values, in contrast the 95% CI for the mean refers to the theoretical sampling distribution of the point estimate (eg; sample mean).**

#### Feedback

**True**

** **

#### Feedback

**False**

**This is an approximate 95% reference range (calculated as mean+/-1.96*SD). The 95% CI for a mean is calculated as mean +/- 1.96*standard error. The standard error for the mean in this example is equal to SD/√n = 0.1. So a 95% CI would be 9.8 to 10.2. Completely different!**

**State whether the following interpretations of a 95% CI are true or false.**

#### Feedback

**False**

**We are 100% confident of this; confidence intervals are built around the sample statistic or point estimate.**

#### Feedback

**False**

**Confidence intervals do not make inference about other samples; they make inference about populations.**

#### Feedback

**False**

**The population parameter is fixed, it is either in the CI or it is not, but we do not know. We’d expect to capture it 95% of the time if we did independent repeat samples and calculated a CI each time.**

#### Feedback

**False**

**The population parameter is fixed; so it is either 100% in the interval or 100% not.**

#### Feedback

**True**