Sampling distributions, Standard Error, Confidence Interval - Week Four

Question 1

Define population and sample

Answer 1

Population = Contains all the elements / members of a data set
Sample = Subset of 1+ observation drawn from the population

Question 2

Three sample statistics

Answer 2

M
S^2
S(SD)

Question 3

Which letters represent population mean, population variance, and population SD

Answer 3

μ = population mean
σ = population SD
σ^2 = population variance

Question 4

Accuracy of sample sizes

Answer 4

Multiple samples of same size differ in means
Represents individual sample mean not score
Narrow sampling = more accurate (larger N , lower σ )

Question 5

How is variability in distribution always measured?

Answer 5

Through standard deviation

Question 6

What does standard error depend on, and what is the equation?

Answer 6

Depends of 1/4 of SD of measured characteristic in pop.
We can estimate σ using SD

SE = SD / √N

Question 7

Define confidence intervals
What is a 95% error interval

Answer 7

The mean of your estimate +/- variation of estimate
95% CI [M - 1.96 x SE , M + 1.96 x SE]

95% of sample means are within 1.96 SD of sampling distribution

Question 8

Is a larger CI or narrower CI more appropriate?

Answer 8

Narrower = Larger N = Smaller SE
Overlapping may produce dissimilarity