Module 4

Question 1

inferential statistics

Answer 1

use a sample’s statistics to esitmate population statistics (parameters)

parameter is an idea more than something concrete that you can access

Question 2

population parameteres

Answer 2

CAN’T ever access them, you can only conceive of them in your mind through inferential statistics

make inferences about everyone

Question 3

estimating a population SD and mean

Answer 3

samples have SDs and means, we can use those samples drawn from a larger population

our best guess for the population mean is using the sample mean from that population

Question 4

sampling error

Answer 4

different random samples from the same population produce different sample means - this is sampling error

sample means are UNBIASED because they are normally distributed

Question 5

estimating a population standard deviation (standard error)

Answer 5

sample SD is biased and it underestimates the population SD

so we use this equation with (n-1) to account for

Question 6

degrees of freedom

Answer 6

Question 7

sampling distribution of the means

Answer 7

the mean of the distribution of the means

Question 8

standard error of the mean

Answer 8

the standard deviation of the sampling distribution of means

Question 9

central limit theorem

Answer 9

1. the mean of the distribution of means is equal to the mean of the population
2. a population has a standard deviation called the standard error - the standard error is always less than standard deviation as long as N > 1
3. the sampling distribution is approxiamtely normal
4. each sample has a different sampling distribution
5. larger samples ivolve less sampling error