Lecture 8: Parameter Estimation, Sampling Distribution, & Standard Error of the Mean

Question 1

What is a parameter?

Answer 1

A parameter is a CHARACTERISTICS of the POPULATION that we ESTIMATE using a STATISTIC from the SAMPLE

Question 2

Sample statistic letter for mean and standard deviation

Answer 2

Mean: M
Standard deviation: s or SD

Question 3

The parameter being estimated by that sample statistic/Population mean and standard deviation letter

Answer 3

Mean: MEW
Standard Deviation: SIGMA

Question 4

What is the sample mean? (M)

Answer 4

It is an unbiased estimate of the population mean (MEW)

Question 5

Sampling Distribution of the Mean

Answer 5

1) millions of different samples collected
2) List of means from all those samples is the Sampling distribution of the mean

Question 6

What is the standard error of the mean (SEM)

Answer 6

The computed standard deviation for the millions of different samples using the sampling distribution of the mean

Question 7

What is the Estimated Standard Error of the Mean

Answer 7

The sample standard deviation (s)/square root of the sample size

Question 8

What does the standard error of the mean do?

Answer 8

quantifies uncertainty in the estimation of MEW/ population mean

Question 9

Why is the standard deviation in the numerator and the sample size in the denominator?

Answer 9

Uncertainty is lower when the sample size is larger and higher when variability in the sample is larger

Question 10

What does the sample standard deviation (s) tell us?

Answer 10

How much the values in the sample vary (dispersion)

Question 11

What does the standard error of the mean (SEM) tell us?

Answer 11

1. How the sample mean (M) varies between different samples
2. The amount of uncertainty in our estimation of the population mean (MEW)