1. Estimation Point Estimates Industrial Engineering

2. Overview Point versus interval estimates
Estimators of a population mean
Estimators of a population proportion
Estimators of a population variance
Estimating other parameters
Method of Moments
Maximum Likelihood Estimates

3. Statistics Descriptive Statistics
is used to summarize a collection of data in a clear and understandable way.
Ex: Histograms, box plots, stem and leaf plots.
Inferential Statistics
are used to draw inferences about a population from a sample.
Ex: 10 subjects perform a task after 3 hours of training. They score 12 points higher than 10 subjects who perform the same task with no training. Is the difference real or could it be due to chance?

4. Point Estimators
Suppose we have a new type of light bulb and we wish to test the bulbs for mean time to burn out.

5. Point Estimators
We select 10 bulbs at random and test to burn out.

6. Point Estimators å = n i x X 1 10
1462 .
1483
1569 + =
= 1,596.2

7. Point Estimators = X 1,596.2 Is called a point estimator
of the true but unknown
mean m.

8. Point Estimators
Suppose we now select a new sample of ten bulbs.

9. Point Estimators X 10
1571 .
1567
1739 + =
= 1,603.0

10. Point Estimators Different samples yield different point estimates ofX 10
1571 .
1567
1739 + =
= 1,603.0
Different samples yield
different point estimates of
the population mean.