1. Jump to first page STATISTICAL INFERENCE Statistical Inference uses sample data and statistical procedures to: n Estimate population parameters; or n Test whether or not a population parameter is likely to satisfy some specified value.

2. Jump to first page STATISTICAL INFERENCE n Estimation of population parameters u The process of using a statistic to infer about the value of an unknown parameter with a specified level of certainty n Test whether a population parameter is likely to satisfy some specified value u The use of sample data to accept or to reject a statement about a parameter value or about a population distribution

3. Jump to first page Properties of Point Estimators n Bias describes the location of an estimator; n Efficiency is a measure of the amount of variation in the sampling distributions for alternative estimators of a parameter; n Consistency describes how the sampling distribution of an estimator concentrates around the parameter values as the sample size increases; and n Sufficiency is a measure of the use of information.

4. Jump to first page ESTIMATION The process of using a statistic to infer about the value of an unknown parameter with a specified level of certainty: n Large Sample 100(1 -  )% Confidence Interval for  ; n Small Sample 100(1 -  )% Confidence Interval for  ; and n Confidence Limit for 

5. Jump to first page Interval Estimation Procedure n Want to use X to estimate  X. n How reliable is a point estimate? n Develop a measure of reliability by finding an interval of numbers within which we expect the true value of the population mean to be contained. n Have  X, but do not know  X.

6. Jump to first page Interval Estimation Procedure n Large-Sample 100( 1 -  )% Confidence Interval for  X is X + Z  /2  X. n The interval X + 1.96  X is called a Large-Sample 95% Confidence Interval for the population mean.