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Chapter 10

# MGMT 1050 Chapter Notes - Chapter 10: Bias Of An Estimator, Confidence Interval, Point Estimation

Department
Management
Course Code
MGMT 1050
Professor
Olga Kraminer
Chapter
10

This preview shows page 1. to view the full 4 pages of the document. Chapter 10
What is Statistical Inference and Estimation?
Statistical inference is finding information about a population by using information from a
sample. It includes estimation and hypothesis testing.
Inference generally involves one of two tasks:
1. Providing an estimate of a parameter, with the appropriate confidence interval or
2. Testing to see if there is statistical evidence that an estimated statistic is similar to or
different from an hypothesized value
2 Aspects of Inference:
Estimation: deriving estimates with their associated confidence intervals
Hypothesis testing: drawing conclusions based on the probability that statements are
correct
Almost all estimation problems involve the same basic structure:
- creating a confidence level around the point estimate
The size of the interval is determined by:
- standard error of the estimated parameter value (standard deviation and sample
size)
- distribution of the estimate (confidence level)
Almost all hypothesis testing involve the same basic steps
- determining the null and alternate hypothesis, the test statistic, and the rejection
region
The test statistic is based on:
- the standard error of the estimated parameter value (standard deviation and sample
size)
The rejection region is determined by:
- distribution of the estimate (confidence interval)
Estimation is trying to determine the value of a population parameter based on the value of
a statistic
Types of Estimators
- point estimators
- interval estimators
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