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Chapter 10

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

by OC295907

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**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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