CHAPTER 9 : Estimation and Confidence Intervals

CHAPTER 9 : Estimation and Confidence Intervals

1. SAMPLING

   • contact the entire population is too time consuming
   • The cost of studying all the items in the population is often too expensive
   • The sample results are usually adequate
   • Certain tests are destructive
   • Checking all the items is physically impossible

2. Point Estimate

   • a single value (point) derived from a sample and used to estimate a population value.

3. Confidence interval estimate

   • a range of values constructed from sample data so that the population parameter is likely to occur within that range at a specified probability
   • Factor for determine the width of confidence interval
     • sample size
     • variability in the population
     • level of confidence

4. Point Estimates and Confidence Intervals for a Mean – σ Known

   • The width of the interval is determined by the level of confidence and the size of the standard error of the mean.
   • The width of the interval is determined by the level of confidence and the size of the standard error of the mean.
   • The standard error is affected by two values:
     • Standard deviation
     • Number of observations in the sample

5. CHARACTERISTICS OF THE t-Distribution

   • a continuous distribution
   • Bell-shaped and symmetrical.
   • Not one t distribution, but rather a family of t distributions
   • The t distribution is more spread out and flatter at the center than the standard normal distribution
   • t-distribution
   • Z-distribution

6. A Confidence Interval for a Proportion (π)

   • To develop a confidence interval for a proportion

7. Selecting an Appropriate Sample Size

   • The level of confidence desired.
   • The margin of error the researcher will tolerate.
   • The variation in the population being Studied.

8. Finite-Population Correction(FPC) Factor

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