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Sampling and Estimation

15 chapters · 1 files

In the real world, it is often not possible to collect data about an entire population to conduct a statistical analysis. For example, to make conclusions about the saving habits of families in a city, it would be impractical to collect and analyse savings data about each and every family in the city. Instead, a small group of families, called a sample, can be used to represent the entire population. We can then use this sample to perform our statistical analysis and estimate parameters for the population. These parameters will however only be estimates of the actual parameters of the population.

Learn about how to obtain sample data and use the sample to estimate parameters of the population.

Chapters

  1. 1Simple Random Sampling and Sampling DistributionRead free
  2. 2Sampling ErrorRead free
  3. 3Stratified Random SamplingRead free
  4. 4Time Series and Cross Sectional DataRead free
  5. 5Central Limit TheoremRead free
  6. 6Standard Error of the Sample MeanRead free
  7. 7Parameter EstimationRead free
  8. 8Point EstimatesRead free
  9. 9Confidence Interval EstimatesRead free
  10. 10Confidence Interval for a Population mean, with a known Population VarianceRead free
  11. 11Confidence Interval for a Population mean, with an Unknown Population VarianceRead free
  12. 12Confidence Interval for a Population Mean, when the Distribution is Non-normalRead free
  13. 13Student’s t DistributionRead free
  14. 14How to Read Student’s t TableRead free
  15. 15Biases in SamplingRead free

Practice quizzes

Files

  • Sampling and Estimation

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