Lessons
- Simple Random Sampling and Sampling Distribution
- Sampling Error
- Stratified Random Sampling
- Time Series and Cross Sectional Data
- Central Limit Theorem
- Standard Error of the Sample Mean
- Parameter Estimation
- Point Estimates
- Confidence Interval Estimates
- Confidence Interval for a Population mean, with a known Population Variance
- Confidence Interval for a Population mean, with an Unknown Population Variance
- Confidence Interval for a Population Mean, when the Distribution is Non-normal
- Student’s t Distribution
- How to Read Student’s t Table
- Biases in Sampling
Sampling Error
Sampling error is the difference between the sample statistics (such as sample mean) and the corresponding population parameter (such as population mean).
Sampling error occurs due to the random selection of the sample and can be reduced by increasing the size of the sample, or by ensuring that the sample more closely represents the population.
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