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Sampling and Estimation

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.

Lessons

01

Simple Random Sampling and Sampling Distribution

Start
02

Sampling Error

Start
03

Stratified Random Sampling

Start
04

Time Series and Cross Sectional Data

Start
05

Central Limit Theorem

Start
06

Standard Error of the Sample Mean

Start
07

Parameter Estimation

Start
08

Point Estimates

Start
09

Confidence Interval Estimates

Start
10

Confidence Interval for a Population mean, with a known Population Variance

Start
11

Confidence Interval for a Population mean, with an Unknown Population Variance

Start
12

Confidence Interval for a Population Mean, when the Distribution is Non-normal

Start
13

Student’s t Distribution

Start
14

How to Read Student’s t Table

Start
15

Biases in Sampling

Start

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