Week 2: Populations and Sampling Techniques

Population

A collective term used to describe the set of all individuals of interest.

Population Size

Denoted by N; this also means population size.

Sample

A collective term used to describe a number of individuals chosen from the population.

Sample Size

Denoted by n; this also means sample size.

Census

An official enumeration of inhabitants, with details as to age, sex, pursuits, etc.

Census Data

Official data that has been collected with respect to a nation's human population.

Vital Statistics

All births and deaths during a defined period and is useful for determining population size.

Representative Sample

When the characteristic makeup of the sample is close to the characteristic makeup of the entire population.

Sampling Bias

A flawed sampling strategy in which an unrepresentative sample is obtained, due to the way in which data is sampled.

Non-Response Bias

When an unrepresentative sample results due to some sampled individuals not responding.

Simple Random Sampling

A sampling process where each member of the population is equally likely to be chosen in the sample.

Sampling without Replacement

Each member may only be selected once in a sample.

Factorials

K! Formula can be considered for calculating the number of different samples of size n that can result when simple random sampling without replacement is carried out.

Factorial Formula for Simple Random Sampling Calculations

N = 4; n = 3; N= 4x3x2x1 = 24; n = 3x2x1 = 6; F! = 4!/3!1! = 24/6x1 = 4.

Hidden Trump Supporters

Some of Trump's policies were seen as divisive, and some may be embarrassed to admit they voted for him.

Under-sampling of pro-Trump groups

Non-college educated people were under-sampled by the polls, who predominantly voted for Trump.

Clinton FBI Investigation

The FBI case into Clinton may have caused voters to switch allegiance and cast her in a negative light.

Implications of Sample Bias

Sample bias can misrepresent data conclusions.

Importance of Representative Sampling

It is pertinent for sampling to take place in a manner which minimizes the likelihood of an unrepresentative sample.

Survey Methodology

Explanation of survey methods and their application in practical scenarios.

Data Integrity

Discussion on the challenges of ensuring data integrity and accuracy in survey results.

Practical Examples

Examples include Australian census data interpretation and historical polling inaccuracies in political elections.

Critical Thinking in Survey Results

The importance of critical thinking in interpreting survey results.