Sampling methods

Qualitative data (Categorical data)

Data that are in words

Quantitative data

Data that are in numbers

Age

Quantitative data

Colours

Qualitative data

Height

Quantitative data

Ordinal data

Qualitative data that can put into order(eg. alphabetical)

Discrete Data

Numerical data values that can be COUNTED

Continuous data

Data that can take any value within a range.

Simple Random Sampling

Researchers select a random group of people from a popuation

Systematic Sampling

Researchers select members of the population at a regular interval

Cluster sampling

The researcher divides people into groups then picks random groups then picks random samples from the random groups they chose

Quota Sampling

A researcher separates population into different groups then CONVENIENTLY selects people out of the group

Stratified Random Sampling

The researcher separates the population into different groups, strata and RANDOMLY selects a few out of the groups.

Randomly pick out 15 names out of the hat

Simple random sampling

A researcher selects every 10th person that enters the mall

Systematic Sampling

A student surveys their grade to find out how much people spend on homework per day

Convenience sampling

A person chooses to sample random grade groups from the whole UWC

Cluster sampling

Separate people by grades then pick the first 5 on the list from each group

Quota sampling

divide a sample of adults into subgroups by age, below 18, 18-29, 30-39, 40-49, 50-59, and 60 and above, the researcher numbers them and picks a random number

Stratified random sampling

p-value

a number describing how likely it is that your data would have occurred by random chance. Represents the strength of correlation

p-value less than 0.05

The data has strong correlation. Statistically Significant.

p-value more than 0.05

Data does not have a strong correlation. Not statistically significant