Overview of Sampling Methods and Data Types

Stratified Sampling

Population divided into homogeneous subgroups (strata); random samples taken from each.

Random Sampling

Every individual has an equal chance of selection.

Systematic Sampling

Select every kth unit after a random start.

Cluster Sampling

Divide population into heterogeneous groups (clusters), then randomly select clusters.

Measurement Error

Wrong/inaccurate answers due to misunderstanding, misreporting, etc.

Non-Response Bias

Certain groups don't respond, skewing results.

Selection Bias

Sample isn't representative due to how it was chosen.

Processing Error

Mistakes during data entry or analysis.

Nominal Data

Eye color, nationality, blood type.

Ordinal Data

Movie ratings, education levels, satisfaction scores.

Interval Data

IQ scores, time (5:00pm), Celsius temperature.

Ratio Data

Speed, income, volts, volume, reaction time, distance.

Descriptive Statistics

Summarizes or describes data.

Inferential Statistics

Makes predictions or generalizations about a population.

Nonparametric Statistics

Used with nominal/ordinal data; no assumptions about population distribution.

Excel Function for Simulating Dice Rolls

Roll an 8-sided die → =RANDBETWEEN(1,8)