Applied Stats 📘 Chapter 1: Defining and Collecting Data

Categorical variable

qualitative variable like labels or categories

Nominal variable

defined categories with no order (e.g.

Ordinal variable

ordered categories (e.g.

Numerical variable

quantitative variable with number values

Discrete variable

arises from a counting process (e.g.

Continuous variable

arises from a measuring process (e.g.

Nominal scale

classifies data into distinct categories with no ranking

Ordinal scale

classifies data into categories with implied rankings

Interval scale

ordered scale with meaningful differences but no true zero

Ratio scale

ordered scale with meaningful differences and a true zero

Population parameter

summarizes a variable for the entire population

Sample statistic

summarizes a variable for a sample

Primary source

data collected firsthand by the researcher

Secondary source

data obtained from another source

Sampling frame

list of items that make up the population

Frame

the source used to define the population list

Non-probability sample

sample based on judgment or convenience

Convenience sampling

selecting items that are easy or inexpensive to sample

Judgment sampling

selecting based on expert opinion

Probability sample

sample where each item has a known chance of selection

Simple random sample

each item has equal chance of selection

Stratified sample

population divided into subgroups and sampled randomly

Systematic sample

selecting every kth item from a list

Cluster sample

dividing population into clusters and randomly selecting clusters