R E B O OT C O M PU T E R S E RVI C ES I N C . · C O L L E G E ST U DY S E R I ES
Statistics 101
The Complete Study Guide to Introductory Statistics
Formulas · Worked Examples · Practice Problems + Solutions
Inside this guide
1 · Data, Variables & Sampling
2 · Descriptive Statistics
3 · Probability Basics
4 · Distributions & the Normal Curve
5 · Sampling Distributions & the CLT
6 · Confidence Intervals
7 · Hypothesis Testing
8 · Master Formula Sheet
9 · Practice Problems with Solutions
10 · Glossary
A self-study companion for introductory statistics · rebootcs.com
, 1 · Data, Variables & Sampling
Statistics is the science of collecting, organizing, analyzing, and interpreting data to make decisions under uncertainty.
Descriptive statistics summarize data; inferential statistics draw conclusions about a population from a sample.
Key Vocabulary
A population is the entire group of interest; a sample is a subset actually studied. A parameter describes a population
(μ, σ); a statistic describes a sample (x̄, s).
Types of Variables
Type Description Example
Categorical (qualitative) Groups or labels eye color, major
Quantitative discrete Countable numbers number of siblings
Quantitative continuous Measurable, any value height, time
Sampling Methods
Simple random (every member equally likely), stratified (sample within subgroups), cluster, and systematic. Good
sampling avoids bias so the sample represents the population.
© Reboot Computer Services Inc. · Created by Mario Washington · Page 2 of 12
Statistics 101
The Complete Study Guide to Introductory Statistics
Formulas · Worked Examples · Practice Problems + Solutions
Inside this guide
1 · Data, Variables & Sampling
2 · Descriptive Statistics
3 · Probability Basics
4 · Distributions & the Normal Curve
5 · Sampling Distributions & the CLT
6 · Confidence Intervals
7 · Hypothesis Testing
8 · Master Formula Sheet
9 · Practice Problems with Solutions
10 · Glossary
A self-study companion for introductory statistics · rebootcs.com
, 1 · Data, Variables & Sampling
Statistics is the science of collecting, organizing, analyzing, and interpreting data to make decisions under uncertainty.
Descriptive statistics summarize data; inferential statistics draw conclusions about a population from a sample.
Key Vocabulary
A population is the entire group of interest; a sample is a subset actually studied. A parameter describes a population
(μ, σ); a statistic describes a sample (x̄, s).
Types of Variables
Type Description Example
Categorical (qualitative) Groups or labels eye color, major
Quantitative discrete Countable numbers number of siblings
Quantitative continuous Measurable, any value height, time
Sampling Methods
Simple random (every member equally likely), stratified (sample within subgroups), cluster, and systematic. Good
sampling avoids bias so the sample represents the population.
© Reboot Computer Services Inc. · Created by Mario Washington · Page 2 of 12
