YALE S&DS; 1000
Introductory Statistics
Complete Study Guide | 2026-2027
Statistical reasoning, data analysis, probability, inference, regression, ANOVA, and
introductory R.
Independent Study Resource
Not affiliated with or endorsed by Yale University.
,How to Use This Guide
Read the explanation first, then try the practice prompts without looking back. For quick revision, focus on the
distinctions, assumptions, and interpretation rules.
Course alignment
This guide is broadly aligned with Yale's 2026-2027 S&DS; 1000 description, including statistical reasoning, data
summaries, study design, probability, confidence intervals, hypothesis testing, correlation, regression, multiple
regression, ANOVA, applications, and introductory R.
The material is independently written and does not reproduce Yale lectures, assignments, exams, answer keys, or
textbook passages.
, Chapter 1 - Statistical Thinking
Population and sample, parameter and statistic, descriptive versus inferential statistics, and how to frame a statistical
question.
Key points
• Identify the population, sample, variables, and target question.
• Choose a method that matches the data and study design.
• Check assumptions before interpreting a result.
• State numerical results in plain language and in context.
Practice
1. Define the main idea in your own words.
2. Give a simple real-world example.
3. Name one common mistake and explain how to avoid it.
4. Write one exam-style question and solve it.
Introductory Statistics
Complete Study Guide | 2026-2027
Statistical reasoning, data analysis, probability, inference, regression, ANOVA, and
introductory R.
Independent Study Resource
Not affiliated with or endorsed by Yale University.
,How to Use This Guide
Read the explanation first, then try the practice prompts without looking back. For quick revision, focus on the
distinctions, assumptions, and interpretation rules.
Course alignment
This guide is broadly aligned with Yale's 2026-2027 S&DS; 1000 description, including statistical reasoning, data
summaries, study design, probability, confidence intervals, hypothesis testing, correlation, regression, multiple
regression, ANOVA, applications, and introductory R.
The material is independently written and does not reproduce Yale lectures, assignments, exams, answer keys, or
textbook passages.
, Chapter 1 - Statistical Thinking
Population and sample, parameter and statistic, descriptive versus inferential statistics, and how to frame a statistical
question.
Key points
• Identify the population, sample, variables, and target question.
• Choose a method that matches the data and study design.
• Check assumptions before interpreting a result.
• State numerical results in plain language and in context.
Practice
1. Define the main idea in your own words.
2. Give a simple real-world example.
3. Name one common mistake and explain how to avoid it.
4. Write one exam-style question and solve it.
