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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)This text is disseminated via the Open Education Resource (OER) LibreTexts Project (https://LibreTexts.org) and like the thousands of other texts available within this powerful platform, it is freely available for reading, printing, and "consuming."
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This text was compiled on 01/11/2026
Required Course Learning Outcomes
- Communicate the language of statistics using the appropriate terminology.
- Analyze numerical summaries and graphical displays of sample data.
- Analyze bivariate data by applying the concepts of correlation and regression.
- Apply the basic rules of probability.
- Utilize the appropriate probability distribution.
- Make inferences about one or more populations using sample data.
- Utilize technology to further statistical understanding and reasoning.
Recommended Topical Outline
I. The Language and Terminology of Statistics
- A. Introduction to experimental vs observational studies
- B. Introduction to qualitative vs quantitative studies
- C. Introduction to the research process
- D. Introduction to sources of bias
- E. Population vs samples
- F. Parameters vs statistics
- G. Types of data (discrete/continuous, quantitative/qualitative)
- H. Types of variables (lurking, confounding, explanatory, response)
- I. Sampling techniques (random, systematic, stratified, cluster, convenience)
- J. Relevance of statistics to scientific and other real-world problems
II. Numerical Summaries and Graphical Displays of Sample Data
- A. Frequency distribution tables including construction
- B. Graphical displays of qualitative and quantitative data including construction
- C. Distribution shapes (modality and skew)
- D. Measures of central tendency (including calculations with or without technology)
- E. Measures of variation (including calculations with or without technology)
- F. Measures of relative position (including calculations with or without technology)
III. Bivariate Data: Correlation and Regression
- A. Scatter plots including construction
- B. Correlation including calculations with or without technology
- C. Linear regression
- D. Analysis of residuals
IV. Fundamentals of Probability
- A. Law of Large Numbers
- B. Addition and multiplication rules
- C. Introduction to permutations and combinations
- D. Complementary events
- E. Conditional probability
V. Probability Distributions
- A. Introduction to discrete probability distributions
- B. Binomial distributions
- C. Normal distributions
VI. Inference for One or More Populations Using Sample Data
- A. The Central Limit Theorem
- B. Sample size for mean and proportion
- C. Confidence intervals for one and two populations
- D. Hypothesis tests for one and two populations
- E. Chi-square and goodness-of-fit tests
- F. Introduction to Analysis of Variance (ANOVA)
VII. Technology to Further Statistical Understanding and Reasoning
Course Alignment Reference Table
This table shows how each chapter in the textbook supports our course objectives and learning outcomes. Use this to reflect on your progress and see how each skill builds toward the full understanding of statistical reasoning with real-world data.
| Textbook Chapter | Primary Course Learning Outcomes (CLOs) | Relevant Topical Outline Elements (TOs) |
|---|---|---|
| 1. Introduction to Data | CLO 1, CLO 6 | I.A – I.J, I.E, I.F, I.G, I.I |
| 2. Exploring and Summarizing Data | CLO 2, CLO 7 | II.A – II.F |
| 3. Visualizing Data | CLO 2, CLO 7 | II.A – II.C |
| 4. Introduction to Probability | CLO 4, CLO 7 | IV.A – IV.E |
| 5. Probability Distributions | CLO 5, CLO 6, CLO 7 | V.A – V.C |
| 6. Sampling Distributions | CLO 6, CLO 7 | VI.A |
| 7. Confidence Intervals | CLO 6, CLO 7 | VI.B – VI.C |
| 8. Hypothesis Testing | CLO 6, CLO 7 | VI.D, VI.E, VI.F |
| 9. Correlation and Regression | CLO 3, CLO 7 | III.A – III.D |
| 10. Appendix and Tables | CLO 7 (supporting) | All through VII |
Legend
- CLO = Course Learning Outcome (Official campus-level outcome)
- TO = Topical Outline Objective (Recommended content coverage by section)
To see the full list of CLOs and outline objectives, refer to the course syllabus or the section below.


