Caveat Academy course · Grades 8 to 12

Data Science Fundamentals: from a question to evidence

Learn the whole cycle data scientists use: write a question data can answer, spot a biased sample, clean a messy spreadsheet with a change log, find the median, quartiles and outliers, catch a chart with a cut-off axis, fit a line and read its residuals, simulate a free-throw streak and test a prediction model fairly. Six modules at your own pace, ending with a project on public data.

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$19one-time · every device you sign in on
Buy · $19

Included with the Caveat Academy pass and Whole-school licenses. Or get it in the High school electives library, $119 for 66 items.

6 modules · 18 lessonsabout 13 hours$19

Six modules, eighteen lessons

Each module ends with a practice set that tracks mastery, an explain-it-back prompt, a short written response and a module exam. The final opens when every module is proficient; passing it earns a certificate with a verification code.

  1. Module 1: What data science is

    Explain the data science cycle, classify variables by type and evaluate samples and study designs for bias and for what they can show.

    • The data science cycle
    • Cases, variables and types of data
    • Samples, bias and study design
    about 2.1 h

  2. Module 2: Spreadsheets and clean data

    Use spreadsheet formulas with relative and absolute references, clean messy data with a change log, and sort, filter and group data.

    • Working in a spreadsheet
    • Cleaning messy data
    • Sorting, filtering and grouping
    about 2.1 h

  3. Module 3: Describing data with numbers

    Compute the mean, median, mode, range, quartiles, IQR and standard deviation, and describe distributions and outliers.

    • Center: mean, median and mode
    • Spread: range, IQR and standard deviation
    • Shapes of distributions
    about 2.2 h

  4. Module 4: Visualizing data

    Choose a chart that fits the question, detect misleading charts and design a clear, honest chart for an audience.

    • Choosing the right chart
    • Honest and misleading charts
    • Telling a story with data
    about 2.1 h

  5. Module 5: Relationships, models and chance

    Interpret correlation and lines of best fit, compute predictions and residuals, and estimate probabilities by simulation.

    • Scatter plots and correlation
    • Lines of best fit and prediction
    • Probability and simulation
    about 2.1 h

  6. Module 6: Data science in the world

    Explain how prediction models are trained and tested, evaluate privacy and fairness risks and plan a reproducible data project.

    • Prediction models that learn from examples
    • Privacy, fairness and ethics
    • A data project from start to finish
    about 2.1 h

Try it before you start

This is how every lesson works: step through a worked example at your own pace, then answer a check and get the reason right away. Nothing here is saved; the course keeps your progress.

Module 5 · Lines of best fit and prediction

Worked example: hours of study and test score

  1. A class's data give the line: predicted score = 52 + 4.5 × hours.

A lesson check from each module

The checks need JavaScript turned on. The course itself works the same way.

What you get

Academics · High SchoolAlso for Enrichment · STEM Explorations$19 · included with the Academy pass and Whole-school licenses

What you finish with
A finished introduction to data science: you can take a question through the full cycle, classify variables, judge samples and study designs for bias, work a spreadsheet with relative and absolute references, clean messy data and log every change, sort, filter and group, compute and interpret center, spread and the five-number summary, flag outliers, choose honest charts and redesign misleading ones, read correlation and lines of best fit, compute predictions and residuals, estimate probabilities by simulation, explain how prediction models are trained and tested, weigh privacy and fairness, and plan a reproducible project. Passing the final earns a Caveat certificate of completion.
Who it is for
Students in grades 8 to 12 curious about data, statistics or computer science, students taking or about to take a data science or statistics elective, and homeschool families who want a practical math course built on real data. Younger or newer students can take it as the Introduction to Data Science enrichment course. A free spreadsheet program is all the software it needs.
Format
An online self-paced course: 6 modules and 18 lessons with worked examples you reveal step by step, 145 practice and exam items (multiple choice, numeric, fill-in and ordering), an explain-it-back prompt and a rubric-checked short response in every module, module exams with one retake, a 24-question final and a certificate with a verification code. About 13 hours in all; works on a phone or a computer.
Access
$19 one-time, yours on every device you sign in on; the course opens once you are signed in with it. Included with the Caveat Academy pass and Whole-school licenses. Also in the High school electives library ($119) and the Academics Suite pass ($149), and 1 more bundle. Progress is saved in this browser on this device, and the certificate page lets you download your record.
Where it lives
The High School space in Caveat Academics; also listed for the STEM Explorations space in Caveat Enrichment (the same course serves the Introduction to Data Science enrichment title).
Support
Access, a receipt, a refund or a correction to the course: team@caveatacademic.com.

How it works

  1. Open the course and start Module 1. Each lesson takes about 25 to 35 minutes; two or three a week finishes the course in about a semester.
  2. Answer the checks as you read. Every answer shows the reason, and a miss links you back to the lesson that covers it.
  3. Finish each module with its practice set and exam. Proficient on every module opens the final; 70 percent passes it.
  4. Print or download your certificate and record from the certificate page.

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Sources and accuracy

The lessons are original writing by Caveat Academic Services. Facts were checked against these free, open references, which are also good places to read further.

  1. OpenStax, Introductory Statistics 2e, on sampling, descriptive statistics, regression and probability, a free textbook: openstax.org
  2. American Statistical Association, GAISE II guidelines for statistics and data science education in grades pre-K to 12: amstat.org
  3. U.S. Census Bureau, Statistics in Schools, free activities and public data: census.gov
  4. National Eye Institute, on how common color vision deficiency is: nei.nih.gov
  5. U.S. Department of Health and Human Services, guidance on de-identifying data and re-identification risk: hhs.gov

Data Science Fundamentals is a self-paced course from Caveat Academic Services. It follows the sequence of a typical introductory data science course but does not replace a school course and awards no credit. Example data in the lessons are made up for teaching and labeled as examples. Never collect personal data from other people without their permission. Support: team@caveatacademic.com.