Batch 01: Arithmetic, Algebra & Mathematical Language / Data Foundations & Univariate Descriptive Statistics

by Synapticz Media

Oct 24, 2026

8 quizzes

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8 quizzes

Showing 1–8 of 8 quizzes · Page 1 of 1

Numbers, Fractions, Percentages & Units

Build practical confidence in numbers, fractions, percentages & units through 20 original single-select and multiselect questions. Prerequisites: Basic numerical literacy; no statistics prerequisite. Compute signed changes and fractions of quantities. Translate ratios, proportions and percentages. Distinguish absolute percentage-point changes from relative changes. Convert measurements and compare compatible units. Interpret rounding and significant figures. Diagnose changing bases and accumulated rounding. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openstax.org/books/college-algebra-2e/pages/1-1-real-numbers-algebra-essentials); [Reference 2](https://openstax.org/books/introductory-statistics-2e/pages/1-3-frequency-frequency-tables-and-levels-of-measurement). Photo by Kindel Media on Pexels.

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Algebra, Powers, Roots & Logarithms

Build practical confidence in algebra, powers, roots & logarithms through 20 original single-select and multiselect questions. Prerequisites: Fractions, percentages and units. Evaluate expressions and solve linear equations. Apply exponent rules and scientific notation. Interpret principal roots and rational powers. Use logarithm definitions, rules and domains. Solve inequalities and discrete feasibility constraints. Check transformed equations and interpret exponential change. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openstax.org/books/college-algebra-2e/pages/1-1-real-numbers-algebra-essentials); [Reference 2](https://openstax.org/books/college-algebra-2e/pages/1-2-exponents-and-scientific-notation); [Reference 3](https://openstax.org/books/college-algebra-2e/pages/1-3-radicals-and-rational-exponents); [Reference 4](https://openstax.org/books/college-algebra-2e/pages/6-5-logarithmic-properties). Photo by Monstera Production on Pexels.

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Functions, Graphs & Summation Notation

Build practical confidence in functions, graphs & summation notation through 20 original single-select and multiselect questions. Prerequisites: Elementary algebra, powers and logarithms. Read coordinates and interpret slopes with units. Evaluate functions and identify valid domains. Invert or compose functions with appropriate restrictions. Expand and transform finite indexed sums. Evaluate finite products and factorials. Reason about piecewise boundaries and limits of tabular inference. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openstax.org/books/college-algebra-2e/pages/3-1-functions-and-function-notation); [Reference 2](https://openstax.org/books/college-algebra-2e/pages/9-4-series-and-their-notations). Photo by Sergey Meshkov on Pexels.

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Sets, Logic & Reading Mathematical Claims

Build practical confidence in sets, logic & reading mathematical claims through 20 original single-select and multiselect questions. Prerequisites: Basic functions and mathematical notation. Distinguish membership, subset and set equality. Compute unions, intersections and complements. Translate quantifiers and their negations. Distinguish necessary, sufficient and equivalent conditions. Construct counterexamples and respect assumptions. Evaluate quantified claims including empty collections. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://discrete.openmathbooks.org/dmoi2/sec_intro-sets.html); [Reference 2](https://discrete.openmathbooks.org/dmoi2/sec_intro-statements.html); [Reference 3](https://discrete.openmathbooks.org/dmoi2/sec_quantifiers.html). Photo by DS stories on Pexels.

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Data Types & Stevens' Scales of Measurement

Build practical confidence in data types & stevens' scales of measurement through 15 original single-select and multiselect questions. Prerequisites: The arithmetic and mathematical-language bridge. Distinguish categorical variables from counts and measurements. Recognize nominal and ordinal scales. Interpret equal intervals and meaningful zero points. Separate numerical labels from quantitative values. Analyze recording resolution and coarsening. Evaluate permissible comparisons and construct interpretations. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openstax.org/books/introductory-statistics-2e/pages/1-3-frequency-frequency-tables-and-levels-of-measurement); [Reference 2](https://openintro-ims.netlify.app/data-hello). Photo by Ron Lach on Pexels.

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Populations, Samples & Sampling Methodologies

Build practical confidence in populations, samples & sampling methodologies through 20 original single-select and multiselect questions. Prerequisites: Data types and measurement scales. Distinguish target population, sampling frame and realized sample. Distinguish population parameters from sample statistics. Recognize simple random sampling and its limitations. Compare stratified, cluster and multistage designs. Diagnose systematic sampling periodicity. Identify mismatches between sampling and target units. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openintro-ims.netlify.app/data-design); [Reference 2](https://openstax.org/books/introductory-statistics-2e/pages/1-2-data-sampling-and-variation-in-data-and-sampling). Photo by Tima Miroshnichenko on Pexels.

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Sampling Biases, Observational Studies & Controlled Experiments

Build practical confidence in sampling biases, observational studies & controlled experiments through 20 original single-select and multiselect questions. Prerequisites: Population, sample and sampling-design vocabulary. Diagnose selection, voluntary response and nonresponse bias. Identify response and social desirability effects. Separate observation from randomized intervention. Recognize confounding and alternative explanations. Evaluate masking and placebo comparisons. Assess survivorship, attrition and limits of causal generalization. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openintro-ims.netlify.app/data-design); [Reference 2](https://openstax.org/books/introductory-statistics-2e/pages/1-4-experimental-design-and-ethics). Photo by Polina Tankilevitch on Pexels.

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Frequency Distributions, Binning & Contingency Tables

Build practical confidence in frequency distributions, binning & contingency tables through 20 original single-select and multiselect questions. Prerequisites: Data types, sampling and study-design basics. Interpret raw and relative frequencies with explicit denominators. Construct and invert cumulative frequencies. Check bin endpoints, widths and coverage. Read joint counts and marginal totals. Explain information loss and binning sensitivity. Audit rounding, missing responses and table consistency. Questions progress from basic recognition to application, interpretation and diagnostic challenges. Worked feedback explains the reasoning and the alternatives; no programming or calculus is needed. Further reading: [Reference 1](https://openstax.org/books/introductory-statistics-2e/pages/1-3-frequency-frequency-tables-and-levels-of-measurement); [Reference 2](https://openstax.org/books/introductory-statistics-2e/pages/2-2-histograms-frequency-polygons-and-time-series-graphs); [Reference 3](https://openintro-ims.netlify.app/explore-categorical). Photo by Artem Podrez on Pexels.

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