Vista Academy • Data Analytics
Inferential Statistics
Learn how statisticians use sample data to understand populations, estimate unknown values, measure uncertainty, and make evidence-based statistical decisions.
What You Will Learn
Inferential statistics is about going beyond the data you directly observe. Instead of only describing a sample, you learn how to use sample evidence to estimate population characteristics and evaluate statistical claims.
Throughout this course, you will work with concepts such as sampling, sampling distributions, the Central Limit Theorem, confidence intervals, hypothesis testing, p-values, t-tests, chi-square tests, and ANOVA.
Sampling
Learn how samples are selected and why sampling matters when studying large populations.
Estimation
Learn how sample statistics can estimate unknown population parameters.
Confidence Intervals
Understand how statistical intervals communicate uncertainty in estimates.
Hypothesis Testing
Learn how statistical evidence is used to evaluate hypotheses.
Statistical Tests
Work with t-tests, chi-square tests, and ANOVA.
Data Analytics
Apply statistical concepts to realistic data analytics problems.
Course Curriculum
Each lesson will combine explanation, worked examples, interactive questions, calculations, and practical statistical scenarios.
Learn Through Practice
This course will not be just a collection of statistical definitions. Lessons will explain the idea first and then let you apply it through interactive questions.
Understand
Learn the concept with simple explanations.
Calculate
Work through statistical calculations.
Practice
Test your understanding with interactive questions.
Apply
Use statistics on realistic data analytics problems.