Master Statistics: From Zero to Data Savy

This 84-lessons statistics course is structured to build your knowledge progressively-starting with the absolute basics and moving toward advanced topics. It covers everything from types of data and sampling techniques to inferential statistics and hypothesis testing. Each lecture is designed to simplify complex topics using real-life examples, Excel demonstrations, and clear visuals to help you not just understand statistics, but apply it with confidence.

15 reasons to take this course:Master the fundamentals of statistics, including key vocabulary, types of data, and essential sampling techniques used in real-world data collection. Learn how to organize and visually display data through frequency tables, histograms, box plots, polygons, and ogives, with practical Excel demonstrations to reinforce skills. Gain a solid understanding of central tendency (mean, median, mode) and variability measures (range, IQR, variance, standard deviation), including how to calculate and interpret them manually and in Excel.

Explore Z-scores, outliers, and the Empirical Rule to understand data distribution and identify unusual observations. Build foundational knowledge of probability theory, including OR, AND, and conditional probabilities, and work with contingency tables to evaluate event relationships. Dive into discrete probability distributions, including how to compute expected values and standard deviations, with a strong focus on binomial distributions and Excel applications.

Study continuous probability distributions, such as the uniform and normal distributions, and use Excel tools to calculate percentiles, Z-scores, and related probabilities. Understand and apply the Central Limit Theorem to sampling distributions for both means and proportions, enabling inference from sample data. Learn how to construct and interpret confidence intervals and grasp the logic and procedures behind hypothesis testing, including how to find critical values.