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Statistics are everywhere, in every industry, but they're a must for anyone working in data science, business, or business analytics. If you're in one of these specialized fields, chances are you need an advanced understanding of statistics. Complete your mastery in this course, part four in our Statistics Foundations series. Eddie Davila covers concepts such as small sample sizes, t-distribution, degrees of freedom, and more. This advanced skills training moves learners into the practical study and application of experimental design, analysis of variance (ANOVA), two-population comparisons, and regression analysis. Use these lessons to go beyond the basics and dive deeper into the specific factors that influence your own calculations and results.

Statistics are a core skill for many careers. Basic stats are critical for making decisions, discoveries, investments, and even predictions. But sometimes you need to move beyond the basics. This third course in the Statistics Foundations series gives you practical, example-based lessons on the intermediate skills associated with statistics: Samples and sampling, standard errors, confidence intervals, and hypothesis testing. Eddie Davila takes a look at topics like sampling, random samples, sample sizes, sampling error, trustworthiness, the central unit theorem, confidence intervals, and hypothesis testing. This course is a must for those working in data science, business, and business analytics—or anyone who wants to go beyond means and medians and gain a deeper understanding of how statistics work in the real world.

Not sure if you need statistics? Think again! Statistics help with making decisions, new discoveries, investments, and predictions. For subjects ranging from political races to healthcare advancements, statistics can improve your understanding of your favorite topic. In this course, Professor Eddie Davila teaches common terms, formulas, and techniques related to probability, the area of statistics where this course focuses. Eddie explains that probability is used to make decisions about future outcomes and to understand past outcomes. He covers permutations, combinations, and percentiles, and goes into how to describe and calculate them. Eddie introduces multiple event probabilities and discusses when to add and subtract probabilities. He describes probability trees, Bayes’ Theorem, binomials, and so much more. You can learn to understand your data, prove theories, and save valuable resources—all by understanding the numbers.