Learn The Core Stats For A Data Science Career. Master Statistical Significance, Confidence Intervals And Much More!
InstructorKirill EremenkoLessons utilize drawings and dynamic explanations rather than static slides to illustrate core concepts.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This educational slide defines statistical distributions by contrasting discrete data, shown as a histogram of age groups, with continuous data, illustrated by a smooth probability density curve.
This statistics slide illustrates a sampling distribution with parameters n=100, mu=95.70, and sigma=124.70, highlighting three regions with probabilities of 22.06%, 57.89%, and 20.05%.
This slide illustrates statistical significance by comparing p-values against an alpha threshold of 0.05 using a fair coin hypothesis test.
This educational slide illustrates the Central Limit Theorem by showing how sampling distributions of means converge toward a normal bell curve regardless of the original population distribution.
The curriculum includes specific analytics challenges, homework assignments, and corresponding solution videos.
The content is described as basic and short, lacking depth in areas like error types or advanced statistical theory.
One signal suggests a lack of in-depth detail and preparation compared to previous instructional work.
The curriculum aligns well with the goal of learning statistics from the ground up for business contexts.
