Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis
Instructor365 CareersThe curriculum includes dedicated sections for practical examples following major theoretical blocks in descriptive and inferential statistics.
Frequent quizzes are interspersed throughout the lectures to verify understanding of specific topics like skewness and the central limit theorem.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This slide illustrates hypothesis testing for grades in a UK university using a normal distribution curve, showing null and alternative hypotheses alongside defined rejection regions.
The presenter introduces the core curriculum pillars, listing descriptive statistics, inferential statistics, and regression analysis as key areas of study.
The presenter highlights the comprehensive learning materials included in the course, such as four case studies, exercise workbooks, quiz questions, course notes, and supplemental resources.
The instructor introduces the use of Microsoft Excel 2016 as a practical tool for performing statistical analysis within the data science curriculum.
Explanations vary; some lectures skip basic definitions or fail to explain the mathematical logic behind specific formulas.
Some exercises and quizzes lack sufficient context, requiring learners to backtrack through videos to find necessary datasets or formulas.
The course aligns well with its target of beginner data professionals, though some learners find it requires more prerequisite knowledge like Excel proficiency.
