Free online courseStatistics

Course Description

"Statistics" is an extensive and highly regarded online course that delves deeply into the fundamental principles of statistics. With a total duration of 12 hours and 44 minutes, this course offers a comprehensive yet concise exploration of various statistical concepts.

Designed for learners at the basic studies level, this course is categorized under Statistics and is well-suited for anyone seeking to build a solid foundation in this important field. The course has received excellent feedback, boasting an impressive average rating of 4.9 out of 5 stars, reflecting its quality and the satisfaction of those who have completed it.

The course begins with an introduction to descriptive statistics, focusing on measures such as the mean, variance, and standard deviation. These foundational elements are crucial for understanding data distribution and variability. Learners will gain insights into the differences between sample and population means, along with an in-depth discussion of sample variance and alternate variance formulas, which are essential for interpreting statistical data.

As the course progresses, it introduces the concept of random variables and dives into probability density functions. These subjects are key to mastering the principles of probability and statistical inference. The binomial distribution is comprehensively covered across several modules, providing learners with a thorough understanding of its properties and applications.

One of the highlights of the course is its exploration of the Poisson process, a fundamental topic in probability theory. The course also delves into the law of large numbers and the normal distribution, including practical exercises using Excel and insightful problems from ck12.org, which enhance the learner's quantitative and qualitative grasp of normal distributions.

Advanced topics such as the central limit theorem, sampling distributions, and the standard error of the mean are also thoroughly explored. These concepts are essential for performing accurate statistical inference and understanding the behavior of sample means.

The course doesn't shy away from challenging topics like hypothesis testing, confidence intervals, and margin of error calculations. It provides learners with practical examples and detailed explanations to build their proficiency in inferential statistics. The distinctions between Z-statistics and T-statistics are clarified, along with a thorough examination of type 1 errors and hypothesis testing for small samples.

Multiple modules are dedicated to regression analysis, explaining how to minimize squared error to the regression line, calculate R-squared, and understand covariance. The course also covers advanced statistical methods like the chi-square distribution and Pearson's chi-square test, which are critical for testing goodness of fit and independence.

Finally, the course concludes with an introduction to ANOVA (Analysis of Variance), providing detailed calculations and hypothesis testing using the F-statistic. The exploration of correlation and causality adds an important layer of understanding to statistical analysis, enabling learners to make informed decisions based on their data.

Overall, "Statistics" offers a structured and engaging learning experience that equips students with the necessary skills to excel in statistics. Whether you are a beginner or looking to solidify your knowledge, this course provides valuable insights into the world of statistics and its applications.