Free online courseStatistics

Course Description

The course "Statistics by" is an extensive exploration into the fundamentals of statistics, designed for those who are just starting their journey into this crucial field. With a duration of 31 hours and 55 minutes, it's a substantial commitment that promises a thorough grounding in the subject.

Belonging to the "Basic Studies" category and diving into the subcategory of statistics, this course has received a remarkable average rating of 4.9 out of 5 stars, reflecting its high-quality content and the effectiveness of its instruction. Guided by a seasoned educator in the field, students can expect a comprehensive and engaging learning experience.

The course begins with an introduction to elementary statistical terms and definitions, ensuring that students are equipped with the foundational vocabulary necessary for more advanced topics. As learners progress, they explore various categories and levels of data measurement, followed by essential sampling techniques to develop random samples efficiently.

One of the core areas covered is the creation of frequency distributions and histograms, providing students the tools to organize and visualize data effectively. This is complemented by lessons on finding the center of a data set through mean, median, and mode, and calculating the standard deviation, which is crucial for understanding data variability.

The course delves deeply into probability, starting with introductory concepts and advancing through the addition and multiplication rules for probability, probability of complementary events, and the fundamental counting principle. Students will also learn about permutations and combinations, broadening their understanding of different probability scenarios.

Probability distributions are another focal point, where learners study both general and binomial distributions, and how to find their mean and standard deviation. This is crucial for interpreting and predicting data patterns.

In the sections covering the normal distribution and continuous random variables, students are introduced to the standard normal distribution and z-scores, which are pivotal for statistical inference. The course explains sampling distributions and the Central Limit Theorem, leveraging these concepts to approximate population characteristics from samples.

Confidence intervals are meticulously covered, including for population proportions and sample means, whether the population standard deviation is known or not. This segment is vital for making reliable population parameter estimates from sample data.

Finally, the course wraps up with hypothesis testing, a cornerstone of statistical analysis. From testing population proportions and means to examining variances and standard deviations, students gain robust skills in making data-driven decisions.

Overall, "Statistics by" offers a rich tapestry of statistical education, meticulously structured to build a solid foundation and advance learners' understanding through practical, real-world applications. Whether you're a beginner in statistics or looking to reinforce your knowledge, this course stands out as a highly recommended resource.