Free Download Hypothesis testing easily explained for everyone Part 1
Published 10/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 34m | Size: 344 MB
Part 1: DESCRIPTIVE STATISTICS
What you'll learn
Understand the background of descriptive statistics
Know how to calculate different measures of central tendency
Know how to calculate different measures of dispersion
Be able to recognise different variable types
Requirements
No prerequisites! Suitable for everyone
Description
Welcome to Part 1: Descriptive Statistics (the first in the series). This course provides an introduction to the fundamentals of descriptive statistics, designed for students with no prior experience in mathematics or statistics. By the end of the course, students will be well-prepared to advance to inferential statistics, which focuses on hypothesis testing and making predictions from data.In this course, students will explore the key concepts of descriptive statistics, including measures of central tendency (such as the mean, median, mode) and measures of dispersion (including range, variance, standard deviation and coefficient of variation), as well as an introduction to different data types (qualitative and quantitative) and scales of measurement. These concepts form the foundation for understanding and summarising data, helping students develop a clear grasp of statistical terminology and basic tools.The course is structured as the first part of a series aimed at building a strong foundation in statistics, making it accessible for learners without a mathematical or statistical background. It ensures that students are comfortable with the basics before advancing to more complex topics, such as hypothesis testing and other inferential methods. Upon completion, students will be well-equipped to progress to the next phase of their statistical education.
Who this course is for
For university students studying/requiring introductory statistics and for those looking to learn the basics of hypothesis testing before going on to further more advanced statistics
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