Beginner's Guide to Statistics for Data Analysis

Beginner's Guide to Statistics for Data Analysis

Key Points Statistics is the science of collecting, analyzing, interpreting, and presenting data, and it can be used to solve many real-world problems and situations. There are two main types of statistics, descriptive and inferential , and they have different purposes and methods. Many methods and techniques can be applied to data types and research questions or problems, such as t-test, ANOVA, regression, correlation, and chi-square. Many tools, such as R, Python, and Excel, can be used to perform data analysis, and each tool has advantages and disadvantages. It is not a perfect or easy subject, requiring constant learning and practice. It may also have pitfalls and challenges, such as bias, error, and misuse. Consider this scenario: you are scrolling through endless news feeds, bombarded with conflicting headlines and statistics on topics ranging from climate change to the latest celebrity scandal.  But how do you know what to believe?  How do you cut through the noise and discern fact from…