This guide helps you make a choice for statistical analysis to be performed on your research data. It focuses on nine key areas which include the following; Use Cases,
Industry Practical Examples,
Data Preprocessing,
Key Assumptions,
Result Interpretation,
Sample size Consideration,
Data Quality,
Validity of Assumptions,
and Data Gathering Techniques.
It is designed to be inclusive and user-friendly, catering to a wide range of readers, including students studying statistics, professionals in non-statistical fields, small business owners, educators, researchers from non-statistical disciplines, data enthusiasts, and professionals in entry-level data analysis roles. The guide recognizes the need for individuals from various backgrounds and professions to understand and apply statistical concepts in their work or daily lives.
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