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Linear Regression: A Step-by-Step Guide

June 10, 2024 / July 27, 2024 by Simon Njeri

Linear Regression: A powerful statistical method used to understand and quantify the relationship between two or more variables.[toc] Introduction to Linear Regression Linear regression is a fundamental concept in statistics and machine learning. At its heart, it explores the linear relationship between variables, aiming to model the relationship between them. This relationship, once established, can be […]

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Applications of linear regression in various fields (e.g. Assumptions of linear regression and how to check them economics Evaluating model fit and prediction accuracy in linear regression Simple linear regression vs. multiple linear regression social sciences)

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A Comprehensive Guide to Correlation

June 8, 2024 / July 27, 2024 by Simon Njeri

Correlation is a fundamental concept in statistics that helps us understand the strength and direction of the linear relationship between two variables. It’s a powerful tool for uncovering patterns and insights in data, making it essential for researchers, business professionals, and social scientists. Key Takeaways Types of Correlation Different types of correlation coefficients are used depending […]

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Applications of correlation analysis in different fields (e.g. Correlation vs. causation in statistical analysis Finance Pearson correlation coefficient calculation and interpretation social sciences) Spearman rank correlation for non-linear relationships

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Regression Analysis: A Comprehensive Guide

June 7, 2024 / July 27, 2024 by Simon Njeri

Regression analysis is a powerful statistical method used to examine the relationship between two or more variables of interest. It helps us understand how the value of a dependent variable changes as the value(s) of one or more independent variables change. This analysis allows us to model and predict the outcome of a particular event […]

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Applications of regression analysis in different fields (e.g. economics medicine) Regression analysis assumptions and diagnostics Regression model selection and validation techniques Simple linear regression vs. multiple linear regression social sciences)

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