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University of Lincoln

Introduction to Statistics without Maths: Regressions

University of Lincoln via FutureLearn

Overview

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Advance your data analysis expertise with an overview of regressions

Have you ever wondered how analysts predict market trends or how scientists determine the impact of variables on an outcome?

Join the University of Lincoln’s final instalment of their Introduction to Statistics without Maths programme and gain fundamental skills rooted in regression analysis.

This course has been designed so that you don’t need to hail from a maths background. However, it’s recommended you complete the other three Introduction to Statistics without Maths courses from the University of Lincoln, before starting this one.

Delve into data modelling and plotting on the Cartesian plane

Begin this course by laying a practical foundation in regression analysis. You’ll learn how to model complex data and plot it on the Cartesian plane.

By the end of the week, you’ll understand what the y-intercept and regression signify, and how to accurately fit a line of best fit to your data. This will help you gain insights into relationships between variables and make informed predictions.

Grasp multiple regression analysis through R-square and correlation coefficients

Week two dives deeper into understanding multiple regression analysis. Analyse relationships using multiple independent variables, both continuous and categorical.

Throughout the week, you’ll interpret R-Square and correlation coefficients, essential outputs for assessing the goodness of fit and the strength of relationships in your models.

Explore special applications, including T-tests and ANOVA

Learn how T-tests and ANOVA can be integrated into regression analysis to test specific hypotheses and evaluate the significance of variables within your models.

This will help you apply more sophisticated analytical techniques and draw more robust conclusions.

This course is designed for anyone interested in statistics and data analysis. You don’t need a maths background, but it may be helpful to refresh your skills with the course Introduction to Descriptive Statistics without Maths: Basic Inferential Statistics.

To really understand data analysis, you will need to also spend some time to learn using the techniques taught on the course. There are lots of different programmes that you can use - please choose the one you are comfortable with. Jamovi is one such option and the one we use within the course:

  • Jamovi. This is a free software that you can download onto your computer. A cloud version is available but requires you to create an account and has some limitations in functionality. You can download this at https://jamovi.org/.
  • Alongside this, we recommend you work through the step-by-step Jamovi guides available on the StatsMadeEasy Website - link.

Syllabus

  • Introduction to Regression
    • Welcome & Course Overview
    • Linear Regression the basics: Cartesian Plane, the y-intercept and slope
    • Fitting a Line of Best Fit
    • Summary
  • Linear Regression: Multiple Independent Variables
    • Overview: Linear Regression
    • Multiple Linear Regression
    • Regression Special Application: T-Test and ANOVAs
    • Summary

Taught by

Joshua Skoczylis

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