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Introduction to Statistics without Maths: Regressions

Build your statistics literacy with this flexible, online introduction to regressions from the University of Lincoln.

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Introduction to Statistics without Maths: Regressions

  • 2 weeks

  • 3 hours per week

  • Digital certificate when eligible

  • Introductory level

Find out more about how to join this course

  • Duration

    2 weeks
  • Weekly study

    3 hours
  • 100% online

    How it works
  • Unlimited subscription

    $244.99 for a whole yearLearn more

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.

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Skip to 0 minutes and 2 seconds Welcome to the Statistics without Maths courses. These are four courses where we’ll teach you fundamental statistic concepts and techniques to bring data to life so that you can make sense of it and that you can explain the findings to others in an easy way. For this course you won’t need any maths. To introduce myself, I’m Doctor Joshua Skoczylis. I’m a senior lecturer in criminology and counter terrorism and I’ve been teaching statistics and quantitative methods for over a decade now. My name’s Scott Kidd and I’m an Associate Lecturer and Researcher in criminology and psychology. My name is John Abiodun Babalola. I’m a PhD student of University of Lincoln, Associate Lecturer in the department of Criminology.

Skip to 0 minutes and 44 seconds I’m teaching quantitative analysis because of the fact that I see it as different to other model of analysis and I see it as very, very interesting and because of the fact that you learn this with little mathematics. Through these courses, we will guide you through the fundamentals of statistics, breaking down complex concepts into easy to understand lessons. Whether you’re a complete beginner or looking to brush up on your skills, you’ll find practical and valuable insights and that you can apply to help you in your studies and your career going forward. Data is all around us. We use it every day. It allows us to carry out research and understand complex and big data sets.

Skip to 1 minute and 18 seconds You need the skills and employment and at university. They’re very transferable skills. For breakdown of the details of the course and the syllabus, just scroll down and you’ll see what each of the four courses covers. We’re looking forward to seeing you on this journey to learning statistics without maths. Thank you very much.

Syllabus

  • Week 1

    Introduction to Regression

    • Welcome & Course Overview

      This activity provides you an overview of the course as well as wider information about the content learned in week 1.

    • Linear Regression the basics: Cartesian Plane, the y-intercept and slope

      In this activity, you will learn how we visualise data on the cartesian plane. You will also learn how to use the y-intercept and understand the slope of a regression.

    • Fitting a Line of Best Fit

      We learn about the line of best fit to understand data trends and make predictions. It helps summarise the relationship between variables and provides a model to estimate values for given inputs.

    • Summary

      This activity gives you a summary of your learning for the week.

  • Week 2

    Linear Regression: Multiple Independent Variables

    • Overview: Linear Regression

      Summary of what you will learn in week 2.

    • Multiple Linear Regression

      Here we will introduce you to multiple regressions. Multiple Regressions are models that have more than one independent variable.

    • Regression Special Application: T-Test and ANOVAs

      Here we will cover T-test and ANOVAs. These are special applications of linear regression.

    • Summary

      This activity provides you with a summary of learning for week 2.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Apply the techniques learned to real world scenarios in academia, government, and the private sector.
  • Demonstrate your ability to understand the output from advanced statistical methods to make sense of the data.
  • Model complex data and the relationships that exist within
  • Identify if your data meets the required assumptions of a regression

Who is the course for?

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.

What software or tools do you need?

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.

Who will you learn with?

Who developed the course?

University of Lincoln

The University of Lincoln is proud to be ranked as a Top 3 University in the WhatUni University of the Year 2024 awards, as well as a triple-gold institution in the latest Teaching Excellence Framework (TEF) 2023.

  • Established

    1996
  • Location

    Lincoln, Lincolnshire, UK

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Ways to learn

Choose the best way to learn for you!

Subscribe & save

$244.99 for a whole year

Automatically renews

Develop skills to further your career

  • Access to this course
  • Access to 1,000+ courses
  • Learn at your own pace
  • Discuss your learning in comments
  • Digital certificate when you're eligible

Cancel for free anytime

Buy this course

$109/one-off payment

Fulfill your current learning need

  • Access to this course
  • Learn at your own pace
  • Discuss your learning in comments
  • Printed and digital certificate when you’re eligible

Limited access

Free

Sample the course materials

  • Access expires 19 Oct 2024

Find out more about certificates, Unlimited or buying a course (Upgrades)

Sale price available until 31 October 2024 at 23:59 (UTC). T&Cs apply.

Find out more about certificates, Unlimited or buying a course (Upgrades)

Sale price available until 31 October 2024 at 23:59 (UTC). T&Cs apply.

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