Why Numbers Matter: Quantitative Research (FutureLearn)

Why Numbers Matter: Quantitative Research (FutureLearn)

Learn how to use quantitative research to make difficult decisions and solve real-world problems. We use numbers in everyday life to make hundreds of small decisions that quickly add up to something bigger. This course will help you to harness the power of quantitative research to make better informed decisions and solve real-world problems.

Class Deals by MOOC List - Click here and see FutureLearn's Active Discounts, Deals, and Promo Codes.

You’ll improve your understanding of how to use statistical analysis to draw meaningful conclusions from numerical data.
Whether it’s making an important financial investment, or testing the effectiveness of workplace practices, quantitative research helps us to make difficult decisions for ourselves and our communities.

What topics will you cover?

  • Why numbers matter in quantitative research
  • How to use statistics to analyse data and solve real world problems
  • How to formulate research questions, informed by accurate and reliable measurement
  • How to select and justify an appropriate research method to answer your question
  • The close relationship between quantitative and qualitative research
  • What will you achieve?

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

  • Apply statistical analysis, including types of data, averages, proportions and confidence intervals, to make decisions about real world problems.
  • Calculate bivariate correlations using computer software
  • Develop an appropriate quantitative study design to answer a research question
  • Justify the role of quantitative research in your research project
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Six Sigma Advanced Define and Measure Phases (Coursera) Coursera
University System of Georgia

Six Sigma Advanced Define and Measure Phases (Coursera)

This course is for you if you are looking to dive deeper into Six Sigma or strengthen and expand your knowledge of the basic components of green belt level of Six Sigma and Lean. Six Sigma skills are widely sought by employers both nationally and internationally. These skills have been proven to help improve business processes and performance. This course will take you deeper into the principles and tools associated with the "Design" and "Measure" phases of the DMAIC structure of Six Sigma.

Jun 22nd 2026
5-12 Weeks
Data to Insight: An Introduction to Data Analysis and Visualisation (FutureLearn) FutureLearn
University of Auckland

Data to Insight: An Introduction to Data Analysis and Visualisation (FutureLearn)

A hands-on introduction emphasizing key ideas, computer skills and statistical thinking. Data is everywhere and the lessons it contains can be the key to making good decisions. We want to give you skills and the confidence to dive into data using computer software and start making discoveries. You will learn key elements of data science and to start thinking like a statistician.

No sessions available
5-12 Weeks
Linear Regression and Modeling (Coursera) Coursera
Duke University

Linear Regression and Modeling (Coursera)

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

Jun 22nd 2026
4 Weeks
Fitting Statistical Models to Data with Python (Coursera) Coursera
University of Michigan

Fitting Statistical Models to Data with Python (Coursera)

In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods. We will also focus on various modeling objectives, including making inference about relationships between variables and generating predictions for future observations.

Jun 22nd 2026
4 Weeks
Six Sigma Tools for Analyze (Coursera) Coursera
University System of Georgia

Six Sigma Tools for Analyze (Coursera)

This course will cover the Measure phase and portions of the Analyze phase of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process. You will learn about lean tools for process analysis, failure mode and effects analysis (FMEA), measurement system analysis (MSA) and gauge repeatability and reproducibility (GR&R), and you will be introduced to basic statistics. This course will outline useful measure and analysis phase tools and will give you an overview of statistics as they are related to the Six Sigma process.

Jun 22nd 2026
4 Weeks
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Jun 22nd 2026
5-12 Weeks
Get ready for a Masters in Data Science and AI (FutureLearn) FutureLearn
Coventry University

Get ready for a Masters in Data Science and AI (FutureLearn)

Identify whether you’re ready for Master’s study, improve your data science skills, and get to grips with the basics of Python. Get a taste of life as a Data Science and AI Master's student. On this course, you’ll have the opportunity to explore the disciplines involved in a Master’s degree in Data Science and Artificial Intelligence (AI).

Apr 17th 2023
2 Weeks
Inferential Statistics (Coursera) Coursera
Duke University

Inferential Statistics (Coursera)

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data.

Jun 22nd 2026
5-12 Weeks
Accounting for Death in War: Separating Fact from Fiction (FutureLearn) FutureLearn
Royal Holloway, University of London,Every Casualty Counts

Accounting for Death in War: Separating Fact from Fiction (FutureLearn)

Discover the main methods used to account for war deaths, how they've been used and practice using them yourself. Calculating the number of deaths during a war is a difficult, but necessary, task - having accurate information is crucial for political and societal debates and decisions. On this course you will explore the methods currently used to account for war deaths and then apply these methods to particular wars.

Available now
3 Weeks
Chemometrics in Air Pollution (FutureLearn) FutureLearn
University of Malaya

Chemometrics in Air Pollution (FutureLearn)

This course briefly introduces the causes and effects of air pollution in Asian, chemometric models and chemometric application. This course briefly introduces the causes and effects of air pollution. Air pollution is a growing concern the we experience in our daily life. But not everyone has a clear understanding of what the sources of air pollution are. Here, you will not only learn how to identify them, but also understand the potential impact air pollution has in our present and future.

May 16th 2022
3 Weeks