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Quantitative Research Methods: Tools for Data Analysis

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Quantitative Research Methods: Tools for Data Analysis

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Gain insight into a topic and learn the fundamentals.
4.5

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Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
4.5

17 reviews

Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Design a basic quantitative study, including determining research questions, selecting appropriate methods, and implementing data collection.

  • Perform basic statistical analyses (mean, standard deviation, correlations) using Excel and R.

  • Interpret descriptive statistical results to support informed decision-making.

  • Apply ethical considerations and quality checks throughout study design, data collection, and analysis to ensure rigor and reliability.

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Assessments

4 assignments¹

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Taught in English

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There is 1 module in this course

In this course, you will explore the world of quantitative research methods and data analysis using Excel and R. Whether you’re a student, business owner, or nonprofit professional, you’ll gain practical tools to collect, analyze, and interpret data for meaningful insights. Through engaging lessons and hands-on practice, you’ll learn to confidently apply statistical techniques and ethical considerations in your research projects.

This course is designed for individuals who are looking to enhance their skills in quantitative research and data analysis. It's ideal for undergraduate students in social or behavioral sciences who need to build a solid foundation in research methods. Entry-level data analysts or interns will also benefit from this course, as it provides practical tools to work with data using Excel and R. Additionally, small business owners seeking to make data-driven decisions and educators or researchers new to quantitative methods will find the content accessible and relevant to their work. To get the most out of this course, learners should have basic computer skills and a general familiarity with spreadsheets (Excel). No advanced statistical knowledge or programming experience is required, as the course starts with the fundamentals and builds up to more complex concepts in an easy-to-understand manner. By the end of this course, you will have a solid foundation in quantitative research methods, including designing studies, analyzing data with Excel and R, and addressing ethical considerations. You’ll be equipped with practical tools to interpret and report your findings confidently. Whether you're diving into research for the first time or enhancing your existing skills, the techniques you've learned here will empower you to approach data with a critical and informed mindset. Keep applying these methods, continue exploring more advanced topics, and watch as your data skills unlock new opportunities for you!

In this course, you will explore the world of quantitative research methods and data analysis using Excel and R. Whether you’re a student, business owner, or nonprofit professional, you’ll gain practical tools to collect, analyze, and interpret data for meaningful insights. Through engaging lessons and hands-on practice, you’ll learn to confidently apply statistical techniques and ethical considerations in your research projects.

What's included

13 videos5 readings4 assignments

13 videosTotal 72 minutes
  • Introduction and Welcome 3 minutes
  • Designing a Strong Study Framework6 minutes
  • Collecting Data Effectively and Efficiently5 minutes
  • Handling Data Ethically and Securely5 minutes
  • Importing & Cleaning Data in Excel7 minutes
  • Calculate Basic Descriptive Metrics (Mean, SD)4 minutes
  • Visualize Data and Identify Trends9 minutes
  • Compute Correlation & Run Simple Analysis in Excel6 minutes
  • Setting Up R & Loading Data7 minutes
  • Running Basic Stats in R 9 minutes
  • Ensure Ethical Data Analysis & Avoid Biases in Code5 minutes
  • Ensuring Quality Control & Reporting Findings 5 minutes
  • Congratulations and Continuous Learning Journey 2 minutes
5 readingsTotal 25 minutes
  • Course Overview5 minutes
  • Ensuring Ethics & Data Quality in Research5 minutes
  • Quick Guide to Excel Data Analysis5 minutes
  • R Basics Cheat Sheet5 minutes
  • Hands On Learning (HOL): R Studio Mini Project 5 minutes
4 assignmentsTotal 110 minutes
  • Quantitative Research Methods: Tools for Data Analysis20 minutes
  • Planning Your Study Parameters30 minutes
  • Sales Data Analysis in Excel30 minutes
  • Beginner’s Data Project30 minutes

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Frequently asked questions

In this course, the quantitative research workflow means turning a measurable question into a simple study, structured data, and clear statistical results. The focus is on a repeatable process that includes study design, basic analysis, interpretation, and ethical handling of data.

You would use this workflow when you need to answer a question with data rather than rely on informal impressions alone. The course applies it to situations where you need to define variables, choose a data collection method, and interpret descriptive results for informed decision-making.

It links the early work of defining a research question and selecting a method with the later work of cleaning, analyzing, and reporting data. In this course, the point is to connect those stages so the findings are consistent, interpretable, and easier to verify.

This workflow is broader than doing a few isolated calculations after data has already been gathered. It starts with a clear question and measurement plan, then carries quality and ethics checks through collection, analysis, and interpretation.

Basic computer skills and a general familiarity with spreadsheets are helpful before starting this workflow. The course does not require advanced statistics or programming experience, because it begins with fundamentals and builds into Excel and R practice.

The course mainly uses Excel and R. Alongside the tool work, it emphasizes descriptive analysis, study design, and ethical data handling.

You practice turning research questions into measurable variables, organizing and cleaning datasets, and running basic descriptive and relationship analyses. You also interpret charts and outputs while applying ethical and data-quality checks to keep the workflow rigorous.

Financial aid available,

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.