Explore

Inclusive Analytic Techniques

Approx. 8 hours to complete

Save Course

Go to Course

Course Summary

This course explores the use of gender analytics in data analysis and decision-making. It emphasizes the importance of inclusivity in analytics and highlights the biases that can arise without it.

Key Learning Points

Learn how to apply gender analytics to data analysis
Understand the importance of inclusivity in analytics
Identify and address biases in data analysis

Learning Outcomes

Apply gender analytics to data analysis
Identify and mitigate biases in data analysis
Understand the importance of inclusivity in analytics

Prerequisites or good to have knowledge before taking this course

Basic knowledge of statistics and data analysis
Familiarity with Excel or any data analysis tool

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced
Video lectures
Assignments and quizzes

Similar Courses

Inclusive Leadership
Gender and Sexuality: Diversity and Inclusion in the Workplace

Related Education Paths

Notable People in This Field

Founder and CEO, Girls Who Code
Author and Speaker

Related Books

Description

Many policies, products, services or processes that we think of as gender-neutral actually have gendered outcomes. Everything from snow plowing to car safety to investment advising to infrastructure investment has impacts that differ by gender. These outcomes can be even more biased if we look at important intersections with race, indigeneity, differences in ability, ethnicity, sexual orientation, and other identities. The question is, what can you do to change this? And, how can you avoid the risks of bias or create innovative new offerings using gender-based insights?

Inclusive Analytics Techniques will provide you with the tools and analytical techniques to uncover these intersectional insights. The course covers both quantitative and qualitative data collection and analysis, including basic statistical techniques and practical instructions for working with customers, beneficiaries and other stakeholders. You will learn to incorporate multiple sources of rich evidence in order to develop innovative insights into how policies, products, services and processes can be made more equitable or serve unique communities. This is the second course of the Gender Analytics Specialization offered by the Institute for Gender and the Economy (GATE) at the University of Toronto's Rotman School of Management. It's great on its own, and you will get even more out of it if you take it as part of the Specialization.

Knowledge

Understand legal & ethical frameworks for collecting, storing, analyzing, and disseminating data to reduce vulnerabilities for marginalized people.
Examine how quantitative data is produced, identify gender-related data gaps; & use analytics skills to uncover intersectional gender-based insights
Collaborate with stakeholders to gain an in-depth understanding of unmet needs using community-based and ethnographic research methods
Learn quantitative & qualitative research and analysis techniques; explore how to integrate insights from both types of data to generate insight.

Outline

Ethical and legal considerations in inclusive data collection
Introduction to Inclusive Analytic Techniques
Why should we collect information about diverse communities?
Why should someone provide you with information?
Addressing legal requirements in a global context
Anchoring your research in the lived experience of informants
Ethics planning in community-based research
Land Acknowledgement
Faculty biographies
Case example: IBM’s Self ID Program
First Nations Principles of Ownership, Control, Access, and Possession of Data (OCAP)
Assessment 1

Quantitative data analysis through a gender lens: probability
Introduction to probability
What we need to know about probability
Statistical inference
Testing a hypothesis – Intuition
Formulating hypotheses
Testing a hypothesis – calculation using Excel
Analyzing subsets within your data
Analyzing multiple subsets at once
Probability distributions
[Optional] Confidence intervals – is Brian’s coin a “fair coin”?
[Exercise] Calculate a probability
Assessment 2

Quantitative data analysis through a gender lens: data and interpretation
Data collection and the data generation process
Where to find data
Are the data reasonable?
Interpreting results
Analyzing relationships: correlation
Analyzing relationships: regression
Taking evidence-based action
Evaluate quantitative data-collection plans
Assessment 3

Qualitative data collection: community-based engagement with stakeholders
What is qualitative community-based research
Community engagement principles
Participatory data collection methods
Valuing lived experience
Empathy
Community engagement steps 1-2
Community engagement steps 3-5
Inclusive participatory practices
Engaging new groups
Analyzing qualitative data
Application Spotlight: Application to your project workplan
Course recap: Inclusive analytic techniques
IAP2 Spectrum of Public Participation
[Worksheet] Research plan for your Gender Analytics project
Congratulations!
Assessment 4

Summary of User Reviews

Discover how to apply gender analytics to your data and create more inclusive analytics strategies with this course on Coursera! Users have found this course to be informative and engaging, with a focus on practical applications of the material.

Key Aspect Users Liked About This Course

Users appreciated the practical approach to applying gender analytics to real-world scenarios.

Pros from User Reviews

Instructors provide clear explanations and examples that are easy to follow.
Course content is relevant and up-to-date with current trends in gender analytics.
Assignments and quizzes are challenging but not overwhelming, helping users retain the material.
Course forums and discussions allow for collaboration and knowledge sharing among peers.
Certificate of completion provides a tangible reward for users who complete the course.

Cons from User Reviews

Some users found the course to be too basic and not challenging enough.
The course may not be suitable for users who are already familiar with gender analytics concepts.
The pace of the course may be too fast for some users, particularly those who are new to the subject matter.
Some users found the course material to be too heavily focused on North American examples and perspectives.
Users who do not enjoy online learning may find the course format to be less engaging than in-person instruction.

Recommended for you

Inclusive Analytic Techniques

Many policies, products, services or processes that we think of as gender-neutral actually have gendered outcomes. The question is, what can you do to change this?...

Save Course