Inclusive Analytic Techniques

Inclusive Analytic Techniques

This course is part of Gender Analytics: Gender Equity through Inclusive Design Specialization

Instructors: Sarah Kaplan

Access provided by Universidad de Guadalajara

6,314 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

97 reviews

8 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

97 reviews

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

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.

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Assessments

5 assignments

Taught in English

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This course is part of the Gender Analytics: Gender Equity through Inclusive Design Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

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.

When collecting and analyzing data from diverse communities, it is important to recognize that this can create vulnerabilities for marginalized individuals and groups. In this module, you will learn about the legal frameworks and ethical requirements related to collecting, storing, analyzing, and disseminating data, paying attention to different country contexts. By the end of the week, you will understand potential risks to research participants and find ways to mitigate such risks and appropriately compensate them for their time and efforts in the data collection and design process. These considerations are important to take into account before you move forward with any data collection and analysis projects.

What's included

6 videos4 readings1 assignment2 discussion prompts

6 videosTotal 22 minutes

Introduction to Inclusive Analytic Techniques2 minutes
Why should we collect information about diverse communities? 5 minutes
Why should someone provide you with information?2 minutes
Addressing legal requirements in a global context2 minutes
Anchoring your research in the lived experience of informants4 minutes
Ethics planning in community-based research5 minutes

4 readingsTotal 36 minutes

Land Acknowledgement1 minute
Faculty biographies10 minutes
Case example: IBM’s Self ID Program10 minutes
First Nations Principles of Ownership, Control, Access, and Possession of Data (OCAP)15 minutes

1 assignmentTotal 30 minutes

Assessment 130 minutes

2 discussion promptsTotal 20 minutes

Benefits of collecting diversity data10 minutes
Barriers to data collection10 minutes

This session will review basic principles of quantitative data analysis, including probability and hypothesis testing, through fun examples and exercises. By the end of the week, you will be able to conduct basic calculations to analyze quantitative data and develop the intuition behind statistical inference and hypothesis testing to understand analytical reports generated by others.

What's included

8 videos3 readings1 assignment

8 videosTotal 62 minutes

Introduction to probability9 minutes
What we need to know about probability6 minutes
Statistical inference6 minutes
Testing a hypothesis – Intuition9 minutes
Formulating hypotheses3 minutes
Testing a hypothesis – calculation using Excel15 minutes
Analyzing subsets within your data6 minutes
Analyzing multiple subsets at once9 minutes

3 readingsTotal 30 minutes

Probability distributions 10 minutes
[Optional] Confidence intervals – is Brian’s coin a “fair coin”? 10 minutes
[Exercise] Calculate a probability10 minutes

1 assignmentTotal 30 minutes

Assessment 230 minutes

This week, we will shed light on how data is produced and how to uncover gender-based insights from data. By the end of the week, you will understand the data generation process, know where to locate sources of gender-disaggregated data, and analyze relationships to interpret results. You will see how emerging insights from gender-disaggregated data analysis can shape the evolution of the problem statement and identify areas for further data collection.

What's included

7 videos2 assignments

7 videosTotal 50 minutes

Data collection and the data generation process13 minutes
Where to find data8 minutes
Are the data reasonable?5 minutes
Interpreting results7 minutes
Analyzing relationships: correlation9 minutes
Analyzing relationships: regression7 minutes
Taking evidence-based action2 minutes

2 assignmentsTotal 60 minutes

Assessment 330 minutes
Evaluate quantitative data-collection plans30 minutes

A big part of applying a gender lens to data analysis is obtaining different perspectives, especially from underrepresented groups. One way to do this is through qualitative research in the communities of interest. This week, you will explore the art of meaningful community engagement. By the end of this week, you will have a better understanding of the concept and value of community engagement as a qualitative data source. You will learn the steps to collect and analyze qualitative data to gain insight into people’s emotions, motivations, aspirations, and pain points. You will also learn how engage responsibly with vulnerable or marginalized communities.