University of Toronto

Inclusive Analytic Techniques

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

Taught in English

Some content may not be translated

Sarah Kaplan
Brian Silverman
Chanel Grenaway

Instructors: Sarah Kaplan

2,823 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.8

(74 reviews)

8 hours (approximately)
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 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.8

(74 reviews)

8 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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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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  • Gain a foundational understanding of a subject or tool
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There are 4 modules in this course

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 quiz2 discussion prompts

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 quiz

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 quizzes

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.

What's included

12 videos3 readings1 quiz

Instructors

Instructor ratings
4.8 (30 ratings)
Sarah Kaplan
University of Toronto
6 Courses19,961 learners

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4.8

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