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Regression Analysis: Simplify Complex Data Relationships
Google

Regression Analysis: Simplify Complex Data Relationships

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Sponsored by UNHCR - The UN Refugee Agency

42,409 already enrolled

Gain insight into a topic and learn the fundamentals.
4.7

(426 reviews)

Advanced level
Designed for those already in the industry
Flexible schedule
Approx. 32 hours
Learn at your own pace
96%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.7

(426 reviews)

Advanced level
Designed for those already in the industry
Flexible schedule
Approx. 32 hours
Learn at your own pace
96%
Most learners liked this course

What you'll learn

  • Investigate relationships in datasets

  • Identify regression model assumptions 

  • Perform linear and logistic regression using Python

  • Practice model evaluation and interpretation

Details to know

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Assessments

27 quizzes

Taught in English

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Build your Data Analysis expertise

This course is part of the Google Advanced Data Analytics Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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  • Gain a foundational understanding of a subject or tool
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There are 6 modules in this course

You’ll begin by exploring the main steps for building regression models, from identifying your assumptions to interpreting your results. Next, you’ll explore the two main types of regression: linear and logistic. You’ll learn how data professionals use linear and logistic regression to approach different kinds of business problems.

What's included

8 videos3 readings4 quizzes1 plugin

You’ll explore how to use models to describe complex data relationships. You’ll focus on relationships of correlation. Then, you’ll build a simple linear regression model in Python and interpret your results.

What's included

9 videos8 readings5 quizzes5 ungraded labs

After simple regression, you’ll move on to a more complex regression model: multiple linear regression. You’ll consider how multiple regression builds on simple linear regression at every step of the modeling process. You’ll also get a preview of some key topics in machine learning: selection, overfitting, and the bias-variance tradeoff.

What's included

10 videos4 readings5 quizzes3 ungraded labs1 plugin

You’ll build on your prior knowledge of hypothesis testing to explore two more statistical tests: Chi-squared and analysis of variance (ANOVA). You’ll learn how data professionals use these tests to analyze different types of data. Finally, you’ll conduct two kinds of Chi-squared tests, as well as one-way and two-way ANOVA tests.

What's included

9 videos3 readings4 quizzes3 ungraded labs

You’ll investigate binomial logistic regression, a type of regression analysis that classifies data into two categories. You’ll learn how to build a binomial logistic regression model and how data professionals use this type of model to gain insights from their data.

What's included

8 videos4 readings5 quizzes3 ungraded labs

You’ll complete an end-of-course project by building a regression model to analyze a workplace scenario dataset.

What's included

5 videos10 readings4 quizzes6 ungraded labs

Instructor

Instructor ratings
4.4 (104 ratings)
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4.7

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