This is the fifth of eight courses in the Google Advanced Data Analytics Certificate. Data professionals use regression analysis to discover the relationships between different variables in a dataset and identify key factors that affect business performance. In this course, you’ll practice modeling variable relationships. You'll learn about different methods of data modeling and how to use them to approach business problems. You’ll also explore methods such as linear regression, analysis of variance (ANOVA), and logistic regression.



Regression Analysis: Simplify Complex Data Relationships
This course is part of Google Advanced Data Analytics Professional Certificate

Instructor: Google Career Certificates
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Access provided by SDU University
59,677 already enrolled
(556 reviews)
What you'll learn
Investigate relationships in datasets
Identify regression model assumptions
Perform linear and logistic regression using Python
Practice model evaluation and interpretation
Skills you'll gain
- Regression Analysis
- Machine Learning
- Exploratory Data Analysis
- Predictive Modeling
- Scikit Learn (Machine Learning Library)
- Advanced Analytics
- Analytical Skills
- Statistical Modeling
- Data Analysis
- Statistical Analysis
- Probability & Statistics
- Correlation Analysis
- Statistical Hypothesis Testing
- Business Analytics
- Supervised Learning
- Variance Analysis
- Python Programming
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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 assignments2 plugins
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 assignments5 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 assignments3 ungraded labs2 plugins
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 assignments3 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 assignments3 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 assignments6 ungraded labs
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Reviewed on Feb 15, 2024
good instructor, slightly complicated notebooks, too much of new information and formulas at once, regression analysis is very powerful technique
Reviewed on Apr 27, 2023
Extremely challenging incredibly for beginners yet rewarding.
Reviewed on Jun 22, 2023
This course is extremely exciting and challenging. I am finally starting to understand the power of models for predicting outcomes.
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