Linear Regression from Coursera

This course is best suited for individuals who have a technical background in mathematics/statistics/computer science/engineering pursuing a career change to jobs or industries that are data-driven such as finance, retain, tech, healthcare, government and many more. The opportunity is endless.

This course is part of the Performance Based Admission courses for the Data Science program.

This course will focus on getting you acquainted with the basic ideas behind regression, it provides you with an overview of the basic techniques in regression such as simple and multiple linear regression, and the use of categorical variables.

Software Requirements: R

Upon successful completion of this course, you will be able to:

- Describe the assumptions of the linear regression models.

- Compute the least squares estimators using R.

- Describe the properties of the least squares estimators.

- Use R to fit a linear regression model to a given data set.

- Interpret and draw conclusions on the linear regression model.

- Use R to perform statistical inference based on the regression models.

What's inside

Syllabus

Module 1: Simple linear regression

Welcome to Linear Regression! In this course, we will cover the following topics: Simple Linear Regression, Multiple Linear Regression, and Regression Models with Qualitative Predictors. In Module 1, we will focus on defining the problem and setting up the simple linear regression model. Additionally, you will be introduced to the least square method as well as performing statistical inferences and predictions using R. There is a lot to read, watch, and consume in this module so, let’s get started!

Module 2: Multiple Linear Regression

Welcome to Module 2 - Multiple linear Regression. This module will focus on deriving parameter estimation using matrices as well as using R to do prediction and inference. There is a lot to read, watch, and consume in this module so, let’s get started!

Module 3: Regression Models with Qualitative Predictors

Welcome to Module 3 – Regression Models with Qualitative Predictors. This module will focus on setting up a linear regression model that involves qualitative predictors. Additionally, we will use R to help us perform statistical inferences and Predictions. There is a lot to read, watch, and consume in this module so, let’s get started!

Summative Course Assessment

This module contains the summative course assessment that has been designed to evaluate your understanding of the course material and assess your ability to apply the knowledge you have acquired throughout the course. Be sure to review the course material thoroughly before taking the assessment.

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Taught by Kiah Ong, who are recognized for their work in the field of Data Science

Explores fundamental concepts and methods in regression analysis, which are foundational in Data Science, Finance, Health Care, and Government sectors

Emphasizes the practical applications of regression analysis and statistical inference using R, a widely used language and toolset in Data Science

Provides a comprehensive overview of the topic through modules covering Simple Linear Regression, Multiple Linear Regression, and Regression Models with Qualitative Predictors

Part of the Performance Based Admission courses for the Data Science program, suggesting the possibility for further study and career advancement

Suitable for individuals with technical backgrounds in Mathematics, Statistics, Computer Science, or Engineering who aspire to make a career shift to Data Science or related fields

Career center

Learners who complete Linear Regression will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use data to help businesses solve complex problems. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Data Scientist, as you will often need to use regression to identify trends and patterns in data.

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Machine Learning Engineer

Machine Learning Engineers build and maintain machine learning models to help businesses solve complex problems. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Machine Learning Engineer, as you will often need to use regression to identify trends and patterns in data.

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Software Engineer

Software Engineers design, develop, and maintain software applications. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Software Engineer, as you will often need to use regression to identify trends and patterns in data.

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Data Analyst

Data Analysts study data to help businesses make informed decisions. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Data Analyst, as you will often need to use regression to identify trends and patterns in data.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts use financial data to help businesses make investment decisions. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Financial Analyst, as you will often need to use regression to identify trends and patterns in financial data.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical methods to help investment firms make investment decisions. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Quantitative Analyst, as you will often need to use regression to identify trends and patterns in financial data.

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Market Researcher

Market Researchers study consumer behavior to help businesses develop marketing strategies. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Market Researcher, as you will often need to use regression to identify trends and patterns in consumer behavior.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical methods to help businesses improve their operations. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as an Operations Research Analyst, as you will often need to use regression to identify trends and patterns in operational data.

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Statistician

Statisticians collect, analyze, and interpret data to help businesses make informed decisions. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Statistician, as you will often need to use regression to identify trends and patterns in data.

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Business Analyst

Business Analysts study business processes to help businesses improve their efficiency and effectiveness. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Business Analyst, as you will often need to use regression to identify trends and patterns in business data.

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Econometrician

Econometricians use mathematical and statistical methods to study economic data. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as an Econometrician, as you will often need to use regression to identify trends and patterns in economic data.

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Data Engineer

Data Engineers design, build, and maintain data pipelines to help businesses store and process data. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Data Engineer, as you will often need to use regression to identify trends and patterns in data.

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Financial Risk Manager

Financial Risk Managers use mathematical and statistical methods to assess financial risk. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as a Financial Risk Manager, as you will often need to use regression to identify trends and patterns in financial data.

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Actuary

Actuaries use mathematical and statistical methods to assess risk and uncertainty. The skills and knowledge you learn in this course will help you build a strong foundation in regression, which is a statistical method used to analyze relationships between variables. This will be essential for your success as an Actuary, as you will often need to use regression to identify trends and patterns in data.

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Linear Regression

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