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    • Linear Regression

    Linear Regression Courses Online

    Explore linear regression for statistical modeling. Learn to analyze relationships between variables and make predictions based on data.

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    Explore the Linear Regression Course Catalog

    • U

      University of Illinois Urbana-Champaign

      Managerial Economics and Business Analysis

      Skills you'll gain: Descriptive Statistics, Supply And Demand, Market Dynamics, Sampling (Statistics), Statistical Inference, Business Analytics, Financial Systems, Financial Policy, Banking, Probability Distribution, Analytics, Statistical Analysis, Statistical Hypothesis Testing, Statistics, Regression Analysis, Microsoft Excel, Economics, Financial Market, Business Economics, Risk Management

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • R

      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Methods, Sample Size Determination, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Linear Algebra for Machine Learning and Data Science

      Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Jupyter, Data Manipulation, Data Science, Applied Mathematics, Python Programming, Image Analysis, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      Duke University

      Introduction to Logic and Critical Thinking

      Skills you'll gain: Deductive Reasoning, Logical Reasoning, Computational Logic, Probability, Sampling (Statistics), Persuasive Communication, Research, Writing, Statistics, Scientific Methods, Oral Expression, Correlation Analysis, Interpersonal Communications, Interactive Learning, Learning Strategies, Instructional Strategies

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      Imperial College London

      Mathematics for Machine Learning: Multivariate Calculus

      Skills you'll gain: Regression Analysis, Calculus, Advanced Mathematics, Machine Learning Algorithms, Statistical Analysis, Linear Algebra, Artificial Neural Networks, Python Programming, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Everyday Excel

      Skills you'll gain: Data Import/Export, Microsoft Excel, Regression Analysis, Data Validation, Data Visualization, Depreciation, Data Management, Excel Macros, Excel Formulas, Statistical Modeling, Financial Analysis, Cash Flows, Predictive Modeling, Financial Modeling, Analysis, Microsoft Word, Business Mathematics, Mathematical Modeling, Complex Problem Solving, Financial Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Amsterdam

      Methods and Statistics in Social Sciences

      Skills you'll gain: Qualitative Research, Scientific Methods, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Research, Sampling (Statistics), Probability Distribution, Correlation Analysis, Research Design, Research Reports, Science and Research, Interviewing Skills, Data Analysis, Probability, Data Collection, Social Sciences, Statistical Methods, Probability & Statistics, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Biostatistics in Public Health

      Skills you'll gain: Biostatistics, Statistical Hypothesis Testing, Regression Analysis, Sampling (Statistics), Statistical Methods, Statistical Visualization, Statistical Analysis, Epidemiology, Medical Science and Research, Quantitative Research, Descriptive Statistics, Statistical Inference, Data Literacy, Probability Distribution, Scientific Methods, Data Analysis, Public Health, Probability & Statistics, Advanced Analytics, Statistical Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Statistics with Python

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Statistics, Bayesian Statistics, Data Visualization, Matplotlib, Statistical Visualization, Probability & Statistics, Statistical Analysis, Jupyter, Statistical Programming, Regression Analysis, Data Visualization Software, Predictive Modeling, Data Analysis, Exploratory Data Analysis, Descriptive Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.3K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Relational Databases, Tableau Software, Stored Procedure, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    Linear Regression learners also search

    Regression
    Linear Programming
    Regression Analysis
    Linear Algebra
    Regression Models
    Logistic Regression
    Predictive Modeling
    Statistical Modeling
    1…567…73

    In summary, here are 10 of our most popular linear regression courses

    • Managerial Economics and Business Analysis: University of Illinois Urbana-Champaign
    • Business Statistics and Analysis: Rice University
    • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
    • Introduction to Logic and Critical Thinking: Duke University
    • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
    • Everyday Excel: University of Colorado Boulder
    • Natural Language Processing: DeepLearning.AI
    • Methods and Statistics in Social Sciences: University of Amsterdam
    • Biostatistics in Public Health: Johns Hopkins University
    • Statistics with Python: University of Michigan

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Linear Regression

    Linear regression is a type of statistical data analysis that examines which variables help significantly predict the outcome of a situation. You can use linear regression to determine the relationships between one dependent variable and one or more independent variables to sort out which variables will contribute most to the outcome you seek to achieve. Linear regression also helps you forecast the impact that changes to variables will make in different scenarios. It's a tool you can use to help predict outcomes and make adjustments to help achieve the outcome you're looking for.‎

    If you're in a career that relies on data analysis, linear regression is a tool that can help you determine the relationship between variables that affect scenarios that you need to predict or plan for. You can use linear regression to anticipate how the factors that affect a situation now will make a difference in the future. For example, you can use linear regression to predict the cost of a project or the amount of time it will take to complete the project based on different variables. Linear regression can help you make more informed and educated decisions to better navigate the present and plan for the future.‎

    Data analysts use linear regression in different areas of business to determine which variables affect outcomes the most. You can apply linear regression as a data scientist or analyst with a single company or in a consultant role across multiple businesses. You can even set up your own business as a consultant to be in control of your own schedule and career trajectory. Analysts use linear regression in polling and surveys as well as in policy research fields, and various corporations use data analysis to help plan for the future. You can also apply your knowledge of linear regression in higher education and as a professor or research assistant.‎

    You can use online courses to learn linear regression in order to deepen your knowledge and skills in your current job or to find a new career. Whether you're already familiar with linear regression or whether you're brand new to the concept, online courses can give you the knowledge you need to apply linear regression in your workplace. Online courses not only teach you the concepts, but they also provide you with real-life applications of what you're learning. One of the biggest benefits of online learning is that you can sharpen your skills in a way that fits your schedule and lifestyle. You can walk away from your online learning confident in what you've discovered about linear regression and prepared to apply it to your career.‎

    Online Linear Regression courses offer a convenient and flexible way to enhance your knowledge or learn new Linear Regression skills. Choose from a wide range of Linear Regression courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Linear Regression, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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