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Linear Regression and Modeling Course

A practical, Excel-based guide to mastering linear regression for real-world business applications.

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

What will you learn in Linear Regression and Modeling Course

  • Understand the fundamentals of linear regression and its assumptions

  • Use regression models to analyze relationships between variables

  • Interpret regression coefficients and determine model validity

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  • Apply regression analysis in real-world business scenarios

  • Use Excel to build and evaluate regression models

Program Overview

Module 1: Introduction to Linear Regression

⏳ 1 week

  • Topics: Dependent vs. independent variables, scatterplots, correlation

  • Hands-on: Building your first regression model in Excel

Module 2: Estimating the Regression Line

⏳ 1 week

  • Topics: Ordinary Least Squares (OLS), residuals, best-fit line

  • Hands-on: Calculating regression line by hand and Excel practice

Module 3: Evaluating the Model

⏳ 1 week

  • Topics: R², adjusted R², hypothesis testing for regression coefficients

  • Hands-on: Model interpretation and evaluating model strength

Module 4: Model Assumptions and Diagnostics

⏳ 1 week

  • Topics: Linearity, independence, homoscedasticity, normality

  • Hands-on: Residual analysis and model refinement

Module 5: Business Applications of Regression

⏳ 1 week

  • Topics: Forecasting, marketing analysis, pricing strategy

  • Hands-on: Real-world business case studies and regression modeling

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Job Outlook

  • Linear regression is a core technique in data science, business analytics, and finance

  • In-demand for roles such as business analyst, data analyst, and financial modeler

  • Salary ranges for analysts with regression skills: $65,000–$110,000/year

  • Applicable in industries like retail, banking, marketing, and consulting

9.7Expert Score
Highly Recommendedx
A practical and conceptually rich course perfect for analysts and business professionals who want to use linear regression confidently in Excel.
Value
9.5
Price
9.3
Skills
9.8
Information
9.7
PROS
  • Clear business-focused explanations
  • Hands-on work in Excel no coding required
  • Real business scenarios included
CONS
  • Requires basic understanding of statistics
  • Not suitable for those looking for Python or R implementations

Specification: Linear Regression and Modeling Course

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

FAQs

  • A basic understanding of averages, percentages, and simple probability is enough.
  • Advanced math or calculus isn’t required.
  • The course explains statistical terms in simple language.
  • Excel demonstrations make concepts easy to follow.
  • Prior exposure to basic statistics helps but isn’t mandatory.
  • The course is Excel-based, no coding needed.
  • You’ll build regression models with formulas and tools.
  • Hands-on practice is focused on spreadsheets.
  • Concepts prepare you for coding later if desired.
  • It’s suitable for business professionals who aren’t programmers.
  • Regression is a common topic in analyst interviews.
  • You’ll learn to explain R², coefficients, and model fit clearly.
  • Knowledge of assumptions shows analytical depth.
  • Business case studies help you link theory to practice.
  • Strengthens both technical and communication skills for interviews.
  • Each module takes around 3–5 hours.
  • Includes video lessons, hands-on Excel practice, and quizzes.
  • With steady pace, course can be done in 4–5 weeks.
  • Learners can accelerate with more time investment.
  • Flexible schedule makes it easy to fit alongside work.
  • You’ll explore regression in sales, pricing, and marketing contexts.
  • Forecasting future trends is covered using regression models.
  • Emphasis is on interpreting business meaning of results.
  • Helps in creating data-driven strategies for decision-making.
  • Builds confidence to apply regression in real workplace scenarios.
Linear Regression and Modeling Course
Linear Regression and Modeling Course
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