Linear regression (lm) in R Programming - Mini Project: Build & Apply

Simple Linear Regression with lm in R

📖 Scenario: You are a data analyst at a small company. You want to understand how advertising spending affects sales. You have data on advertising budgets and sales for several months.

🎯 Goal: Build a simple linear regression model using lm in R to predict sales based on advertising spending.

📋 What You'll Learn

Create a data frame with advertising and sales data

Create a variable for the formula to use in the model

Use the lm function to build the linear regression model

Print the summary of the model to see the results

💡 Why This Matters

🌍 Real World

Linear regression is used in business to understand relationships between variables, like advertising spend and sales.

💼 Career

Data analysts and data scientists use linear regression to build predictive models and make data-driven decisions.

1

Create the data frame

Create a data frame called ad_data with two columns: advertising and sales. Use these exact values: advertising = c(10, 20, 30, 40, 50), sales = c(15, 25, 35, 45, 55).

R Programming

# Create the data frame ad_data with advertising and sales columns
# Your code here

Need a hint?

Use data.frame() to create the data frame with the exact column names and values.

2

Create the formula variable

Create a variable called model_formula that stores the formula sales ~ advertising.

R Programming

ad_data <- data.frame(advertising = c(10, 20, 30, 40, 50), sales = c(15, 25, 35, 45, 55))
# Create the model_formula variable with sales ~ advertising
# Your code here

Need a hint?

Use the tilde ~ to create the formula for the model.

3

Build the linear regression model

Use the lm function to create a linear model called model using model_formula and the data frame ad_data.

R Programming

ad_data <- data.frame(advertising = c(10, 20, 30, 40, 50), sales = c(15, 25, 35, 45, 55))
model_formula <- sales ~ advertising
# Create the linear model called model using lm()
# Your code here

Need a hint?

Use lm(formula, data = ...) to build the model.

4

Print the model summary

Print the summary of the linear model model using the summary() function.

R Programming

ad_data <- data.frame(advertising = c(10, 20, 30, 40, 50), sales = c(15, 25, 35, 45, 55))
model_formula <- sales ~ advertising
model <- lm(model_formula, data = ad_data)
# Print the summary of the model
# Your code here

Need a hint?

Use print(summary(model)) to see the details of the regression.