Exercise 4 Overview - Hypothesis Tests and Confidence Intervals

Exercise Overview

• Focus: Hypothesis Tests and Confidence Intervals in Multiple Regression

Data Preparation

• Import data: rental data lucerne 3.csv

• Required R packages:

  • "tidyverse"

  • "sandwich"

  • "lmtest"

  • "car"

Linear Regression Analysis

• Conduct a linear regression using specified independent variables.

Evaluating Statistical Significance

• Evaluate independent variables excluding intercept term (β0).

Addressing Heteroskedasticity

• Apply MacKinnon and White (1985) method for robust standard error correction.

• Repeat significance test and analyze interpretation changes.

Model Utility

• Assess if the model explains variation in rental prices effectively.

Confidence Interval Calculation

• Calculate confidence interval for β1 (number of rooms).

• Significance level (α = 0.10) and apply t-distribution critical value.