Which method in pandas is used to read a CSV file containing the dataset for Linear Regression?
read_csv()
load()
from_csv()
loadtxt()
What does a residual represent in linear regression?
The slope of the regression line.
The difference between the actual and predicted values of the dependent variable.
The intercept of the regression line.
The predicted value of the dependent variable.
What type of visualization tool is commonly used to initially assess the relationship between two continuous variables in linear regression?
Histogram
Scatter plot
Pie chart
Bar chart
Which of the following is the general equation for a simple linear regression model?
y = b0 + b1x1 + b2x2 + ... + bn*xn
y = b0 + b1*x + e
y = b0 * x^b1
y = e^(b0 + b1*x)
Feature selection in linear regression primarily aims to:
Improve model performance and generalization by focusing on the most relevant predictors
Ensure that all features have a statistically significant p-value
Make the model more complex and harder to interpret
Increase the number of features used for prediction
What does the linearity assumption in linear regression imply?
The dependent variable must have a normal distribution.
The independent variables are unrelated to each other.
The relationship between the dependent and independent variables can be best represented by a straight line.
The data points are evenly distributed around the regression line.
What graphical tool is commonly used to visualize the relationship between two continuous variables in linear regression?
What is the primary goal of feature selection in linear regression?
Maximize the number of features used in the model
Increase the complexity of the model
Introduce bias into the model
Improve the model's interpretability and reduce overfitting
How does the Mean Squared Error (MSE) penalize larger errors compared to smaller errors?
It squares the errors, giving more weight to larger deviations.
It doesn't; all errors are penalized equally.
It takes the absolute value of the errors, ignoring the sign.
It uses a logarithmic scale to compress larger errors.
Who is credited as a pioneer in developing the method of least squares, a foundational element of linear regression?
Ada Lovelace
Carl Friedrich Gauss
Alan Turing
Blaise Pascal