Multiple linear Regression Expreiment

In summary, the conversation is about creating an experiment for a regression class with specific criteria for predictors. The idea is to create a model that predicts ending auction prices for a playstation 3 on ebay, using numerical and categorical predictors such as the number of games, auction duration, number of controllers, and condition and bundle of the console. The data would be collected by searching for auctions on ebay.
  • #1
zzmanzz
54
0

Homework Statement



Hi,

I need to create an experiment for my regression class and I would appreciate some ideas which would allow me to generate the data with minimal resources (preferably something on the computer where I can get data instantly)

The main criteria for the experiment is that we must have at least 3 numerical predictors and one categorical predictor with two levels, and another one with three levels.

Homework Equations





The Attempt at a Solution



My idea was to create a model which predicts ending auction prices for a playstation 3 on ebay based on:

1. how many games
2. how many days the auction is running
3. how many controllers
4. used or new (categorical 1)
5. console only, console and controllers, console controllers and games (categorical 2)
 
Physics news on Phys.org
  • #2
I would collect the data by searching for auctions on ebay and record the above variables as well as the ending auction price. This way I could generate the data with minimal resources.
 

Related to Multiple linear Regression Expreiment

1. What is multiple linear regression?

Multiple linear regression is a statistical method used to analyze the relationship between multiple independent variables and a single dependent variable. It is often used to predict the value of the dependent variable based on the values of the independent variables.

2. What is the purpose of a multiple linear regression experiment?

The purpose of a multiple linear regression experiment is to determine the strength and direction of the relationship between the independent variables and the dependent variable. This can help us understand how the independent variables affect the dependent variable and can be used for prediction and analysis.

3. How is a multiple linear regression experiment conducted?

A multiple linear regression experiment is conducted by collecting data on the independent and dependent variables, and then using statistical software to run a regression analysis. This analysis will determine the relationship between the variables and provide information on the significance and strength of the relationship.

4. What are the assumptions of a multiple linear regression experiment?

The assumptions of a multiple linear regression experiment include linearity (the relationship between variables is linear), independence of observations, normality (the data follows a normal distribution), homoscedasticity (the variance of the dependent variable is consistent across all values of the independent variables), and no multicollinearity (the independent variables are not highly correlated with each other).

5. What are some limitations of a multiple linear regression experiment?

Some limitations of a multiple linear regression experiment include the assumption of linearity, which may not always hold true in real-world situations, and the potential for multicollinearity, which can lead to inaccurate results. Additionally, the presence of outliers in the data can also affect the accuracy of the regression analysis. It is important to carefully consider and address these limitations when conducting a multiple linear regression experiment.

Similar threads

I Coefficient sign flip in linear regression with correlated predictors
    • Set Theory, Logic, Probability, Statistics
Replies
13
Views
2K
I Expected coefficient change from simple to multiple linear regression
    • Set Theory, Logic, Probability, Statistics
Replies
4
Views
1K
I Linear regression, feature scaling, and regression coefficients
    • Set Theory, Logic, Probability, Statistics
Replies
8
Views
2K
I Linear Model with independent categorical variable
    • Set Theory, Logic, Probability, Statistics
Replies
5
Views
1K
B Comparing Approaches: Linear Regression of Y on X vs X on Y
    • Set Theory, Logic, Probability, Statistics
2
Replies
64
Views
3K
A Error estimation in linear regression
    • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
I How to propagate errors through a regression & non-linear model?
    • General Math
Replies
8
Views
2K
Linear Least-Squares Regression: a_0 = ?
    • Calculus and Beyond Homework Help
Replies
3
Views
2K
How Do You Calculate Predicted Values in Least Squares Regression?
    • Calculus and Beyond Homework Help
Replies
10
Views
1K
I Collinearity between predictors: what happens under the hood
    • Set Theory, Logic, Probability, Statistics
Replies
13
Views
1K

Hot Threads

Recent Insights

Back
Top