Chapter 5: Linear Regression Analysis Flashcards
(29 cards)
attempts to model the relationship between a dependent variable and independent variable
Linear Regression
case where there’s only one independent variable
Simple Linear Regression
case where there are two or more independent variable
Multiple Linear Regression
used when we want to predict the value of a variable based on the value of another variable using one independent variable only
Simple Linear Regression
Linear Regression involves in:
-Finance
-Economics
-Epidemiology
-Environment Science
-Machine Learning
analyzing and quantifying systematic risk of an investment relating the return on investment to the return on all risky assets
Finance
predicting assumption, spending fixed investments, spending inventory, purchases exports and imports, demand, liquid assets, labor demand and labor supply
Economics
observational studies
Epidemiology
describing possible relationship between variables
Environment Science
one of the most fundamental supervised machine learning algorithms due to its relative simplicity and well-known properties
Machine Learning
the “predictors”
Independent Variables
the risk factors
Independent Variables
the co-founder
Independent Variables
experimenter changes or control
Independent Variables
assumed to have a direct effect on the dependent variable
Independent Variables
denoted by letter “x”
Independent Variables
X
Number of Units
the response factors
Dependent Variables
denoted by the letter “y”
Dependent Variables
being tested
Dependent Variables
dependent on the independent variable
Dependent Variables
Y
Total Cost
a
Total Fixed Cost
b
Variable Cost
