Question

Discuss in 300 words regression, analysis, assumptions?

can you please type it, it is really hard to read some handwriting?

Answer 1

Regression Analysis:

It is a statistical method to determine the relation between two or more independent variable to the dependent variable, Typically we use the linear and logistic regression for first modelling algorithms

The simple regression the general form of the equation is given by

Y=B0+B1Xi+ei   ,i=1,.....n

In multiple regression there are more than one independent variable and its equation is given by

Yi=B0+B1xi+B2xi^2+ei ,i=1,....n

Suppose Y=10+5X+e this tell that if there is no X then Y=10,If X is our increase price this inform if there is no increase in ticket price while satisficaiton increase 10 points

Dependent variable means we are trying to predict

Independent Variables are the factor that we have hypothesize have an impact on our dependent variable.For analysis the regression analysis we needs to defined the dependent variable ,In mathematical equation model dependent variable is whose value is to be determined by that equation

The logistic regression is used to describe the data of the relationship between one dependent binary variable and one or more nominal, ordinal or other independent variable,

The main five assumption as follows:

Liner relationship

Multivariate normality

No or little multicolinearity

Homoscedasticity

No Auto correlation,  

Multicolinearity occurs when the independent variable are highly correlated with each other

Its taking some criteria such as Correlation matrix Tolerance and Variance inflation Factor.

In Correlation matrix correlation coefficient is less than 1

In Tolerance the tolerance T is defined as T=1-R^2

In Variance Inflection Factor VFI=1/T

The assumption about the error term is given by:

1.The random error ei have a mean of zero, i.e.E(ei)=0

2.The random error ei have same variance

3.The random error ei are independent

4.The random error ei are normally distributed