# Aiou Code 395 Business Statistic – II Solved Assignment 2

Aiou Code 395 Business Statistic – II Solved Assignment 2 is now available in solved position. Students of I.com along with F A students of aiou can find solved assignment for this code 395. Business statistic – II assignment explain most important topic of regression and needs to differentiate the regression, regress and regressor.

## AIOU CODE 395 BUSINESS STATISTIC – II SOLVED ASSIGNMENT 2 AUTUMN 2016

Aiou subject business statistic including the regression topic and here it is explained in detail.
Regression is a statistical measure used In finance, investing and other disciplines that attempts to determine the strength of the relationship between one dependent variable (usually denoted by Y) and a series of other changing variables (known as independent variables). Regression helps investment and financial managers to value assets and understand the relationships between variables. Such as commodity prices and the stocks of businesses dealing in those commodities.

### AIOU CODE 395 BUSINESS STATISTIC – II SOLVED ASSIGNMENT 2 TYPES OF REGRESSION

The two basic types of regression are linear regression and multiple linear regression, although there are nonlinear regression methods for more complicated data and analysis. Linear regression uses one independent variable to explain or predict the outcome of the dependent variable V. while multiple regression uses two or more independent variables to predict the outcome Regression can help finance and investment professionals as well as professionals in other businesses.

Regression can help predict sales for a company based on weather, previous sales, GDP growth or other conditions. The capital asset pricing model (CAPM) is an often-used regression model in finance for pricing assets and discovering costs of capital. The general form of each type of regression is:- Y = a + bX+u
Multiple Regression:- Y = a +b1x1 + b2x2 + b3+3 + ………btxt + u
Where:-
Y = The variable that you are trying to predict (dependent variable)
X = The variable that you are using to predict Y (independent variable)
a = the intercept
b = the slope
u = The regression residual

REGRESSION:- Takes a group of random variables, thought to be predicting Y, and tries to find a mathematical relationship between them. This relationship is typically in the form of a straight line (linear regression) that best approximates all the individual data points. In multiple regression, the separate variable are differentiated by using numbers with subscript.

REGRESSAND:- In regression process the dependent variable is called regressand. It is also called as the response variable or the predict and variable or the dependent variable on the explained variable.
REGRESSOR:- In regressor process the independent variable is called regressor. It is also called as predictor variable or the independent variable or the controlled or explanatory variable.

AIOU SOLVED ASSIGNMENT 2 CODE 395 AUTUMN 2016

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