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Regression analysis

Introduction

Basically it includes the techniques for modeling and analyzing numerous variables, it is used when there are relationship between dependent and independent variables.

Dependent variable

A dependent variable in a problem is a parameter of the problem varies under the influence of other parameters of the problem (which themselves may vary, and are either more dependent variables, either independent variables ). This usually corresponds to the parameters endogenous , we seek to characterize.

For example, in a problem of fluid mechanics , the forces of pressure , the temperature , the field of speed Are dependent variables, because their changes are controlled by variations in the time and the space (independent variables), and in many cases by changes in other dependent variables (e.g., the advection has a component related to the spatial variation of a dependent variable, controlled by the velocity field, which can be a dependent or independent according the problem studied: pure advection, advection-diffusion, etc.) (Salkind, 2007, 78-89)

Independent Variable

An independent variable in a problem is a parameter that varies the problem without being influenced by other parameters of the problem. This usually corresponds to the parameters exogenous or imposed by nature. For example, a mechanical problem not relativistic, the time and spatial coordinates are independent variables. Their influence by changing the cons of the dependent variables of the problem.

Descriptive Statistics

Descriptive statistics are basically used to define the fundamental features of the information/data in a study. The purpose of descriptive statistics is basically to provide simple and easy way of summarizing about the sample and also summarizing about the measures of that sample. Together with simple graphical analysis, this descriptive statistics is used to analysis the quantitative data.

Descriptive Statistics

Mean

Std. Deviation

N

Gross Sales

9.6305E4

59776.56575

50

Noncom

2.0000

1.39971

50

Populationin10km

65.5960

42.90470

50

AvgIncome

4.8680E4

23321.10613

50

AvgNocar

1.2700

.73297

50

MedianAge

5.1780

4.31652

50

In this descriptive statistics table it can be seen the dependent variable that is gross sales' mean is around 9.6 where as its standard deviation is about 59776.56, the other independent variables are as following number of competitors' mean is about 2 and its standard deviation is about 1.39, population within 10 km mean is about 65.59 and its standard deviation is 42.9 ,average income variable mean is about 4.8 and standard deviation of its is 23321.10 , average number of cars used within that area its mean is about 1.27 and its standard deviation is about .7329 , the last independent variable is median average age within that area and its mean is calculated about 5.17 and its standard deviation is about 4.3.

Variables Entered/Removed

Model

Variables Entered

Variables Removed

Method

1

MedianAge, AvgIncome, No of Comp, Populationin10km, AvgNocara

.

Enter

a. All requested variables entered.

b. Dependent Variable: Gross Sales

Here in this table the entered method is being used the dependent variable is gross sales and the other variables are independent variables

ANOVAs

The analysis of variance is a statistical technique fundamental. As its name does not indicate, it aims to compare averages over several samples.

Terms of Use and cons Warnings

A comparison of averages of two samples is possible with the Student t test or z test using the normal law ...