Regression Analysis is a very effective quantitative forecasting technique for short, medium and long range time horizons and can be easily updated and changed. Regression Analysis: presupposes that a linear relationship exists between one or more independent (casual) variables, which are predicted to affect the dependent(target) variable. Linearity: The observed relationship between the independent and dependent variables Example: A HR can use regression analysis to predict the number of personnel required to perform the work.` Regression projects the future based on the past historical relationship between the independent and dependent variables Simple Regression Prediction model

General form of a simple LINEAR FUNCTION
Y=a+bX
This equation describes any straight line. The slope of the linear relationship between X and Y is represented by the letter b. The constant(y intercept) is represented in the equation by the letter a. The dependent(tatget)vatiable is represented by Y. The independent(casual) variable is represented by X. By using this formula we can determine the values of Y Warning: When you use a regression equation, do not use values for the independent variable that are outside the range of values used to create the equation. That is called extrapolation, and it can produce unreasonable estimates.. Example: SIMULATION MODEL/REGRESSION FORECAST

TARGET STORES STAFFING FORECAST MODEL
Y = 8 + .0011(X1) + .00004(X2) + .02(X3)
Y = Number of employees needed to staff the store
X1 = Square feet of sales space
X2 = Population of metropolitan area
X3 = Projected annual disposable income in millions of dollars Y = 8 + .0011(50,000sq ft) + .00004(150,000popul) + .00000002($850 million) Y = 8 + 55 + 6 + 17
Y = 86 employees needed at this store
Regression is a valuable forecasting technique and it enables us to plan and execute recruitment, selection, training and development programs in a planned, proactive fashion to ensure the trained...

...Quick Stab Collection Agency: A RegressionAnalysis
Gerald P. Ifurung
04/11/2011
Keller School of Management
Executive Summary
Every portfolio has a set of delinquent customers who do not make their payments on time.
The financial institution has to undertake collection activities on these customers to recover the
amounts due. A lot of collection resources are wasted on customers who are difficult or
impossible to recover. Predictive analytics can...

...PREDICT ARTIRIAL OXYGEN.
1. Always start with scatter plot to see if the data is linear (i.e. if the relationship between y and x is linear). Next perform residual analysis and test for violation of assumptions. (Let y = arterial oxygen and x = blood flow).
twoway (scatter y x) (lfit y x)
regress y x
rvpplot x
2. Since regression diagnostics failed, we transform our data.
Ratio transformation was used to generate the dependent variable and reciprocal...

...partial correlation we recognize more than two variables but consider only two variables to be influencing each other, the effect of other influencing variables being kept constant. For example, in the rice production if we limit our correlation analysis of yield and rainfall to periods when the amount of fertilizers used existed, it becomes a problem of partial correlation.
iv. Linear and non-linear correlation:
The distinction between linear and non-linear correlation is...

...distribution' can be an asset for any business project.
I’m not sure how to put this in words but gives the business a picture of what the outcome could be both positive and negative outcomes.
3. Describe in at least two paragraphs the quantitative analysis approach, to include a high level overview of the importance of identifying the problem, developing a model, acquiring input data, developing a solution, testing the solution, analyzing results, and implementation....

...CWRU
Regression Project Report
OPRE 433
Tianao Zhang 12/5/2011
Introduction
According to the data I’ve received, there are 6578 observations. The data base is composed by 13 columns and 506 rows. All the explanatory variables are continuous as well as the dependent variable and there are no categorical variables. My goal is to build a regression model to predict the average of Y or particular Y by a given X. 1. Do the regression...

...Delta Song Case Analysis
Possible cost drivers that will allow us to estimate a salary cost function for Delta are: available seat miles, number of departures, available ton miles, revenue passenger miles, and revenue ton miles. The two cost drivers we chose were revenue passenger miles and available ton miles. The salaries consist of payments to pilots, flight attendants and ticket agents. Their salaries are determined by the number of passengers and cargoes and the miles or...

...RegressionAnalysis (Tom’s Used Mustangs)
Irving Campus
GM 533: Applied Managerial Statistics
04/19/2012
Memo
To:
From:
Date: April 19st, 2012
Re: Statistic Analysis on price settings
Various hypothesis tests were compared as well as several multiple regressions in order to identify the factors that would manipulate the selling price of Ford Mustangs. The data being used contains observations on 35 used Mustangs...

...STA9708
RegressionAnalysis: Literacy rates and Poverty rates
As we are aware, poverty rate serve as an indicator for a number of causes in the world. Poverty rates are linked with infant mortality, education, child labor and crime etc. In this project, I will apply the regressionanalysis learned in the Statistics course to study the relationship between literacy rates and poverty rates among different states in USA. In my study, the...