OBJECTIVE OF PROBLEM: Main objective of the problem is to maximize profit of the company‚ that produces milk made products and minimize shipping cost of these products to supply at different stores in the city. The main objective is achieve by using linear programming optimization methods. EXACT PROBLEM DEFINITION: A company produces milk made products such as‚ Cream‚ Skim milk‚ Full Cream Milk‚ butter and ghee. The company uses 3000000 liters of milk monthly for producing milk made goods. From
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Regression Analysis Exercises 1- A farmer wanted to find the relationship between the amount of fertilizer used and the yield of corn. He selected seven acres of his land on which he used different amounts of fertilizer to grow corn. The following table gives the amount (in pounds) of fertilizer used and the yield (in bushels) of corn for each of the seven acres. |Fertilizer Used |Yield of Corn | |120
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and union membership. We will use the technique of linear regression and correlation. Regression analysis in this case should predict the value of the dependent variable (annual wages)‚ using independent variables (gender‚ occupation‚ industry‚ years of education‚ race‚ and years of work experience‚ marital status‚ and union membership). Regression Analysis Based on our initial findings from MegaStat‚ we built the following model for regression (coefficient factors are rounded to the nearest hundredth):
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proposal summarizes what is going to be done. It consists of the following: 1) Statement of the problem – A carefully worded statement of the problem that led to analysis. 2) Summary of finding and recommendations – A list of major findings and recommendations of the study. It is ideal for the user who requires quick access to the analysis of the system under study. Conclusions are stated‚ followed by a list of the recommendations and a justification for them. 3) Details of
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MINI PROJECT ON TOPIC NEW SOFT DRINK LAUNCH IN HYDERABAD SUBMITTED TO‚ PROF. SHANTHAN BY‚ D.PRATHIK REDDY M.PAVAN REDDY Supreme beverages limited EXECUTIVE SUMMARY: This includes the company profile and its products. This also consists the target market and the segment. The company has identified the need of the soft drinks especially for the children. So the company wants to introduce the new product into the market for children but the company does not wants to confine to
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6: Multiple Linear Regression Data Mining for Business Intelligence Shmueli‚ Patel & Bruce © Galit Shmueli and Peter Bruce 2010 Topics Explanatory vs. predictive modeling with regression Example: prices of Toyota Corollas Fitting a predictive model Assessing predictive accuracy Selecting a subset of predictors (variable selection) Explanatory Modeling Goal: Explain relationship between predictors (explanatory variables) and target Familiar use of regression in data analysis Multiple
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Regression Analysis: A Complete Example This section works out an example that includes all the topics we have discussed so far in this chapter. A complete example of regression analysis. PhotoDisc‚ Inc./Getty Images A random sample of eight drivers insured with a company and having similar auto insurance policies was selected. The following table lists their driving experiences (in years) and monthly auto insurance premiums. Driving Experience (years) Monthly Auto Insurance Premium 5 2 12 9
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Applied Linear Regression Notes set 1 Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa‚ AL 35487-0348 Phone: (205) 348-4431 Fax: (205) 348-8648 September 26‚ 2006 Textbook references refer to Cohen‚ Cohen‚ West‚ & Aiken’s (2003) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. I would like to thank Angie Maitner and Anne-Marie Leistico for comments made on earlier versions of these notes. If you
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TITLE : Automatic Room Cloth Dryer System 1.0 Introduction This project is to reduce human hard work. By this project human can dry he cloth in this room without worries forget to pick up dry cloth that put inside this room. this room is dry the cloth by using sunlight. 1.1 Problem statement Normal way to dry our cloth is put outside the sunlight. But this are not able to know when dark or rain. this will cause our cloth undry and smelling.. This system helps to help protect
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Question 1: Run the regression Report your answer in the format of equation 5.8 (Chapter 5‚ p. 152) in the textbook including and the standard error of the regression (SER). Interpret the estimated slope parameter for LOT. In the interpretation‚ please note that PRICE is measured in thousands of dollars and LOT is measured in acres. Model 1: OLS estimates using the 832 observations 1-832 Dependent variable: price VARIABLE COEFFICIENT STDERROR T STAT P-VALUE
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