relationship between CREDIT BALANCE and SIZE 2591+ 403.221 Determine the coefficient of correlation. Interpret. .75/ r-sq(56.6%). There is a mild correlation. Determine the coefficient of determination. Interpret. 56.6% Test the utility of this regression model (use a two tail test with α =.05). Interpret your results‚ including the p-value. P-value=0. Reject the null hpothesis. T value 7.9147 Based on your findings in 1-5‚ what is your opinion about using SIZE to predict CREDIT BALANCE? Size
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32.11 | 2010 | 4284 | 3.28 | 31.23 | 2011 | 3674 | 2.65 | 24.16 | Using regression analysis we want to determine the relationship between ROA‚ ROE and stock price of PT BCA Tbk. In this case‚ ROA and ROE are the independent or explanatory variable (X)‚ while stock price is the dependent variable that we want to explain (Y). Regression Analysis SUMMARY OUTPUT | | | Regression Statistics | Multiple R | 0.13028475 | R Square | 0.016974116 | Adjusted R Square | -0.263890422
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A proposal to extend the ABC Gas Company Ltd’s gas distribution network to the NOIDA industrial cluster‚ about 40 km east of Delhi‚ at distance of about 20 kms from the ABC’s existing transmission line‚ is under the consideration of its CEO‚ Prerna Goyal. The NOIDA industrial cluster is dominated by the textiles industry including texturising‚ weaving‚ spinning and yarn units with over 2‚500 small and medium size units. The potential of gas consumption in these industries is mainly on account of
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Regression Analysis of Army Jackboots Ochirmunkh Boldbaatar‚ Myriam Hirscher‚ Bastian Latz‚ and Manuel Padutsch ECON 510 Aun Hassan November 26‚ 2012 Introduction The German company we established the data from sells cloths and shoes. The customers are not private customers but mostly national divisions like the military or fire departments. The company has around 20 stores in Germany; however‚ the stores have different prices for the same products. The data package we received includes
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Linear Regression Models 1 SPSS for Windows® Intermediate & Advanced Applied Statistics Zayed University Office of Research SPSS for Windows® Workshop Series Presented by Dr. Maher Khelifa Associate Professor Department of Humanities and Social Sciences College of Arts and Sciences © Dr. Maher Khelifa 2 Bi-variate Linear Regression (Simple Linear Regression) © Dr. Maher Khelifa Understanding Bivariate Linear Regression 3 Many statistical indices summarize information about
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Analysis on Inflation Regression Model Done by: Hassan Kanaan & Fahim Melki Presented to: Dr. Gretta Saab Due on: Tuesday‚ January 25‚ 2011 Outline: I. Introduction A. Definition of Variables B. Type of Variables II. Background and Literature Review A. Inflation and Unemployment B. Inflation and Oil Prices C. Inflation and GDP D. Inflation and Money Supply III. Analysis A. SPSS 17 analysis B. E-Views 5 analysis IV. Conclusion and Recommendation V. Indexes
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1. Affirmative Action destroys the idea of meritocracy and students should be chosen based on their intelligence instead of their race or gender. “At the University of Wisconsin‚ the median composite SAT score for blacks who were admitted was 150 points lower than for whites and Asians and the Latino median SAT score was 100 points lower”. This quote shows how Affirmative Action destroys the idea of meritocracy and applicants are mainly chosen on someone’s race not intelligence. (http://brandongaille
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• 3. „Expect the Unexpected.“David Axson • 4. Forecasting a critical business process in turbulent times. • 5. What is a forecast? Forward Looking Fact-based Flexible Focused on Risks & Opportunities • 6. „The end result ... is not an accurate picture of tomorrow‚ but better decisions about the future.“Peter Schwartz‚ The Art of the Long View • 7. Good forecasting practices create value Career Perform n ance Reputatio • 8. The traditional approach... J F M A M J J A S O
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STA9708 Regression Analysis: 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 regression analysis learned in the Statistics course to study the relationship between literacy rates and poverty rates among different states in USA. In my study‚ the poverty rates will be the independent variable (x) and literacy
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linear regression In statistics‚ linear regression is an approach to model the relationship between a scalar dependent variable y and one or more explanatory variables denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable‚ it is called multiple linear regression. (This term should be distinguished from multivariate linear regression‚ where multiple correlated dependent variables are predicted‚[citation needed] rather than a single
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