Determinants of the Level of Imports Across Countries Presented to: Prof. Angela D. Nalica School of Statistics Faculty University of the Philippines‚ Diliman In Partial Fulfillment of the Requirements of Statistics 136: Regression Analysis Presented by: Mary Ann A. Boter Michael Daniel C. Lucagbo Krystalyn Candy C. Mago April 9‚ 2009 Abstract The level of a country’s imports measures its participation and competitiveness in the international market. As such‚ it
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------------------------------------------------- Statistical analysis of the relation between Crime Rate‚ Education and Poverty: USA‚ 2009 Sonarika Mahajan 100076 Research Question In this research paper‚ analysis is done to conclude whether the level of education and poverty influence the total crime rate in the United States of America. Using descriptive statistics such a mean‚ standard deviation‚ variance‚ histograms‚ scatter diagrams and simple linear regression analysis performed upon both independent variables
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Predict ‘kicks’ or bad purchases using Carvana – Cleaned and Sampled.jmp file. Create a validation data set with 50% of the data. Use Decision Tree‚ Regression and Neural Network approached for building predictive models. Perform a comparative analysis of the three competing models on validation data set. Write down your final conclusions on which model performs the best‚ what is the best cut-off to use‚ and what is the ‘value-added’ from conducting predictive modeling? Upload the saved file with
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Assignment Week 1 Answer the following questions: 1. Describe the rationale for utilizing probability concepts. For practical reasons‚ variables are observed to collect data. The sampled data is then analyzed to elicit information for decision making in business and indeed in all human endeavors. However‚ sampled information is incomplete and not free from sampling error. Its use in decision-making processes introduces an element of chance. Therefore‚ it is important for a decision-maker
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correlated. To choose which variable should be kept‚ two regressions must be run‚ one without each variable. When evaluating these regressions‚ the variable that leads to the higher R Square value needs to
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Residual Analysis The concepts behind residual analysis for a multiple linear regression model are similar to those for a simple linear regression model. However‚ they are much more important for the multiple linear regression models because of the lack of good graphical representations of the data set and the fitted model. In simple linear regression a plot of the response variable against the input variable showing the data points and the fitted regression line provides a good graphical summary
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Factor Analysis Introduction Basic Concept of Factor Analysis Factor analysis is a statistical approach to reduce a large set of variables that are mostly correlated to each other to a small set of variables or factors. It is also used to explain the variables in the common underlying factors. (Hair et al‚ 1998) Malhotra‚ 2006 mentioned that factor analysis is also an interdependence technique that both dependent and independent variables are examined without making distinction between them
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quantitative techniques in the decision making process have proven to assist users in improving the process by quickly delivering tools and other useful information used by organizations and have resulted in more economical decisions. “Quantitative analysis has been in existence since the beginning of recorded history‚ but it was Frederick W. Taylor who in the 1900’s pioneered the principles of the scientific approach to management”. (Render‚ Stair & Hanna‚ 2009) The use and success of quantitative
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survey Sampling Fieldwork Data analysis Managerial implications Figure : the stages of customers evaluation research Normally the starting point of any research process is the research problem and research objectives. The next stage is to design plans of getting information of both quantitive and qualitative figures. Then the the objectives transform in to questionnaire. In the survey both quantitive and qualitative questions are used. Multiple choices with scale measure is used on
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Chapter 25 Discriminant Analysis Content list Purposes of discriminant analysis Discriminant analysis linear equation Assumptions of discriminant analysis SPSS activity – discriminant analysis Stepwise discriminant analysis 589 590 590 593 604 When you have read this chapter you will understand: 1 The purposes of discriminant analysis. 2 How to use SPSS to perform discriminant analysis. 3 How to interpret the SPSS print out of discriminant analysis. Introduction This chapter
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