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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Simple Linear Regression Model 1. The following data represent the number of flash drives sold per day at a local computer shop and their prices. | Price (x) | Units Sold (y) | | $34 | 3 | | 36 | 4 | | 32 | 6 | | 35 | 5 | | 30 | 9 | | 38 | 2 | | 40 | 1 | | a. Develop as scatter diagram for these data. b. What does the scatter diagram indicate about the relationship between the two variables? c. Develop the estimated regression equation and explain what the
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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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QUANTITATIVE METHODS:- Quantitative methods of forecasting include ASSOCIATIVE (CAUSAL) MODELS:- There is a causal relationship between the variable to be forecast and another variable or a series of variables. (Demand is based on the policy‚ e.g. cement‚ and build material. Causal Model: Demand for next period = f (number of permits‚ number of loan application....) There is no logical link between the demand in the future and what has happened in the past. There are other factors which can
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Chapter 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
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Chapter 4 Simple regression model Practice problems Use Chapter 4 Powerpoint question 4.1 to answer the following questions: 1. Report the Eveiw output for regression model . Please write down your fitted regression model. 2. Are the sign for consistent with your expectation‚ explain? 3. Hypothesize the sign of the coefficient and test your hypothesis at 5% significance level using t-table. 4. What percentage of variation in 30 year fixed mortgage rate is explained
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LINEAR REGRESSION MODELS W4315 HOMEWORK 2 ANSWERS February 15‚ 2010 Instructor: Frank Wood 1. (20 points) In the file ”problem1.txt”(accessible on professor’s website)‚ there are 500 pairs of data‚ where the first column is X and the second column is Y. The regression model is Y = β0 + β1 X + a. Draw 20 pairs of data randomly from this population of size 500. Use MATLAB to run a regression model specified as above and keep record of the estimations of both β0 and β1 . Do this 200 times. Thus you
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(架構圖、分析步驟、考慮變數(因素)、資料與調查) 2. (30%) Trip Generation Model 下列為針對淡水區進行的旅次產生調查，共分為 6 個交通分區(traffic zone)： Zone Trip production Car ownership 1 650 250 2 450 190 3 950 715 4 850 625 5 750 290 6 290 135 (1) 試建立一線性迴歸函數(linear regression model)，進行參數校估，列出校估後之函 數，並計算模式之 R2、透過 t 檢定(t-test)檢驗顯著性。 (2) 試建立一對數線性迴歸函數(log-linear regression model) (即乘冪迴歸模式) 進行參 ， 2 數校估，列出校估後之函數，並計算模式之 R 、透過 t 檢定(t-test)檢驗顯著性。 (3) 比較上述兩個模式之差異，討論孰優孰劣。 共 2 頁 第 1 頁 3. (30%) Mode Choice Model 考慮旅運者對三種運具的(負)效用函數： COSTk U k ak 0.3OVTk
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Yukl’s Multiple-Linkage Model Yukl’s linkage model of management is based on the notion of shared direction (Winston and Patterson‚ 2005)‚ between organization process and managerial influence on those processes through leadership to achieve a common goal. In plain terms at the interpersonal levels‚ the manager influences and persuades followers to work towards’ the organizational mission and objectives (Winston and Patterson‚ 2005). Types of variable in the Yukl
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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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