Marketing Proposal for Daimler Chrysler - Essay Example

 Marketing Research Proposal for Daimler Chrysler Table of contents: Executive Summary Background: brief overview of Daimler chrysler & situation overview. Definition of the Problem Research questions Research design rational Research design References Appendices Executive Summary The researchers’ aim is to point out to the effect of Faddish; Carefree; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty, with Daimler Chrysler Informational Data. The computed F was greater than the tabular values of F-statistics at 0.05 degree of freedom. There is small value of MSE denominator than the MSE numerator so the estimator is a good fit of the regression. Multiple coefficient of determination showed that the data produced a good predictions. This was stated because the adjusted R2 is closer to the unadjusted R2. Background: Based on Daimler Chrysler dataset it is been found out that there were a declined car market trend from 1990 to 2004. In 1990 there was value of 23.9 percent while in 2004 there were only 18.3 percent. This gives a wake up call to the companies under Daimler Chrysler. They checked the importance of styling and prestigious promotion to the market. And they find a way on how to attract yuppies crowds. They made a new exciting designed car without looking the shortage of capital. Definition of the Problem The objective & goal of this research is to determine there is a significant difference between the Consider Buying Dodge Viper and selected variables such as : Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty, with Daimler Chrysler Informational Data. Research questions The Researcher to achieve insights on the defined problem will build the questions as follows: A.) What steps in statistical analysis will be used to process, summarize and display Daimler Chrysler Informational Data? B.) What statistical test will be used to measure the risk associated with variables of Daimler Chrysler Informational Data? C.) What statistical treatment will be used to show existence of linear relationships between variables found in Daimler Chrysler Informational Data? D.) Is there a significant difference between the Consider Buying Dodge Viper and selected variables such as : Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty? Hypotheses: Ho : There is no significant difference between the Consider Buying Dodge Viper and other variables under Daimler Chrysler Informational Data. Data and facts: Daimler Chrysler dataset have a declined car market trend from 1990 to 2004. In 1990 there was value of 23.9 percent while in 2004 there were only 18.3 percent. This gives a wake up call to the companies under Daimler Chrysler. They checked the importance of styling and prestigious promotion to the market. And they find a way on how to attract yuppies crowds. They made a new exciting designed car without looking the shortage of capital. There were 400 rows and 31 columns in the informational data. The researcher made clusters based on his common sense. This clusters were categories based on Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty. Research design Sample Size: Clustering the dataset through commons sense, then after clustering the researcher calculated the mean of every clusters, then results will be used in multiple regression for determination of the predictors elasticity. Sample selection: All samples from the dataset were used Editing of data: Standard editing and coding procedures with SPSS: Analysis of data: Simple tabulation and cross-tabulation used. RESULTS: This section presents the analysis of the data on the study to find out if there a significant difference between the Consider Buying Dodge Viper and selected variables such as : Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty. The Multiple Regression model were used to examined the effect of the other values to Consider Buying Dodge Viper and other variables under Daimler Chrysler Informational Data. The descriptive statistics was also used in this study for the presentation purposes. Graphs 1 show the inflation of the elasticity of the variables. Graph 1 Graph 1 shows that the range of the elasticity have a limits of 10 and there was only 9 elasticity variables. It is been found out there were some variables belongs to 3 below range. This also shows that the category under Faddish got lowest range. It is notable that one variable have yield a range of one and one got two range. Three variables belongs to three range and three variables got four range. The elasticity variables were categories as 1.) Faddish; 2.) Carefreet; 3.)Paranoid; 4.) Consciensous; 5.) Irresponsible; 6.) Positive outlook; 7.) Pro-active; 8.) Responsible parenting; and 9.) Patriot/ Loyalty. The Analysis of Variance was used to determine if the selected variables such as : Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty have no effect on Consider Buying Dodge Viper. Thus, Ho: μ1 = μ2 = μ3= μ4= μ5 = μ6= μ7= μ8 = μ9, or Ho: All independent variables have an significant effect on Consider Buying Dodge Viper . The alternative is that not all independent variables have a significant effect on Consider Buying Dodge Viper . Let’s assume that there should be at most five percent chance of erroneously rejecting a true Ho. Thus we specify a level of significance of 0.05. We used F-distribution and an Analysis of variance (ANOVA)test , and next step is to define the rejection or critical region. The dfnum value is k-1, or 10-1, or 9 and the dfden value is T-k, or 399 - 9, or 390. So with α = 0.05, the critical value of F in this analysis of variance test is F0.05 (9,390) = 1.88. The decision Rule is Reject Ho in favor of Ha if the value of the computed F is greater than the value of tabulated F. Otherwise, do not reject Ho. The next step is to compute the test statistic. Find the computed F, by dividing the mean sum of square of regression value by the mean sum of square of residual value. The final step now is to make the statistical decision. Since computed F (F c) is greater than Tabulated F (Ft), Ho is rejected and thus, not all the independent variables of this study have a significant effect on the Consider Buying Dodge Viper. The result of the “Analysis of Variance” (ANOVA) shows that the computed F (32.240) is greater than the tabular values of F-statistics at 0.05 degree of freedom (1.88). The Regression results are as follows: the unbiased estimator of the variance of the error in the multiple regression model is equal to 3.927. There is small value of MSE denominator than the MSE numerator (126.597) so the estimator is a good fit of the regression. Standard error of estimate is equal to 1.98166. Multiple coefficient of determination is .427. (R2) and an adjusted multiple coefficient of determination is equal to .413 (R2) showed that the data produced a good predictions. This was stated because the adjusted R2 is closer to the unadjusted R2. conclusion: In this paper, the researcher empirically examined the success of multiple regression model. The researcher investigated if the selected variables such as : Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty have an effect on Consider Buying Dodge Viper under Daimler Chrysler Informational Data. The researcher also used Frequency distribution and analysis of variance (ANOVA). This paper examined the Daimler Chrysler Informational Data. The researcher discovered that the the selected variables such as : Faddish; Carefreet; Paranoid; Consciensous; Irresponsible; Positive outlook; Pro-active; Responsible parenting; and Patriot/ Loyalty have an effect on Consider Buying Dodge Viper under Daimler Chrysler Informational Data. This means that other variables can affect the flaws of the Consider Buying Dodge Viper. The researcher suggested the additional parameters for the greater accuracy of the model. References: [1] Aczel,Amir D.,(1996) Complete Business Statistics, 3rd Ed., Irwin/ McGraw-Hill Companies.,USA. , pp. 100 – 106,549-553, and 470 – 479. [2] Altman,E,( 1968) Financial Ratio, Discriminant Analysis and the Prediction of Corporate Bankruptcy, Journal of Finance, Vol 23, No. 4 [3] Cooke, R., (1991) Experts in Uncertainty: Opinion and Subjective Probability in Science, Oxford University Press, New York, P. 61.-68. [4] Crosbie, P. I. and Bohn, J. R.(2002) Modeling Default Risk, KMV LLC, Mimeo. [5] Culp, C.(2001), The Risk Management Process: Business Strategy and Tactics, Wiley, New York, 60 -75. [6] Gardner, Lawrence , (2006) Why businesses fail: ... and strategies for a successful turnaround, Detroiter, retrieved July 3, 2006, [7] Geroski, P. A. and Gregg, G.(1997) Coping with Regression: Company Performance in Adversity, Oxford University Press. 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McGraw-Hill pp. 36 -43, and 328- 332 [15] Spindler, A., Publication Information: Book Title: The Politics of International Credit: Private Finance and Foreign Policy in Germany and Japan, The Brookings Institution, Washington, DC., 1984, P. 37-50. [16] Vlieghe, G.(2001) Corporate Liquidations in the United Kingdom, Bank of England Financial Stability Review [17] Tudela, M and Young, G.,(2003) A Merton Model Approach to Assessing the Default Risk of UK Public Companies, forthcoming Bank of England Working, [18] Weygandt, Jerry J., Kieso, Donald E. and Kimmel Paul D. (1998) Financial Acounting, John Wiley and son Inc. 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The Different Elasticity variables based on their clusters Y X1 X2 X3 X4 X5 X6 X7 X8 X9    Legend: 6 5 5 4 4 5 5 4 4 7   y = Consider Buying Dodge Viper 9 5 6 5 5 4 5 5 5 5   X1= Faddish 8 8 6 6 4 4 4 6 4 4   X2= carefree 3 3 4 4 7 6 6 5 6 6   X3 = Paranoid 5 5 5 4 5 4 5 6 5 5   X4 = Consciensous 1 3 3 3 4 4 4 5 3 4   X5 = Irresponsible 3 7 3 5 5 6 6 5 7 6   X6 = Positive outlook 3 2 4 5 5 5 4 5 5 4   X7 = Pro-active 7 7 3 5 5 6 5 6 5 5   X8 = Responsible parenting 4 3 5 3 5 4 4 5 6 2   X9 = Patriotism/Loyatlty 2 5 4 3 6 5 5 4 6 3     8 5 4 5 4 4 3 3 4 5     6 5 3 5 3 4 4 5 5 6     1 4 3 5 4 4 4 6 6 3     3 4 6 5 6 6 5 7 4 4     6 5 4 5 3 4 5 5 6 6     1 5 4 3 6 4 4 4 5 2     9 4 7 7 6 7 6 6 5 7     9 4 7 6 6 6 6 4 4 7     7 3 6 3 6 6 3 4 4 6     9 5 5 7 6 6 6 6 5 4     2 5 5 3 5 6 4 4 6 5     2 4 4 4 5 5 4 5 5 3     8 7 7 6 5 5 5 4 5 6     8 3 5 6 6 6 6 8 6 4     5 6 4 5 6 7 5 5 4 4     1 5 4 5 2 3 4 7 3 6     3 5 2 3 5 5 6 5 4 4     7 6 3 4 2 3 3 3 3 5     9 6 6 6 6 6 5 5 4 5     3 5 4 4 4 5 5 4 5 5     6 3 7 6 5 5 3 6 5 5     9 4 4 5 5 6 5 5 6 7     8 4 6 4 6 6 5 7 6 5     5 3 4 4 4 4 4 4 5 5     4 4 5 5 7 5 5 4 3 4     8 6 6 7 6 5 5 7 5 5     9 3 7 6 6 5 5 5 6 6     6 5 6 7 4 5 5 6 4 6     2 5 5 4 5 5 4 5 6 5     8 4 6 4 3 4 4 5 7 6     5 4 4 5 6 6 6 6 6 4     6 5 6 6 4 4 5 7 4 5     5 3 5 6 6 5 5 4 5 4     5 3 4 4 5 5 5 5 4 4     3 4 4 3 4 4 5 4 6 3     7 6 5 6 4 4 4 6 5 6     6 5 5 6 5 5 5 7 5 4     4 5 5 6 7 6 6 4 5 5     5 3 3 6 2 3 4 8 6 6     9 5 5 6 5 5 5 7 3 6     2 5 4 4 5 4 4 5 4 3     8 6 6 4 5 5 6 7 5 6     2 3 4 3 3 3 4 5 5 3     8 4 8 6 4 3 4 4 3 6     7 4 5 4 7 7 7 5 5 5     9 5 7 6 5 4 4 4 5 4     4 7 5 4 3 4 4 4 5 6     3 5 4 5 5 4 5 5 5 3     3 5 4 5 6 7 4 5 5 5     4 6 5 4 6 7 6 5 5 5     1 4 5 5 6 6 4 4 5 4     3 4 4 6 5 5 5 6 5 5     6 6 6 6 5 6 6 7 5 5     6 4 7 6 6 6 6 7 6 5     5 6 6 5 5 4 5 5 5 4     2 4 3 4 6 6 5 5 6 4     4 4 5 6 4 3 5 5 7 4     2 2 5 5 6 6 6 5 5 5     8 5 7 7 4 6 6 6 5 6     7 5 6 5 4 3 5 6 6 3     7 5 4 5 3 5 4 4 6 7     6 4 6 5 7 7 5 5 7 5     1 4 6 3 4 3 3 5 6 3     1 5 4 4 5 4 4 4 5 4     9 3 3 6 6 6 6 6 3 7     4 6 5 4 4 5 4 5 4 6     4 7 6 4 5 5 4 6 6 5     6 6 5 5 7 6 7 6 6 5     9 8 5 5 5 6 5 5 5 5     1 3 5 4 5 5 5 3 6 4     6 6 6 5 5 5 5 5 4 3     9 6 8 7 6 6 5 7 5 6     6 6 6 5 4 4 5 7 5 5     2 5 5 4 5 4 4 3 6 4     8 6 5 5 6 6 6 5 6 6     6 4 4 4 6 5 5 5 5 5     3 5 3 3 4 6 4 4 7 7     5 6 5 4 4 4 4 4 4 5     3 3 4 4 5 5 4 5 4 3     6 6 6 5 6 6 5 5 6 5     8 6 5 5 6 5 3 4 4 5     2 5 3 3 5 5 4 4 5 3     5 6 4 5 5 5 4 4 5 4     6 5 5 4 5 5 6 6 5 4     7 3 5 6 2 4 5 5 4 5     7 3 4 5 6 7 5 5 5 6     5 4 5 5 5 5 5 6 6 4     7 5 6 5 6 6 6 5 6 4     6 4 5 4 5 4 5 5 5 4     3 4 4 4 5 5 4 4 5 4     5 3 5 7 4 5 4 5 5 5     8 4 7 6 7 6 6 5 3 5     8 4 4 3 4 5 5 5 5 4     1 4 8 6 5 4 5 6 3 5     9 4 6 6 6 5 6 5 6 4     8 5 6 5 6 5 5 6 5 5     8 6 4 5 7 8 7 6 4 6     7 6 5 4 4 3 4 5 6 5     5 6 6 6 7 7 6 5 4 7     2 4 4 4 3 4 3 3 4 5     2 3 5 4 7 6 6 6 6 4     3 6 6 3 7 6 4 3 7 3     8 5 6 6 5 5 5 6 6 5     2 3 4 5 4 4 4 3 5 4     2 3 4 4 2 3 4 4 6 5     8 7 6 5 6 7 5 6 5 6     9 5 6 7 4 6 5 6 5 7     5 2 3 4 3 4 5 4 6 5     6 5 6 5 5 6 4 6 4 5     7 4 5 4 5 4 5 4 7 6     4 5 6 6 5 4 3 4 6 4     6 8 2 5 5 4 4 6 5 4     5 7 4 4 7 5 5 5 5 3     8 6 6 5 6 4 6 6 7 4     4 4 4 4 3 3 4 4 4 4     7 6 7 5 6 6 4 4 6 6     8 4 6 5 3 2 5 5 5 5     2 3 4 4 3 3 3 4 3 4     1 4 6 5 6 5 5 6 7 4     7 6 5 5 3 4 4 5 5 7     9 4 6 6 3 4 4 5 5 6     7 8 4 4 5 5 5 4 7 5     5 5 5 4 4 4 5 7 5 4     5 4 6 6 5 4 5 7 5 5     9 6 5 6 4 5 6 6 6 5     9 6 5 4 5 5 4 6 5 5     9 5 6 6 5 4 5 5 5 5     7 9 4 5 5 6 6 5 5 5     3 5 5 5 6 6 5 5 6 5     8 5 6 6 3 4 5 5 6 7     9 4 7 6 5 5 3 4 2 5     8 4 5 3 3 3 5 5 6 5     4 3 6 5 5 3 5 4 6 2     8 3 6 6 3 3 4 5 5 4     5 5 5 5 5 4 5 5 3 4     5 4 4 4 3 4 5 6 5 4     8 6 6 6 7 6 5 5 3 5     4 4 3 4 2 4 5 4 5 5     3 6 6 5 7 6 6 5 7 6     7 6 5 5 5 5 4 3 6 5     1 4 5 4 5 4 4 4 7 3     2 4 4 4 4 4 5 4 6 5     1 4 5 5 5 4 6 8 5 4     1 5 5 5 5 5 5 7 3 5     7 4 6 4 5 5 5 6 5 5     5 6 5 4 3 3 5 5 4 4     5 6 3 4 4 4 5 5 5 5     1 5 4 5 5 6 4 5 6 4     4 5 6 5 8 7 5 3 5 2     1 3 4 3 3 4 4 3 4 5     2 4 4 5 4 3 6 7 6 4     9 6 5 4 6 5 5 4 4 5     7 4 4 5 6 5 6 8 5 3     6 5 5 5 6 6 4 5 6 4     9 5 5 6 6 7 6 6 4 7     9 5 6 5 5 5 5 5 5 6     6 4 6 3 7 7 5 4 6 5     5 4 6 5 6 7 5 5 6 6     4 4 5 5 6 6 5 5 5 6     3 4 3 4 4 4 5 7 5 2     6 5 6 4 7 6 5 4 5 3     6 5 5 6 5 5 6 6 5 4     4 4 6 4 4 4 3 5 5 4     5 3 6 5 5 5 3 4 5 6     7 5 5 7 5 5 5 8 4 6     2 4 4 5 5 6 5 5 4 6     6 2 4 4 5 6 5 4 2 4     5 4 6 5 5 4 4 4 6 4     6 5 5 5 5 5 5 5 4 5     3 4 3 5 2 3 4 6 4 5     8 6 6 6 4 4 5 7 6 5     2 4 3 3 6 6 5 6 6 4     5 6 5 5 6 6 6 4 5 4     3 6 3 4 3 4 4 5 4 4     4 5 4 4 5 4 5 5 6 4     2 6 5 5 6 5 4 5 3 4     3 4 5 5 7 6 6 4 5 5     8 8 4 6 5 6 5 6 3 6     3 3 5 4 3 3 5 4 5 4     9 4 6 5 3 5 6 6 7 7     1 1 2 3 5 6 5 3 6 6     3 2 2 4 6 7 5 7 6 6     1 4 3 4 5 5 4 4 5 3     2 3 4 4 5 5 4 5 8 5     5 5 5 5 5 5 5 5 6 6     1 4 5 4 5 3 4 4 5 3     5 6 4 3 5 6 5 4 3 6     6 6 6 5 5 5 5 5 5 6     7 6 6 5 4 4 5 5 4 5     1 4 3 3 6 7 3 2 5 4     1 3 5 4 2 3 3 5 4 4     1 3 3 3 5 6 5 4 5 5     4 4 5 6 5 5 4 5 4 5     4 5 4 5 4 5 5 6 6 7     8 4 7 5 7 7 5 4 5 6     4 4 5 5 5 4 4 5 6 3     7 6 5 6 4 3 4 6 5 5     4 4 4 4 4 4 5 6 4 5     4 5 6 5 6 5 6 4 5 5     2 4 4 5 6 7 4 4 6 4     6 6 3 5 4 4 6 6 5 5     6 6 6 6 7 5 6 5 6 5     6 6 6 3 4 3 4 5 4 4     7 6 6 5 6 4 5 5 6 4     2 3 3 4 3 4 4 5 4 5     9 5 6 5 6 6 5 6 6 7     4 4 7 6 5 4 4 5 6 6     1 5 4 4 4 5 4 4 6 4     9 7 6 6 5 6 5 6 5 5     3 5 6 5 5 3 4 4 4 2     5 3 6 5 6 6 6 4 5 7     7 6 7 7 5 5 6 7 5 6     2 4 4 4 5 5 4 4 5 5     2 4 6 5 6 6 6 6 3 5     8 6 5 7 5 4 4 5 5 5     9 4 5 6 3 4 4 7 6 4     2 4 4 4 6 5 4 2 7 3     4 5 5 4 7 6 5 5 4 3     1 3 5 3 4 4 4 2 5 5     7 3 6 5 5 5 5 6 5 6     1 2 4 3 5 5 5 3 6 5     3 4 6 5 4 3 4 5 6 3     6 5 4 6 5 4 5 6 5 3     2 5 5 4 5 5 5 5 5 4     6 5 6 5 6 5 4 4 5 3     2 1 4 4 5 6 6 6 6 6     8 5 5 5 6 6 7 6 6 7     4 5 4 5 5 4 5 5 5 4     4 2 6 5 6 6 6 7 4 6     1 5 4 5 3 3 4 5 3 3     1 5 5 4 5 5 5 4 6 6     2 4 5 3 4 4 3 4 4 3     2 3 4 4 2 2 3 4 4 3     8 6 6 5 4 5 5 5 3 6     3 4 5 3 6 6 3 4 5 6     3 4 6 4 6 5 6 7 6 4     3 5 3 4 5 5 5 4 5 5     1 5 3 4 5 5 4 4 6 3     1 3 2 3 5 6 5 5 4 4     6 5 4 4 5 4 5 4 7 4     8 4 6 6 4 5 6 7 5 6     3 4 6 5 6 6 3 3 6 5     7 7 6 5 4 5 5 5 5 5     5 5 4 6 5 5 5 6 5 5     9 6 6 5 3 3 3 4 7 5     8 6 4 6 4 5 6 5 7 6     3 3 5 4 5 7 5 5 6 7     5 5 6 6 5 4 6 6 5 4     6 5 5 5 6 6 4 4 6 6     3 5 4 3 5 5 5 3 6 5     4 4 5 5 6 6 5 4 6 7     6 3 5 5 5 3 5 5 6 4     1 4 5 6 5 5 4 6 5 5     1 4 5 4 4 4 5 5 6 5     5 4 7 4 7 5 3 3 5 3     6 7 5 6 5 5 4 3 5 5     6 4 4 5 6 5 5 6 6 5     9 6 6 6 5 5 4 5 6 6     6 6 3 4 4 5 6 5 6 4     9 6 4 6 3 4 4 5 6 7     9 4 6 6 5 5 4 6 6 5     6 5 5 4 3 5 4 6 7 6     7 4 6 5 4 4 4 5 4 3     3 4 5 4 6 7 5 4 4 7     8 5 3 5 7 7 7 6 4 6     4 3 4 5 3 3 3 4 5 5     2 6 2 5 4 5 5 6 5 5     6 4 5 4 7 7 5 4 3 5     4 7 5 5 6 5 6 5 7 5     8 6 6 7 4 3 6 7 7 4     3 3 4 5 6 4 4 7 5 3     3 3 4 4 4 4 5 5 6 4     6 6 5 4 5 3 5 3 3 3     4 4 5 5 4 5 4 3 5 6     4 5 4 3 3 3 5 6 5 3     9 5 5 6 6 7 5 5 3 8     5 4 5 5 4 4 3 3 5 5     6 3 5 4 8 8 6 5 4 6     4 3 4 5 6 7 6 4 6 5     5 5 6 5 6 5 5 6 7 5     3 5 3 3 3 3 5 5 5 4     3 4 4 3 5 5 4 3 3 3     2 5 7 5 4 4 5 5 4 5     5 6 5 4 3 3 4 6 6 4     9 6 6 6 7 6 5 4 8 6     5 4 4 5 4 4 6 7 4 3     1 4 4 4 5 5 5 4 5 4     3 3 4 4 4 5 6 6 5 5     4 5 3 5 4 4 4 3 4 5     3 5 3 6 5 6 6 6 6 5     6 4 6 5 6 6 5 5 5 7     8 6 6 5 5 6 5 4 5 6     1 6 4 4 4 3 4 5 5 3     5 6 5 5 5 5 6 7 4 5     3 4 3 3 4 4 2 3 5 3     4 4 5 4 5 6 4 5 6 5     8 5 4 6 6 6 6 7 7 5     2 6 4 4 5 5 4 5 6 5     5 5 4 4 4 4 4 3 5 4     3 5 4 4 5 4 4 3 6 4     2 2 4 4 8 7 6 4 4 4     3 5 4 4 5 5 4 5 3 4     2 4 6 4 5 4 5 5 5 3     5 5 6 4 5 4 5 5 5 3     8 4 3 6 6 6 6 5 5 4     3 5 5 5 5 4 5 5 5 2     1 3 5 4 6 7 5 5 6 5     6 3 6 4 4 5 5 4 4 6     3 6 4 3 5 5 5 6 6 3     7 5 6 5 8 6 6 5 7 4     8 6 7 4 6 5 5 4 7 4     9 3 6 7 2 2 4 5 5 4     2 3 5 5 6 6 5 5 3 4     3 5 7 5 6 6 5 5 3 4     5 2 6 6 8 6 5 4 7 5     7 5 7 6 7 7 4 7 8 6     7 5 4 5 2 3 5 5 5 6     3 4 4 3 4 3 4 5 5 4     7 7 5 4 6 6 4 3 5 4     3 3 5 5 6 6 5 6 5 4     9 6 5 4 4 4 6 6 6 5     2 4 6 4 4 4 4 4 5 4     9 5 6 5 6 6 5 5 5 3     3 3 5 4 5 5 5 5 5 5     9 6 5 4 5 4 3 5 5 3     2 4 4 5 4 3 3 4 4 5     8 3 5 6 5 6 4 5 5 5     9 4 5 5 5 5 6 6 6 3     5 4 4 5 6 5 6 6 7 4     1 6 5 5 4 5 5 6 6 5     9 4 5 8 5 5 5 5 7 6     9 4 5 6 7 7 6 6 4 7     1 6 5 5 3 4 4 6 4 5     8 5 5 6 5 5 6 6 5 7     7 6 4 6 4 4 6 7 5 5     1 5 6 5 5 4 5 5 6 4     4 7 6 4 6 4 5 5 6 4     9 5 5 6 6 7 6 8 5 6     3 4 5 5 5 5 5 4 5 5     4 4 3 3 3 5 5 3 6 5     9 9 5 5 5 6 6 6 5 5     1 2 6 5 6 5 5 4 4 3     3 5 5 5 6 7 4 3 4 6     9 5 7 6 3 4 5 6 8 5     1 3 5 3 3 4 3 4 2 4     5 4 4 2 7 8 5 5 5 6     2 3 4 4 4 4 4 6 5 5     7 5 6 4 6 5 5 6 6 5     9 5 5 4 6 6 5 4 4 6     6 3 5 5 4 4 3 4 6 3     5 4 5 5 6 6 4 4 7 5     7 3 3 5 6 5 5 6 4 3     4 5 5 4 5 5 5 5 5 5     6 3 5 5 5 5 4 5 4 5     1 3 2 3 5 5 4 4 6 3     4 2 6 5 5 4 5 4 5 3     2 4 3 4 4 4 4 6 6 3     7 4 5 5 4 4 4 6 4 5     5 6 7 5 4 6 5 5 6 7     4 6 3 4 4 4 4 4 7 3     5 5 5 5 4 3 4 5 3 5     9 6 6 5 6 6 4 4 6 5     5 7 5 4 6 5 4 4 6 4     5 6 7 7 7 6 6 7 5 6     5 4 6 5 5 5 5 6 4 5     2 4 3 5 3 5 3 3 6 6     4 3 4 5 5 5 5 6 5 5     1 4 5 4 4 5 4 6 6 6     8 4 5 5 2 5 5 4 7 6     7 4 5 6 5 5 6 5 5 7     9 4 5 6 4 4 5 6 4 5     6 5 6 4 4 4 5 4 5 4     8 5 5 5 6 6 5 5 5 5     1 4 4 2 5 5 4 4 4 3     5 5 7 5 6 6 5 4 5 5     9 4 5 6 4 4 5 7 7 7     9 6 5 6 6 7 6 7 6 7     9 7 6 5 3 3 5 6 4 4     9 4 5 7 5 5 5 6 7 5     1 4 4 3 6 4 3 2 5 3     3 4 5 4 6 6 5 4 5 5     3 4 5 5 4 5 3 5 4 7     7 5 7 4 6 5 7 5 6 2     2 4 4 5 7 6 5 5 5 4     5 5 4 5 5 4 7 6 4 4     6 4 6 4 5 5 5 3 6 6     1 4 4 4 3 5 4 7 3 4     5 6 5 6 4 5 7 7 5 6     8 6 6 7 5 4 4 6 6 4     Regression Variables Entered/Removed(b) Model Variables Entered Variables Removed Method 1 X9, X4, X1, X8, X7, X2, X6, X3, X5(a) . Enter a All requested variables entered. b Dependent Variable: Y Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .653(a) .427 .413 1.982 a Predictors: (Constant), X9, X4, X1, X8, X7, X2, X6, X3, X5 ANOVA(b) Model Sum of Squares df Mean Square F Sig. 1 Regression 1139.375 9 126.597 32.240 .000(a) Residual 1531.422 390 3.927 Total 2670.797 399 a Predictors: (Constant), X9, X4, X1, X8, X7, X2, X6, X3, X5 b Dependent Variable: Y Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -6.700 .895 -7.484 .000 X1 .470 .080 .231 5.886 .000 X2 .478 .101 .213 4.739 .000 X3 .767 .122 .303 6.260 .000 X4 -.096 .146 -.045 -.659 .510 X5 -.013 .159 -.006 -.081 .936 X6 .356 .138 .124 2.573 .010 X7 .022 .105 .010 .213 .831 X8 .055 .092 .023 .605 .546 X9 .417 .111 .191 3.758 .000 a Dependent Variable: Y Read More