Variable: Alumni Giving Rate | Model Summary | Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | 1 | .646a | .417 | .404 | 10.375 | a. Predictors: (Constant)‚ % of Classes Under 20 | ANOVAb | Model | Sum of Squares | df | Mean Square | F | Sig. | 1 | Regression | 3539.796 | 1 | 3539.796 | 32.884 | .000a | | Residual | 4951.683 | 46 | 107.645 | | | | Total | 8491.479 | 47 | | | | a. Predictors: (Constant)‚ % of Classes Under 20b. Dependent Variable: Alumni
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Balance($) Predictor Coef SE Coef T P Constant -3.516 5.483 -0.64 0.524 Credit Balance($) 0.011926 0.001289 9.25 0.000 S = 8.40667 R-Sq = 64.1% R-Sq(adj) = 63.3% Analysis of Variance Source DF SS MS F P Regression 1 6052.7 6052.7 85.65 0.000 Residual Error 48 3392.3 70.7 Total 49 9445.0 This MiniTab output shows the equation of the best fit line in the income. Income = - 3.52 + 0.0119 Credit
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The design and implementation of a businesses’ network enterprise can play a major role in the success of that business. This proposal will provide a solution for the Worldwide Advertising Inc. Windows network infrastructure. This proposal will include a solution for WAI’s core IT services‚ such as DNS and DHCP. In addition we will provide a solution for application services‚ active directory and file and print sharing. This proposal will also address scheduling and manpower needed for the Windows
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Table of Contents Frequencies: Statistics RESPONDED GENDER HSC GPA STUDY HOUR N Valid 75 75 75 Missing 0 0 0 Mean 1.51 4.8520 4.5600 Median 1.51a 4.9442a 4.5094a Mode 2 5.00 4.00 Std. Deviation .503 .23673 1.00324 Variance .253 .056 1.006 Skewness -.027 -1.608 .408 Std. Error of Skewness .277 .277 .277 Kurtosis -2.055 1.864 -.117 Std. Error of Kurtosis .548 .548 .548 Range 1 1.00 4.00 Sum 113 363.90 342.00 Percentiles
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QUANTITATIVE RESEARCH METHODS WEEK 1 Date: 28 March 2015 Session Time: 14:00 Course Name: Quantitative Research Methods Meeting location: Meeting Room 3 Discussion subject(s): Summary Statistics T-test One-way ANOVA Contents Introduction 3 Introductory information 3 Summary Statistics 3 Basic Definitions 3 T-test 5 Independent samples t test 5 SPSS Steps 5 One-way ANOVA 6 SPSS Steps 6 Introduction This document focuses specifically on Block/Week 1. The following topics will be covered: Introductory
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Economics of Risk and Uncertainty Applied Problem Jessica Shrewsbury BUS640 Managerial Accounting Instructor Choi February 23‚ 2015 Economics of Risk and Uncertainty Applied Problem Problem 1: A generous university benefactor has agreed to donate a large amount of money for student scholarships. The money can be provided in one lump sum of $12 million in Year 0 (the current year)‚ or in parts‚ in which $7 million can be provided at the end of Year 1‚ and another $7 million can be provided at
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a=mkdir /home/max/literature/classics‚ mkdir ~max/literature/classics‚ or mkdir ~/literature/classics b=rmdir /home/max/literature/classics‚ rmdir ~max/literature/classics‚ rmdir ~/literature /classics‚ rm –r /home/max/literature classics. 4) The df utility displays all mounted
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-----0.10 0.10 ------ Immediately mix by inversion and record the increase in A280nm for approximately 10 minutes. Obtain the r A280nm/minute using the maximum linear rate for both the Test and Blank. CALCULATIONS: Units/ml enzyme = (0.001) (0.1) df = Dilution factor 0.001 = The change in A280nm/minute per unit of Tyrosinase at pH 6.5 at 25° C in a 3 ml reaction mix 0.1 = Volume (in milliliters) of enzyme used units/ml enzyme Units/mg
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FACEBOOK‚ ACADEMIC PERFORMANCE‚ MULTITASKING AND SELF-ESTEEM Tajana Ljubin Golub‚ Ph.D. Department for Educational Sciences‚ Faculty of Teacher Education University of Zagreb‚ Croatia Marina Miloloža Department for Educational Sciences‚ Faculty of Teacher Education University of Zagreb‚ Croatia ABSTRACT Objectives of this study were to compare Facebook users and non-users on self-esteem and academic achievement variables and to investigate the factors related to perceived positive and/or negative
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009comten 0.253 .0398 0..0489 0.0055 0.0033 reg lnsalary lnsales lnmktval ceoten comten Source Model Residual Total ln_salary ln_sales ln_mktval ceoten comten _cons . SS 22.5202805 42.1259326 64.6462131 Coef. .1918844 .0940901 .0169211 -.009415 4.576374 df 4 172 176 MS 5.63007012 .244918213 .367308029 t 4.82 1.92 3.05 -2.82 18.05 P>|t| 0.000 0.056 0.003 0.005 0.000 Number of obs F( 4‚ 172) Prob > F R-squared Adj R-squared Root MSE = = = = = = 177 22.99 0.0000 0.3484 0.3332 .49489 Std. Err. .039824
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