...Assignment on: Paul Tillich’s Theological Method of Correlation Submitted to: Dr. Samuel George Submitted by: Sunil K. Rajan, M. Div. – III ------------------------------------------------- Date: November 10, 2011 1.0. Introduction Paul Tillich (1886-1965) was a major figure in twentieth-century theology. After holding several academic posts in Germany, he and his family moved to the United States in November 1933. He subsequently held teaching positions at Union Theological Seminary, Harvard Divinity School, and the University of Chicago Divinity School. The author of several well-known books, he is possibly best remembered for his three-volume Systematic Theology. The present paper is an attempt to give a summary of Tillich’s theological method of correlation and offer an evaluation. 1.1. Summary of Method In his Systematic Theology, Tillich undertakes this mediating task by exhibiting a correlation between religion and culture. Tillich begins by contrasting “kerygmatic” theology with “apologetic” theology. Kerygmatic theology “emphasizes the unchangeable truth of the message (kerygma) over against the changing demands of the situation.” The relation between the two, he suggests, is like the correlation between “questioning” and “answering” in a conversation. Although Tillich maintains that the statements of apologetic theology must be based on the kerygma, his real concern is using what he terms “the ‘method of correlation’ as a way of uniting message and situation...
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...d(x,2) d2x(t) = dx(t) – dx(t-1) = (1-B)^(2)x(t) taking first differences twice Generate / d12x = d(x,0,12) d12x(t) = x(t) - x(t-12) = [1-B^(12)]x(t) seasonal difference for monthly data Generate d12_1x = d(x,1,12) d12_1x(t) = (1-B)[1-B^(12)]x(t) Geneartion of dummy variables: seasonal dummies: s=1,2,3,... Generate / ds = @seas(s) as command: series ds = @seas(s) Generate / d1 = 0 and manually in View/Spreadsheet use Edit+/p-value for x of a test statistic as command: (N-, t-, scalar p scalar p scalar p scalar p scalar p Chi2-, F-distribution) = 1 - @cnorm(x) = 1 - @cnorm(abs(x))*2 = 1 - @ctdist(x,df) = 1 - @cchisq(x,df) = 1 - @cfdist(x,df1,df2) 1-sided, right 2-sided 1-sided, right df ... degrees of freedom Determinant of correlation matrix: (as command) group grpx x1 x2 x3 x4 matrix x = @convert(grpx) group...
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...Strengths and Limitations of Correlational Design Walden University FPSY 6115-3 Understanding Forensic Psychology Research Strengths and Limitations of Correlational Design Correlational research designs are used to determine if a relationship exists between two or more variables and also describes the relationship amongst them (Stangor, 2011). The data can be results from observational research, questionnaires, or experiments and a scatterplot is often used to yield a visual of the collected data and the patterns of relationships can be described as positive linear, negative linear, nonlinear (independent), or curvilinear (Stangor, 2011). Correlational research identifies relationships between variables but does not explain a cause and effect and therefore within the design there are strengths and weaknesses. One strength of correlational research is it provides a visual image between variables in graphical form which displays the strength of the relationship. The research can be quick and easy and the predictor variables cannot be manipulated and while this design can predict a strong or not strong association between variables a main weakness is it does not imply causation which can lead to inaccurate conclusions (Stangor, 2011). Two research articles were reviewed and will be discussed to obtain a better understanding of correlational research. The first article Family and Social Factors as Predictors of Drug Misuse and Delinquent Behavior in Juveniles (Sharma, Sharma...
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...International Communications in Heat and Mass Transfer 33 (2006) 1088 – 1095 www.elsevier.com/locate/ichmt Measurement of mixing of two miscible liquids in a stirred vessel with electrical resistance tomography ☆ Sin Kim a,⁎, Andre Ngansib Nkaya b , Tomasz Dyakowski b b a Department of Nuclear and Energy Engineering, Cheju National University, Cheju 690 756, Korea School of Chemical Engineering and Analytical Science, University of Manchester, Manchester M60 1QD, United Kingdom Available online 12 July 2006 Abstract An electrical resistance tomography (ERT) system is used to measure the mixing of two miscible liquids. A data analysis method to monitor and measure the mixing process is proposed. On the basis of the reconstructed pixel conductivity data obtained from multi-plane ERT sensors, the mixing time can be measured and the best-correlated pairs of pixels are identified to determine the dispersion velocity of the secondary liquid in the primary liquid as well. Experimental results for the mixing of liquids in a stirred tank are presented. © 2006 Elsevier Ltd. All rights reserved. Keywords: Mixing; Miscible liquids; Electrical resistance tomography; Process tomography 1. Introduction Mixing is a common process in many industrial applications, but due to its complexity theoretical approaches are very limited. Monitoring or measuring the mixing properly is of great importance from the practical point of view and for the validation of theoretical models as well...
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...Vannessa Colon Ortiz Psych 313 Research Methods The Interpretation of Significant Correlations A 186 people that were surveyed, on a scale of 1-5, 1 being the lowest 5 being the highest: Importance: 1. Spending time each day reading Scripture. The importance of reading scripture each day was significantly related to the frequency of reading scripture each day with a positive moderate correlation of .503. The importance of reading scripture each day was significantly related to the frequency of spending time each day in prayer with a positive moderate correlation of. 483.The importance of reading scripture each day was significantly related to the frequency of spending time fasting a positive weak correlation of .199. 2. Spending time each...
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...------------------------------------------------- Impact of Training and Development on Employees Performance and Productivity Problem statement: The human resource department is the only one department wherein a good decision is being carried out from the start of hiring process up to the point of the promotion and retention. One purpose of HR is to produce a talent that would be fit in the needs of the organization and be suitable the human knowledge in their position. The idea of having a right people in the right position is not impossible through the integration of the training and development. But on How will the training can affect the productivity of the employees in service sector? Objectives of research: The main objective is to increase the understanding regarding employee’s training and development in relation to firm's performance. * Identify the major purposes of training and development, as well as the key internal and external influences on training. * Ascertain the training and development policy in operation at selected organizations (Bank of Punjab, National Bank of Pakistan, PTCL, and Ufone). * To explore the employee training contributes to their performance. To explore why Training is important for employees and firm performance. * To find out whether training and development programmers have positive effect on the performance of workers and productivity. * Outline and explain the training and development practices and...
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...competence. Since , Nursing students have a low passing rate result in board exams, while radiology technology students have a high passing rate result in their board exams. Time restraint is one factor why students failed in their academic performances Hypotheses The hypotheses for this study were as follows: H 1: There is a correlation between scores of associate degree nursing students on a general test of critical thinking skills, the CCTST, and a discipline specific critical thinking test, the Arnett CTOE tool, in the following ways: a. There is a positive correlation between the total scores of associate degree nursing students on the CCTST and the total scores of the Arnett CTOE tool. b. There is a positive correlation between the analysis subscale scores of associate degree nursing students on the CCTST and the combined analysis and interpretation subscale scores of the Arnett CTOE tool.5 c. There is a positive correlation between the evaluation subscale scores of associate degree nursing students on the CCTST and the combined evaluation and explanation subscale scores on the Arnett CTOE tool. d. There is a positive correlation between scores of associate degree nursing students on the inference subscale scores on the CCTST and the inference subscale scores on the Arnett CTOE tool. H 2: Intervening variables are associated with critical thinking in associate degree nursing students in the following...
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...|-σ | |0.5 |0.5 | |+σ |-σ | Two projects Model: |0.25 |0.25 | |+σ ; +σ |-σ ; +σ | |+σ ; -σ |-σ ; -σ | They found that under intermediate level of profitability and slack potential, the aggregation contract is preferred and the advantage is maximized. They also found that it is better to bundle projects with negatively correlated profitability when principal choose the aggregation evaluation. If the projects are positively correlated, aggregation evaluation could still be beneficial as long as the correlation is small enough. What does it mean? One of the aggregation advantages is to reduce the managerial costs of the principal. As now you treated multiple projects as one, related costs and time will relatively less for a combined project compared to the sum of the individual cost. When the principal faces the greatest conflict between reducing organizational slack and maintaining profitable production, it is...
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...EDU 695 Week 2 DQ 1 Common Core State Standards NEW To Buy This material Click below link http://www.uoptutors.com/edu-695-ash/edu-695-week-2-dq-1-common-core-state-standards-new Common Core State Standards Common Core State Standards (CCSS) establish clear expectations for student learning and are the standards for a set of learning for all students in the United States regardless of geographic location. This discussion is focused on CCSS and the role these standards take in the school setting. There are two parts to this discussion as explained below. • Part One: First, in one paragraph, summarize your understanding of the foundation of the CCSS for Math and English Arts. Next, adopting the perspective of a teacher leader, in at least two paragraphs, evaluate how CCSS (Math and English Language Arts) can be used to influence the use of technology-enhanced differentiated instructional strategies to support the needs of all learners. Finally, in one paragraph, justify why it is important to have purposeful planning of differentiated instructional strategies to promote student learning and provide at least one specific example to support your justification. • Part Two: Include a link to your ePortfolio (Pathbrite) in your initial post along with a one-paragraph reflection about your experience with the redesign for the Week One Assignment in terms of challenges you encountered and how you overcame those challenges. Be sure to include any difficulties you experienced...
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...USING EXCEL TO FIND MEASURES OF ASSOCIATION by Edward F. Stafford, Jr., PhD Professor of Management Science, UAH Purpose of Handout The purpose of this handout is to describe how to obtain measures of association between two variables using the Microsoft Excel software. These measures include covariance and correlation. For the most part, each measure may be obtained in two ways: (1) “by hand”; and (2) by Excel’s fX function operator. “By hand” does not mean to actually do the computations by hand; rather, it means to use Excel for statistical computations as though the fX function operator did not exist. Example Problem An example problem is used to demonstrate all of the features described in this handout. The problem is extracted from Case Problem 2, “National Health Care Association,” Chapter 3 of the Anderson, Sweeney, and Williams textbook assigned for this course. In particular, the “University Hospitals” data is used in this handout. The data are scales indicating respondent’s “degree of satisfaction” in their work, their pay, and their opportunities for promotion. Scale values range from 0 to 100. The actual data values used are shown in Figure 1. The user may acquire these data, user-ready, in an Excel file by going to Dr. Stafford’s home page on the web {http://cas.uah.edu/stafford/}, then clicking on the following, in order: (1) MSC 287; (2) scroll down then Special Handouts; (3) Excel Materials including Instructions for Statistical Calculations {click on...
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...Further research is necessary to provide more corroborating evidence that would further support the findings of this study. Researchers also recommend to continuously explore changes in demographic factors in order to evaluate whether these changes will affect consumer’s purchase intention as oppose to the results of this study. In addition, it is also suggested to construct the survey which is answerable by Juster’s scale (7 point scale) as recommended by marketers (East et al, 2013). 2. Managerial Suggestions Ang pangit ng sentence ko. haha Ang pangit ng sentence ko. haha The reason why consumers are not likely to buy eco-labelled products is that they are not familiar with eco-labels. Since there is a low positive linear correlation between awareness and purchase intention, marking products with eco-labels could be a viable source of competitive advantage provided that the eco-labeled products have extensive advertisement to increase perceived quality and is on par with other popular products in terms of price. Researchers suggest placing eco-labels on products with higher demand. Management should also be aware of the risks related to costs of placing eco-labels on products and enhancing consumer’s familiarity. 3. Suggestions to future researchers The researchers recommend that a study focused mainly on level of awareness on eco-labels be held to...
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...Individual Correlation Discussion BSHS/382 July 24, 2013 Vanessa Byrd Pearson product Moment is a method that is used often in order to compute any correlation between two variables showing a linear relationship. This could be used to look at how the consumption of carbohydrates plays a role in weight loss. The advantages of using this method are that an individual is able to make predictions when there is information on the correlation. When or if two variables are correlated then predictions can be made based on one variable or the other. A disadvantage of this is that even though correlation is similar to causation it does not determine the cause and often times that is forgotten. This helps to determine that there is a relationship between the variables but it cannot determine the cause. This can only be applied of the variables are not dichotomous. Spearman Rank Correlation is the most popular method used with non linear correlations and just like Pearson's it measures the relationship between two variables. Because the data used is in the form of ranks the correlation will continuously remain the same. The disadvantage is that this method is best used for data that is continuous and normally distributed which creates the ranks and cannot be used with actual data. This form could be applied when looking at test scores or a business’s monthly reports. Point-Biserial Correlation is used to estimate the degree of the relationship between a natural occurring dichotomous...
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...Squared(X - Mx)(Y - My): Product of Deviation Scores | X - Mx Y - My (X - Mx)2 (Y - My)2 (X - Mx)(Y - My) 141.00033.000-27.00066.00029.000-6.000-236.000Mx: 22.000 | 0.0950.0330.027-0.023-0.0100.002-0.121My: 0.504 | 19881.0001089.000729.0004356.000841.00036.00055696.000Sum: 82628.000 | 0.0090.0010.0010.0010.0000.0000.015Sum: 0.026 | 13.3351.075-0.717-1.546-0.302-0.00928.657Sum: 40.491 | X Values ∑ = 154 Mean = 22 ∑(X - Mx)2 = SSx = 82628 Y Values ∑ = 3.531 Mean = 0.504 ∑(Y - My)2 = SSy = 0.026 X and Y Combined N = 7 ∑(X - Mx)(Y - My) = 40.491 R Calculation r = ∑((X - My)(Y - Mx)) / √((SSx)(SSy)) r = 40.491 / √((82628)(0.026)) = 0.8717 Meta Numerics (cross-check) r = 0.8717 This is a strong positive correlation The P-Value is 0.010696. The result is significant at p < 0.05. 2. X - Mx Y - My (X - Mx)2 (Y - My)2 (X - Mx)(Y - My) -134.250171.75087.750-152.250183.75015.750-56.250-116.250Mx: 1016.250 | -11.05012.5503.550-4.4507.8501.850-9.150-1.150My: 80.750 | 18023.06229498.0627700.06223180.06233764.062248.0623164.06213514.062Sum: 129091.500 | 122.103157.50212.60219.80361.6223.42283.7231.323Sum: 462.100 | 1483.4632155.462311.512677.5131442.43729.137514.688133.688Sum: 6747.900 | X Values ∑ = 8130 Mean = 1016.25 ∑(X - Mx)2 = SSx = 129091.5 Y Values ∑ = 646 Mean = 80.75 ∑(Y - My)2 = SSy = 462.1 X and Y Combined N = 8 ∑(X - Mx)(Y - My) = 6747.9 R Calculation r = ∑((X - My)(Y - Mx)) / √((SSx)(SSy)) r = 6747...
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...A PRELIMINARY ASSESSMENT OF THE IMPACT OF E-COMMERCE TECHNOLOGIES IN SUPPLY CHAIN MANAGEMENT This empirical study assesses the organizational impact of using eCommerce technologies in supply chain management utilizing the following constructs: system quality, information quality, system usage, and user satisfaction. A sample data set was collected from maquiladoras in Juárez, Mexico to investigate relationships among these constructs. A SEM analysis was undertaken, using AMOS, on the dataset. The analysis provided statistically significant relationships among some constructs. Keywords: Supply Chain Management, eCommerce Technologies, e-Enabled Supply Chain Management INTRODUCTION The use of eCommerce technologies (the Internet/World Wide Web, intranets, and extranets) in supply chain management (SCM) is a relatively recent phenomenon. Accordingly, very few studies have been conducted to date on the extent to which eCommerce technologies have been utilized in SCM, and, more importantly, on whether or not e-enabled supply chain management (eSCM), with the use of such technologies, has brought about improvements in managing supply chains. DeLone and McLean [1] proposed interrelationships among six IS dimensions in what is referred to as the ‘DeLone and McLean (D&M) IS Success Model’. The six dimensions in the D&M model are (1) system quality, (2) information quality, (3) system usage, (4) user satisfaction, (5) individual impact, and (6) organizational impact. While DeLone and...
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...Blue Pelican Java by Charles E. Cook Version 3.0.5h Copyright © 2004 - 2008 by Charles E. Cook; Refugio, Tx (All rights reserved) 1-1 “Blue Pelican Java,” by Charles E. Cook. ISBN 1-58939-758-4. Published 2005 by Virtualbookworm.com Publishing Inc., P.O. Box 9949, College Station, Tx 77842, US. ©2005, Charles E. Cook. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, recording or otherwise, without the prior written permission of Charles E. Cook. Manufactured in the United States of America. Preface You will find this book to be somewhat unusual. Most computer science texts will begin with a section on the history of computers and then with a flurry of definitions that are just “so many words” to the average student. My approach with Blue Pelican Java is to first give the student some experience upon which to hang the definitions that come later, and consequently, make them more meaningful. This book does have a history section in Appendix S and plenty of definitions later when the student is ready for them. If you will look at Lesson 1, you will see that we go right to work and write a program the very first day. The student will not understand several things about that first program, yet he can immediately make the computer do something useful. This work ethic is typical of the remainder of the book. Rest assured that full understanding...
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