...100 percent, or the estimated numbers do not add up to the total number in the category.” The goal of this study is to show the statistical increase and decrease in the foster care population. While the population focus is based on all races that enter the foster care system. “Data was obtained from the Adoption and Foster Care Analysis and Reporting System (AFCARS). AFCARS collects information on all children in foster care for whom State child welfare agencies have responsibility for placement, care, or supervision and all children who are adopted with public child welfare agency involvement.” This study was conducted by The U.S. Department of Health and Human Services without being bias towards any race, religion, or gender. As such, there is not any evidence of being bias found in this study and based solely on statistical information. The problems I found, as stated above, was the stated fact of the children not being recorded more than once. This missing statistic would benefit the final outcome of measuring the foster care overall statistical recordings. The confounding variables stated in this study revolves around the “unknown or undetermined” race within the statistical recording. As such, the listed races are recorded as the mass majority while the undetermined are left as a bias and confounding record of what racial background these children come from. I believe the results are presented fairly...
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...concise academic statement of your plans for graduate study, your career goals, and how MSU's graduate program will help you meet your career and educational objectives. As I imagine my career plans today, it should be a combination of professional data manipulation and statistical modeling analysis to dealing with practical problems, which encourage me to pursue a higher degree in Statistics. Because some useful statistics topic in my undergraduate education were either only brought up for a definition or not covered, besides the missing value imputation method, the graphical Markov models, fixed and random effects, and variance analysis are also some of the topics I wish to learn in my graduate study. Besides advanced statistical methodology, I am particularly motivated to develop the links between statistics and computer science, although I have made every effort in studying Statistic software, like SPSS, Eviews, and Clementine, and I use my spare time learning R and C language by myself, I think there is still long way to go. I plan to further improve my programming ability, especially the options and programming techniques I didn’t know before, like the combination of C++ and R will make the loop in R run faster. With the huge amounts of data collected in the worldwide everywhere in every second, the marriage of theories, the effective methodology of numerical analysis and computer science becomes more urgent and important than ever. I believe a good statistician need also be a good...
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...Tell when to use a Pearson’s correlation, the possible research hypotheses for this statistical model, and when correlation can be used to test each type of Research Hypothesis (attributive, associative and causal). 1. A Pearson's correlation is used when you want to find a linear relationship between two variables. It can be used in a causal as well as a associativeresearch hypothesis but it can't be used with a attributive RH because it is univariate. 2. Pearson's correlation should be used only when there is a linear relationship between variables. It can be a positive or negative relationship, as long as it is significant. Correlation is used for testing in Within Groups studies. A possible research hypothesis for this statistical model would be that there is a positive linear relationship between variables. Another possible research hypothesis would be that there is a negative linear relationship. If there is no linear relationship between the variables, then we would retain the null hypothesis. 3. Pearson's correlation should be used when there is a significant effect. (p > .05) When there is a relationship between two variables. There can be a positive or negative correlation. It cannot be used when we retain the null hypothesis because then there is no relationship. It can be used if the null is rejected. 4. A Pearson's correlation is used when two quantitative variables are being tested in the RH. This cannot test attributive RH, but can associative and causal. The...
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...prepared you to do this project. Given a scenario and a dataset (see attached excel file), you are required to run regression of the dataset, and present your results in a report. In your report, you should include an introduction which describes the case, the study purpose and the demand function as an equation which you would like to estimate and regression results in table. Following the introduction, you need to include the four steps to interpret the regression results: * Step 1: interpret coefficient signs and magnitudes Hints: * negative coefficient shows that as the independent variable (Xn) changes, the variable (Y) changes in the opposite direction * positive coefficient shows that as the independent variable (Xn) changes, the dependent variable (Y) changes in the same direction * The magnitude indicates one unit changes in Xn cause the amount of changes in Y. * The regression coefficients are used to compute the elasticity for each variable * Step 2: compute elasticity coefficient and interpret the elasticities. Please use data of Store 1 to compute elasticities, as shown below: Sales (1000) | Price ($) | Advertising ($1000) | Price X ($) | Income ($1000) | 3.5 | 80 | 3.3 | 61 | 4.9 | Hints: * Price elasticity of demand: inelastic or elastic? * Cross elasticity: complement or substitution good? * Income elasticity: inferior, normal or superior good? * Step 3: Statistical evaluation...
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...Ingraham January 3, 2013 Introduction This paper will address the following questions as it pertains to data analysis approach and quantitative and qualitative result reporting for BP. “How will you have access to the population to be sampled or interviewed? What are the instruments you will use to collect data or qualitative information? What is the appropriate sampling method? What sampling frame will be used? What is the appropriate sampling size? How will the sample size be determined? Which qualitative methods will be used and why? Which statistical tests will be used and why? How will the results and insights be displayed? What conclusions should be made if the hypothesis is found to be correct or if it is incorrect?” (University of Phoenix, 2014) The paper will also “discuss the timing and resources required to conduct this research effort and how you will use the insights developed from the study to influence an improvement in the business process or attempt further research”. (University of Phoenix, 2014) Access to the Population BP has access to a large population. With the thousands of employees to the hundreds of franchise owners, BP will be able to conduct a wide variety of surveys, interviews, and focus groups. The participants will have the benefits of the study explained to them, have their rights and protections explained to them, and the conductors of the research will obtain consent (Cooper, 2014, p. 56). Participants will also be assured no physical...
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...the experimental manipulation 3 8. Stimulus sampling 4 9. Reliability and validity of measures of the independent and/or dependent variables 4 10. Confounding variables in 4 11. Order of items/events 4 The Statistical Analyses 5 1. Excluded participants 5 2. Missing data 5 3. Validity and reliability of dependent variables 5 4. Sufficient statistical power 5 5. Statistical assumptions 6 6. Correct use of inferential statistics 6 7. Correct interpretation of analyses 6 8. Alternative analyses 6 The Discussion 6 1. Alternative explanations 6 2. Cause-effect ambiguities 6 3. Third variable 7 4. Mediators and moderators 7 5. Replication 7 6. Interaction or main effect?: 7 Place the Research in the Context of Similar Research 8 Suggestions for Future Research 8 Inappropriate Criticisms 8 1. Criticizing the article rather than the research 8 2. Ethical criticisms 8 3. Incomplete criticisms 8 4. Criticisms of the reliability or effectiveness of methodology that produced the predicted results 9 5. Random allocation of participants to conditions 9 How Not to Use this Document! 10 Structuring a Critical Review 10 Useful Websites 11 Background Reading 11 References 12 The Theory You may wish to criticize the theory that the researchers are testing. How does it compare against competing theories in the area? What are its strengths and weaknesses? An excellent resource for thinking about theory construction...
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...controlled, the value of alpha is related to the level of importance that are selected as a direct bearing on type I errors. Alpha is the maximum probability that there will be a type I error. If the value of alpha is 0.05 this equates to a 95% confidence level. Meaning there is a 5% probability that a true null hypothesis will be excluded. In the long run, one out of every twenty hypothesis tests performed at this level will result in a type I error. (www.statistics.about.com, 2014). Type II error, also known as a "false negative": the error of not rejecting a null hypothesis when the alternative hypothesis is the true state of nature. In other words, this is the error of failing to accept an alternative hypothesis when you don't have adequate power. Plainly speaking, it occurs when we are failing to observe a difference when in truth there is one. So the probability of making a type II error in a test with rejection region R is 1 (is true) a − P R H. The power of the test can be (is true) a P R H. (www.stat.berkeley.edu,...
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...Select one: True False Studies that look at what has happened is what type of research Select one: a. Descriptive b. Scientific c. Alternative d. Explanatory Secondary data should be avoided: Select one: a. Where its reliability is questionable b. As the project will not then be your own research c. At all times d. Unless its original use exactly mirrors the current research project Confidentiality is compromised in a focus group as the participants will see and speak to each other. Thus, there is no requirement to keep the information obtained confidential. Select one: True False At the end of a quantitative study, a researcher simply lists the data obtained from the questionnaire and calculates percentage for each type of response. To get more meaningful statistics the next step should be? Select one: a. Echelons to the left by right marker b. Format columns of fours by outlier (wrong) c. Cross-tabulations by classification variable d. Percentages by classification variable AMI [a major New Zealand insurance company] employs a team of "data miners" whose specialist job it is to hunt for new business opportunities within the firm's extensive customer and industry database. This is an example of what research paradigm? Select one: a. Deductive Logic b. Extrapolation Logic c. Experimental Logic d. Instrumental Logic e. Inductive Logic Which of the following is/are [a] good example[s] of using the Case Study method in Management Research...
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...Statistics, University of Idaho, Moscow, Idaho 83844-1104, USA E-mail: redgeman@uidaho.edu Abstract: For decades now TQM has been a dominant management concept for improving competitiveness and financial results. In recent years, however, TQM seems to have lost some of its nimbus with other concepts and approaches such as Lean Enterprise and Six Sigma launched and increasingly in vogue. The aim of this paper is to look at TQM and Six Sigma, their backgrounds, definitions and ingredients, and their similarities and differences to see whether the two concepts really are different dishes or contain the same ingredients in different proportions. Keywords: quality; Quality Management; Six Sigma; Total Quality Management (TQM). Reference to this paper should be made as follows: Klefsjö, B., Bergquist, B. and Edgeman, R.L. (xxxx) ‘Six Sigma and Total Quality Management: different day, same soup?’, Int. J. Six Sigma and Competitive Advantage, Vol. x, No. x, pp.xxx–xxx. Biographical notes: Bengt Klefsjö is a Professor of Quality Technology and Management at Luleå University of Technology in Sweden. He has published over 100 papers in Reliability Theory and Applications and in Quality Technology and Management in International Journals and Conference Proceedings. Furthermore, he is a co-author of more than 20 published books on Mathematics, Statistics, and Quality Management. One of these, ‘Quality from customer needs to customer satisfaction’ is in its second edition sold by ASQ...
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...itself to this sort of reading. There are, however, more efficient approaches that enable you, a student of social psychology, to cut through peripheral details, avoid sophisticated statistics with which you may not be familiar, and focus on the central ideas in an article. Arming yourself with a little foreknowledge of what is contained in journal articles, as well as some practical advice on how to read them, should help you read journal articles more effectively. If this sounds tempting, read on. Journal articles offer a window into the inner workings of social psychology. They document how social psychologists formulate hypotheses, design empirical studies, analyze the observations they collect, and interpret their results. Journal articles also serve an invaluable archival function: They contain the full store of common and cumulative knowledge of social psychology. Having documentation of past research allows researchers to build on past findings and advance our understanding of social behavior, without pursuing avenues of investigation that have already been explored. Perhaps most importantly, a research study is never complete until its results have been shared with others, colleagues and students alike. Journal articles are a primary means of communicating research findings. As such, they can be genuinely exciting and interesting to read. That last claim may have caught you off guard. For beginning...
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...analysis and interpretation Concepts and techniques for managing, editing, analyzing and interpreting data from epidemiologic studies. Key concepts/expectations This chapter contains a great deal of material and goes beyond what you are expected to learn for this course (i.e., for examination questions). However, statistical issues pervade epidemiologic studies, and you may find some of the material that follows of use as you read the literature. So if you find that you are getting lost and begin to wonder what points you are expected to learn, please refer to the following list of concepts we expect you to know: Need to edit data before serious analysis and to catch errors as soon as possible. Options for data cleaning – range checks, consistency checks – and what these can (and can not) accomplish. What is meant by data coding and why is it carried out. Basic meaning of various terms used to characterize the mathematical attributes of different kinds of variables, i.e., nominal, dichotomous, categorical, ordinal, measurement, count, discrete, interval, ratio, continuous. Be able to recognize examples of different kinds of variables and advantages/disadvantages of treating them in different ways. What is meant by a “derived” variable and different types of derived variables. Objectives of statistical hypothesis tests (“significance” tests), the meaning of the outcomes from such tests, and how to interpret a p-value. ...
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...BUSINESS STATISTICS DEMYSTIFIED Demystified Series Advanced Statistics Demystified Algebra Demystified Anatomy Demystified Astronomy Demystified Biology Demystified Business Statistics Demystified Calculus Demystified Chemistry Demystified College Algebra Demystified Earth Science Demystified Everyday Math Demystified Geometry Demystified Physics Demystified Physiology Demystified Pre-Algebra Demystified Project Management Demystified Statistics Demystified Trigonometry Demystified BUSINESS STATISTICS DEMYSTIFIED STEVEN M. KEMP, Ph.D SID KEMP, PMP McGRAW-HILL New York Chicago San Francisco Lisbon London Madrid Mexico City Milan New Delhi San Juan Seoul Singapore Sydney Toronto Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights reserved. Manufactured in the United States of America. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. 0-07-147107-3 The material in this eBook also appears in the print version of this title: 0-07-144024-0. All trademarks are trademarks of their respective owners. Rather than put a trademark symbol after every occurrence of a trademarked name, we use names in an editorial fashion only, and to the benefit of the trademark owner, with no intention of infringement of the trademark. Where such designations appear in this book, they have been...
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...very few, they ought to bother many" (Journal of Management Studies, vol. 30(6), 1993). Do you agree with these statements? If so, why, and what are the implications of your beliefs for research methods in strategic management and organization science? If not, why not, and what are the implications of your beliefs for research methods in those areas? Lay out the components of the Runkel and McGrath (1972) Research Cycle and the Martin (1982) Garbage Can Model of the research process. What are the aims of either approach? What assumptions does each approach make? What basic themes does each approach emphasize? What kinds of constraints on the process of doing research does each approach highlight? How are the two approaches alike and different in other ways? What are the likely pitfalls of viewing the research process from only one of these two viewpoints? Define (and discuss important features or issues concerning) the following constructs of Philosophy and Logic of Science. (Define any four terms). 1. Null hypothesis 3. Paradigm 4. Independent variable 5. Operational definition 6. Nomological network 8. The fallacy of affirming the consequent 9. Theory 2. Logical empiricism (positivism) 7. Modus tollens A4. Organizational Studies may be described as either a basic or an applied discipline. From your point of view, is Organizational Studies a basic discipline or an applied discipline, or both? What should it be? When answering this question, be sure to define distinctions...
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...No matter where you are in the United States, when a word like racism is thrown around, its subject and all related material are bound to cause controversy and disagreements. Color blindness, or racial blindness is one of these issues associated with racial advantages or opportunities. It is a sociological term meant to disregard when discussing participation in something. My view on this issue is con-color blindness for several reasons. First of all, the United States is still not seen as truly equal when offering some opportunities. Also, there are not distinctions or classifications for people to base any kind of statistics on. For these and other reason, color blindness used nationally would not be successful in this country. Affirmative action is one case of con-color blindness. This is a method of offering opportunities to certain people according to race, gender, or religion that are misrepresented in the process. In other words, they are not getting an equal opportunity for jobs or education. I believe this helps open up chances for everyone that would normally not offered to them. It creates more of a broad spectrum in the fields of employment and education as everyone is more represented in these fields. Most Americans are split on this issue and with the introduction of racial color blindness; it has created more controversy on the subject of equality. The role of education would be changed dramatically if we did not recognize race. Several scholarships...
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...accountid=28844 Purpose of the study: This study looked into various theories on why adult online learners fail to continue their education and examined limitations of understanding learner’s behaviors. The purpose was to identify consequential factors that contribute learners to discontinue their education from online classes and eventually investigate what can be done to keep students in online classes by involving sufficient number of participants and including meaningful variables; individual characteristics, external factors, and internal factors that are also differentiated by age, gender, educational background and employment status. They also considered external factors of family support and organizational support, and students own motivations that are sub-categorized by relevance and satisfaction. The study did not look at other internal factors like social and academic integration, and technological issues. They raised two important questions that follow; 1. Do the dropouts and the persistent learners of online courses show differences in their individual characteristics (i.e., age, gender, and educational background), external factors (i.e., family support and organizational support), and internal factors (i.e., motivation in terms of satisfaction and relevance)? 2. Factors are significant to predict learners’ decision to drop out of online courses? Participants: The term” participant” refers to the sample studied. Under this heading, you should include a description...
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