Course Description This course prepares students to apply statistics and probability concepts to business decisions. Students learn important criterion for developing effective research questions, including the creation of appropriate sampling populations and instruments. Other topics include descriptive statistics, probability concepts, confidence intervals, sampling designs, data collection, and data analysis – including parametric and nonparametric tests of hypothesis and regression analysis
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Data to Knowledge Analysis Patricia Warble University of Maryland April 26, 2015 Data to Knowledge Analysis It is estimated that at least 94% of the U. S. population have at least one cardiovascular/stroke risk factor, with major risk factors (diabetes, hypertension, hyperlipidemia, smoking, obesity) in at least 38% (Roger, et al., 2012). The presence of peripheral arterial or carotid disease detected during community cardiovascular screening changes risk stratification. Evidence-based treatment
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Dhaka, Bangladesh Gulshan 2, Dhaka-1212, Bangladesh EDUCATION: Post Doctoral Industrial Statistics, (Concentration: Quality Improvement) September 2002 University of Calgary, Alberta, Canada. Research: Modeling censored data for quality improvement from replicated design of experiments. Ph.D. Industrial Engineering, (Area: Production Management and Applied Statistics.) September 1999 Northeastern University, Boston, USA. Thesis: Analysis of censored
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essential in the analysis of most laboratory experiments. Association: A relationship between two variables. Bar chart: A picture in which frequencies are represented by the height of a set of bars. It should be the areas of a set of bars, but SPSS Statistics ignores this and settles for height. Bartlett’s test of sphericity: A test used in MANOVA of whether the correlations between the variables differ
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Statistics in Psychology Team B April 5, 2014 PSY/315 Nancy Walker Many people find the topic of statistics to be very difficult and a world of confusion. If asked, most would simplify statistics to being a breakdown of information using those colorful charts and graphs. This paper will give a brief introduction into the world of statistics by examining the differences between descriptive and inferential statistics, as well as, introduce some key terms that are frequently used. It
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1. Introduction Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). Cluster analysis is an unsupervised form of learning, which means, that it doesn't use class labels. This is different from methods like discriminant analysis which use class labels and come under the category of supervised learning. K-means is the
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Understanding Business Research Terms and Concepts: Part 4 Que McMannis Res 351 03/17/2015 Mark Robinson Abstract The three most commonly used research instruments in quantitative research Studies include Questionnaire, Tests, and Surveys. Validity is the degree to which an instrument measure what it is purports to measure. Imprecise information collection can influence the outcome of a study and eventually lead to unacceptable results. Reliability is the internal consistency or stability
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.......................................................................1 Interactive Mode versus Syntax Mode ..........................................................................................................................2 Descriptive Statistics .....................................................................................................................................................4 Transformations..............................................................................
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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
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A Handbook of Statistical Analyses using SAS SECOND EDITION Geoff Der Statistician MRC Social and Public Health Sciences Unit University of Glasgow Glasgow, Scotland and Brian S. Everitt Professor of Statistics in Behavioural Science Institute of Psychiatry University of London London, U.K. CHAPMAN & HALL/CRC Boca Raton London New York Washington, D.C. Library of Congress Cataloging-in-Publication Data Catalog record is available from the Library of Congress This book contains
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