CORPORAL PUNISHMENT RESEARCH STUDY CHAPTER 4: DATA ANALYSIS, INTERPRETATION AND PRESENTATION OF FINDINGS 4.1 INTRODUCTION To interpret something is to give it a meaning., Ttherefore, data analysis is the act of organising and reducing the data to a more manageable and interpretable form (Krüger, De Vos, Fouché & Venter, and 2005: 218). To put it more concisely, data analysis is the organisationing of raw data into more concise and intelligible data which can later be analysed (Bless & Kathuria
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credible, and meaningful to enable the incorporation of lessons learned into decision-making process of users and funders (OECD, 2010) 2. Evaluation is also can be said as a process of gathering and synthesizing proof based on empirical evidence or data and typically on social research methods (Lipsey and Freeman, 2004). 3. It emphasizes the expected and accomplished achievements, processes, the results chain, contextual factors and causality in order to comprehend accomplishments or the need. (UNEG
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III.4. Grounded theory III.4.i. Definition and distinctive features Grounded theory is a research strategy in which theory is developed from data generated by a series of observations or interviews principally involving an inductive approach. According to Goulding (2002), this method is particularly helpful for research to predict and explain behavior, the emphasis being upon developing and building theory. As much of business and management is about people’s behaviors, for example consumers’ or
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analytics technique. Predective analytics uses both new and historical data to foresee the result, activity, behavior and trends. Statistics is branch of mathematics, mainly concerns about collection, analysis, interpretation and presentation of tons of numerical facts. Statistics is used in almost every field of research. Head to Head Comparisons Predictive Analytics Statistics Definition Predictive analytics is branch of the data analytics to predict the future events. Statistics in simpler terms
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Exploratory Data Analysis Course Project Part A Subject: Applied Managerial Statistics Faculty: Curtis Allen Brown Submitted by: Christian Oji Introduction Exploratory Data Analysis (EDA): Exploratory data analysis is an approach to analyze statistical data using a variety of techniques out of which many are graphical analyses. EDA is used to dissect the data and look for the hidden patterns and correlations. Some of the graphical methods include pie charts, bar graphs, histograms, frequency
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NEOLOGISMS AND MORHOLOGICAL ANALYSIS OF GAY LANGUAGE OF STUDENTS IN SURIGAO DEL SUR STATE UNIVERSITY S.Y. 2015-2016 A Concept Paper Presented to Maria Lady Sol A. Suazo, Ph.D, Instructor Surigao Del Sur State University Tandag City In partial fulfillment Of the requirements for the Degree Bachelor of Secondary Education Major in English JOSIE ALNGOG NICOLE HOPE ARIO CRISLER ATIBULA RUBELLE HOPE BANTAYAN JANUARY 2016 INTRODUCTION The language of gays known as gayspeak has
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Performance Evaluation Study Guide 5 LEARNING OBJECTIVES At the end of this Study Guide, you should be able to: • Understand the reason why it is critical to use a separate set of data not used in the training to evaluate the performance of a model. • Describe the different validation methods to evaluate model performance. • Explain the different measures used to measure model performance, including lift chart. • Describe a systematic search process to find the
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Big data is nothing but the collection of large set data which cannot be examined with the normal conventional methods. Big data plays a huge role in different types of industries to improve their business efficiently and effectively. The role of big data is much more in business because many business takes decision based on the data. The workers collects the data relevant to the decisions making. For example, data analyst can track the customer transaction data and helps them to know what kind of
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Predicting borrowers’ chance of defaulting on credit loans Junjie Liang (junjie87@stanford.edu) Abstract Credit score prediction is of great interests to banks as the outcome of the prediction algorithm is used to determine if borrowers are likely to default on their loans. This in turn affects whether the loan is approved. In this report I describe an approach to performing credit score prediction using random forests. The dataset was provided by www.kaggle.com, as part of a contest “Give
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The Situation of Big Data Technology Yu Liu International American University BUS 530: Management Information Systems Matthew Keogh 2015 Summer 2 - Section C Introduction In this paper, I will list the main technologies related to big data. According to the life cycle of the data processing, big data technology can be divided into data collection and pre-processing, data storage and management, data analysis and data mining, data visualization and data privacy and security, and so on.
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