CHAPTER 3 Methodology A.Research Design: In order to gather the necessary data, the researchers used descriptive method. It includes techniques that are used to summarize and describe numerical data for the purpose of easier interpretation . A survey was administered to 38 students from the Philippine Women's College of Davao , Grade 10 Probity. It is an important tool for collecting and analyzing information from selected individuals. B. Research Instrument The researchers designed a questionnaire
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Examination Quiz / Class Test Class Participation Group Activity : : : : 25 10 05 10 • Total : 50 2 Session 1: Learning Objectives • Explain how information management delivers value to an organization. • Demonstrate the relationship between data, information and knowledge. • Identify key management issues of information and the perspective of information System 3 Today’s business environment Changes & driven by 4 The Emerging Digital Economy • To get a market of 50 Million People
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costs, including direct/indirect, tangible/intangible, programmatic, opportunity, etc -Valuation of benefits and costs -Discounting -Consideration of equity -Data Collection -Decision Criteria -Reliability & Validity -Scope & Limitations -Summary Chapter IV: Data Analysis – -Introduction -Description of Data Sources -Data Analysis & Synthesis -Summary of Analytical
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Analysis of data Qualitative data Data is a subjective description in words which varies depending on who is recording it (it is open to interpretation) such as a description of housing quality * In its simplest form this could be an analysis of some graphs. This is quick, visual and shows the obvious anomalies. * One of the simplest approaches to qualitative analysis is to see if two variables are related by using a scatter graph. A line of best fit will show the correlation between the
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| Internet of Things | 2014| Pragya Vaishwanar | Aricent Marketing Research Report | Summary It’s fair to say that more people have heard of the “internet of things” than have experienced it. More objects are becoming embedded with sensors and gaining the ability to communicate. The resulting information networks promise to create new business models, improve business processes, and reduce costs and risks. There is breathless press coverage of the phenomenon—always patiently re-explained
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Time Study / Work Sampling “Lab” Report Objective 1. To perform a time and motion data analysis of an assembly task and compute the mean and standard deviation of the times recorded. 2. To discuss and analyze the set of data from (1), analyze current method, and figure out possible approaches to simplify the job and improve overall productivity. 3. To analyze the activity-time study for the secretary and compute % of time spent on each activity using different methods. 4. To develop
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An arrow for displaying sort and filter commands is added to each column label in a table. b) In a table that contains a company’s employee data, a filter could be used to display only the employees in a specific department. c) It may be necessary in order to sort or filter the data by last name. 3. One way to avoid data entry errors is to specify data entry criteria for a cell or range of cells. 4. It would be useful to use a PivotTable if a states school’s performance scores were in a
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static loading effect of stress concentration is not very serious but for brittle materials even for static loading it is important. From the Table 1.1 and Figure 1.1, there are slightly different of experimental data when compared to the theoretical (ideal) data. The experimental data are collected after do simulation of stress analysis
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(2 hours) a) Create an efficient database structure that minimises data duplication. Ensure you use all and only the fields provided Screen-print relationships in the database, making sure table names, field names and relationships can be clearly seen b) Use the correct date types and key fields for your database. Produce screen-prints in DESIGN view of each of your tables showing only the field names, data types and primary keys c) An efficient database must include suitable
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MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat jeff@google.com, sanjay@google.com Google, Inc. Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Many real world tasks
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