DATA COLLECTION Business Statistics Math 122a DLSU-D Source: Elementary Statistics (Reyes‚ Saren) Methods of Data Collection 1. 2. 3. 4. 5. DIRECT or INTERVIEW METHOD INDIRECT or QUESTIONNAIRE METHOD REGISTRATION METHOD OBSERVATION METHOD EXPERIMENT METHOD DIRECT or INTERVIEW Use at least two (2) persons – an INTERVIEWER & an INTERVIEWEE/S – exchanging information. Gives us precise & consistent information because clarifications can be made. Questions not fully understood by the respondent
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chapter 1: STATS – STATISTICS DATA AND STATISTICAL THINKING 1.1 The science of statistics * Statistics - is the science of data. It involves collecting‚ classifying‚ summarising‚ organising‚ analysing‚ and interpreting numerical information. 1.2 types of statistical applications in business * Descriptive Statistics - describe collected data. Utilizes numerical and graphical methods to look for patterns in data‚ summarize the information in the data and to present the information in a
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Censored data & Truncated data Censoring occurs when an observation or a measurement is outside the range and people don’ t know the certain value. The value is always above or below the range that people set. However‚ truncated data means that because of the limits‚ such as time‚ or space‚ people lose some data. Truncation is to cut off the data. In other words‚ we have collected and use the data‚ but the data is not in the range we have. It is called censored data. We don’t use the data because
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Running head: DESCRIPTIVE STATISTICS PAPER Descriptive Statistics Paper Mickey Gahan‚ Tony Goss‚ Gerry Camacho and Rob Jacobson University of Phoenix Research Process Paper Few sports have had the social impact that baseball has had over the years. Baseball has long been the all-American pastime. Baseball parks in most major cities across the U.S. attract families including children with dreams of becoming
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DATA COMPRESSION The word data is in general used to mean the information in digital form on which computer programs operate‚ and compression means a process of removing redundancy in the data. By ’compressing data’‚ we actually mean deriving techniques or‚ more specifically‚ designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms‚ including both compression and decompression. Data Compression
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Statistical Data Analyses Graeme Ferdinand D. Armecin‚ MHSS Outline of Presentation Overview of Research Designs Functions of Statistics Sampling Principles of Analysis and Interpretation (with Computer Package) – Descriptive Statistics – Inferential Statistics Graeme Ferdinand D. Armecin‚ MHSS Statistical Data Analyses Purposes of Research Design Exploratory/Descriptive Research design – Basic or fundamental in the research enterprise – What is going on? –
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STANDARD COSTING VARIANCES Materials Actual Production X X X Vs. Standard Usage Standard Price Actual Usage Actual Production X X X Vs. Standard Usage Standard Price Actual Usage Actual Price Actual Price Total Variance Actual Production X X X Vs. Standard Price Actual Usage Actual Usage Actual Production X X X Vs. Standard Price Actual Usage Actual Usage Price Variance Actual Price Actual Price Standard Price Standard Price Actual Usage
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Submitted: November 12‚ 2013 Date Due: November 12‚ 2013 BUS – 320 Business Research Methods Research Analysis – Environmental Sustainability of Hotel Industry TABLE OF CONTENTS 1. List of Statistical Techniques…………………………………………………………………………………………..3 2. Purpose of using the Statistical techniques…………………………………………………………………….4 3. Tab Plan………………………………………………………………………………………………………………………….5 4. Analysis and Interpretation…………………………………………………………………………………………….6 i. Chi Square Testing………………………………………………………………………………………………6
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1.5(Q3 – Q1) below the lower quartile or above the upper quartile. On graph paper draw a box plot to represent these data‚ indicating clearly any outliers. (7) Jan 2001 2) The random variable X is normally distributed with mean 177.0 and standard deviation 6.4. (a) Find P(166 < X < 185). (4) It is suggested that X might be a suitable random variable to
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Chapter 1 Multivariate analysis refers to all statistical techniques that simultaneously analyze multiple measurements on individuals or objects under investigation. Factor analysis identifies the structure underlying a set of variables Discriminant analysis differentiates among groups based on a set of variables. All the variables must be random and interrelated in such ways that their different effects cannot meaningfully be interpreted separately. Nonmetric measurement scales Nominal
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