DS 265 EMU – Essentials of Business Statistics Ch 1 – Flashcards
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Data Set
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Data collected for a particular study
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Elements
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person, object, event, or other entity upon which data are collected.
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Variable
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characteristic of an element
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Quantitative
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numerical data, i.e. data that is measured on a numerical scale
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Qualitative (categorical)
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nonnumerical data, i.e. data that is calssified into categories
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Cross-sectional data
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data that is collected at the same or approximately the same time
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Time series data
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data that is collected ofver different time periods
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Existing sources
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sources already gathered by public or private sources. examples: internet, companies, industry and special interest associations, government agencies
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Experimental Study
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If the factors are under the control of analyst, then the study is an experimental study (e.g. a drug study)
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Observational Study
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If the factors are not under the control of analyst, then the study is an observational study (e.g. a survey)
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Population
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A set of all elements about which we sish to draw conclusions. (All elements of interest)
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Sample
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A subset of all the elements in the population.
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Population of data
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(measurements, observations) the set of data measured from each and every population element
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Sample of data
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(measurements, observations) a subset of data from the population
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Descriptive Statistics
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The science of describing the important aspects of a set of measurements, one of the two types of statistics
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Inferential Statistics
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The science of using a sample of measurements to make generalizations (i.e., draw an inference) about the important aspects off a population of measurements, one of the two types of statistics
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Random Sampling (Simple)
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Occurs when every unit remaining in the population has the same chance of being selected. Examples: hat method, random number table, computer generated random numbers
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Sampling a process
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When one is potentially interested in studying the population of all units that will or could potentially be produced by a process.
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A Process
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a sequence of operations that takes inputs (labor, materials, methods, machines, etc.) and turns them into outputs (products, services, etc.). Processes produce output over time. INPUTS (Auto factory)-----> Process ------> Outputs (Finished Cars)
