Chapter 1 An Introduction to Business Statistics

Chapter 1An Introduction to Business StatisticsCopyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/IrwinAn Introduction to Business Statistics1.1 Data1.2 Data Sources1.3 Populations and Samples1.4 Three Case Studies that Illustrate Sampling and Statistical Inference1.5 Ratio, Interval, Ordinal, and Nominative Scales of Measurement (Optional)1-*1.1 DataData: facts and figures from which conclusions can be drawnData set: the data that are collected for a particular studyElements: may be people, objects, events, or other entriesVariable: any characteristic of an elementLO1-1: Explain what a variable is.1-*Data ContinuedMeasurement: A way to assign a value of a variable to the elementQuantitative: the possible measurements of the values of a variable are numbers that represent quantitiesQualitative: the possible measurements fall into several categoriesLO1-2: Describe the difference between a quantitative variable and a qualitative variable.1-*Cross-Sectional DataCross-sectional data: Data collected at the same or approximately the same point in timeTime series data: data collected over different time periodsLO1-3: Describe the difference between cross-sectional data and time series data.1-*Time Series DataLO1-4: Construct and interpret a time series (runs) plot.Table 1.2 and Figure 1.11-*1.2 Data SourcesExisting sources: data already gathered by public or private sourcesInternetLibraryPrivate data sourcesExperimental and observational studies: data we collect ourselves for a specific purposeResponse variable: variable of interestFactors: other variables related to response variableLO1-5: Describe the different types of data sources: existing data sources, experimental studies, and observational studies.1-*1.3 Populations and SamplesPopulationThe set of all elements about which we wish to draw conclusions (people, objects or events)CensusAn examination of the entire population of measurementsSampleA selected subset of the units of a populationLO1-6: Describe the difference between a population and a sample.1-*Descriptive Statistics and Statistical InferenceDescriptive statistics: the science of describing the important aspects of a set of measurementsStatistical inference: the science of using a sample of measurements to make generalizations about the important aspects of a population of measurementsLO1-7: Distinguish between descriptive statistics and statistical inference.1-*1.4 Three Case Studies That Illustrate Sampling and Statistical InferenceEstimating Cell Phone CostsThe Marketing Research Case: Rating a New Bottle DesignThe Car Mileage Case: Estimating MileageLO1-8: Explain the importance of random sampling.1-*1.5 Ratio, Interval, Ordinal, and Nominative Scales of Measurement (Optional)Quantitative variablesRatio variable: a quantitative variable measured on a scale such that ratios of its value are meaningful and there is an inherently defined zero valueInterval variable: a quantitative variable where ratios are not meaningful and there is no defined zeroQualitative variables (categorical)Ordinal variable: a qualitative variable for which there is a meaningful ranking of the categoriesNominative variable: a qualitative variable for which there is no meaningful ranking of the categoriesLO1-9: Identify ratio, interval, ordinal, and nominative scales of measurement (optional).1-*