Chap 001 stat

Chapter 1An Introduction to Business StatisticsMcGraw-Hill/IrwinCopyright 2011 by The McGraw-Hill Companies, Inc. All rights reserved.

An Introduction to Business Statistics1.1Data1.2Data Sources1.3Populations and Samples1.4Three Case Studies that Illustrate Sampling and Statistical Inference1.5Ratio, Interval, Ordinal, and Nominative Scales of Measurement 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 elementLO 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 (or categorical): the possible measurements fall into several categoriesLO 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 time(survey)Time series data: data collected over different time periodsLO 3: Describe the difference between cross-sectional data and time series data.1-*

Time Series DataLO 4: Construct and interpret a time series (runs) plot.1-*

1.2 Data SourcesExisting sources: data already gathered by public or private sourcesInternetLibraryUS GovernmentData collection agencyExperimental and observational studies: data we collect ourselves for a specific purposeResponse variable: variable of interest Factors: other variables related to response variableLO 5: Describe the different types of data sources.1-*

1.3 Populations and SamplesLO 6: Describe the difference between a population and a sample.1-*

PopulationThe 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 population

Descriptive Statistics and Statistical InferenceDescriptive statistics: the science of describing the important aspects of a set of measurements ex: comparison of 2 males/

Statistical inference: the science of using a sample of measurements to make generalizations about the important aspects of a population of measurementsLO 7: Distinguish between descriptive statistics and statistical inference.1-*

1.4 Three Case Studies That Illustrate Sampling and Statistical InferenceThe Cell Phone Case: Estimating Cell Phone CostsThe Marketing Research Case: Rating a New Bottle DesignThe Car Mileage Case: Estimating MileageLO 8: Explain the importance of random sampling.1-*

The Cell Phone Case: Estimating Cell Phone CostsConsidering using a company to manage their cellular resourcesRandom sample of 100 employees working in the bank on 500-minute plan last monthMany overages and underage(statistical)Sample:100Population: employee /variableExisting data/ratioLO81-*

The Cell Phone Case: The DataLO81-*

The Marketing Research Case: Rating a New Bottle DesignStudying to see if changes should be made in the bottle design for a popular soft drinkUsing mall intercept methodOn one Saturday, randomly select a sample size of 60 shoppers to interview. Experimental/cross sec/sample: 60 /popu:infinity/qualitative/ordinal convert quali to quan/ratioScore:quantitave LO81-*

The Marketing Research Case: The Form and the DataLO81-*

TermsProcess: a sequence of operations that takes inputs and turns them into outputsFinite population: a population of limited sizeInfinite population: a population of unlimited sizeLO81-*

The Care Mileage Case: Estimating MileageStudy of tax credit offered by the federal government for improving fuel economyAutomaker has introduced a new model and wishes to demonstrate it qualifies for the tax credit/subject /mileage /popu:infinite/timeseries/quantititave /ratio/experimental/mileage already thereThere are 50 consecutive production shifts, and each shift produced 100 cars. Randomly select one car from each production shifts. (i.e. a sample of 50 cars).LO81-*

The Care Mileage Case: The DataLO81-*

1.5 Ratio, Interval, Ordinal, and Nominative Scales of Measurement 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 value(grade score)Interval variable: a quantitative variable where ratios are not meaningful and there is no defined zero(weather)Qualitative variables (categorical)Ordinal variable: a qualitative variable for which there is a meaningful ranking of the categories(, freshman , senior , junior , grade A , B, C) classification Nominative variable: a qualitative variable for which there is no meaningful ranking of the categories(m vs f , rainbow)LO 9: Identify scales of measurement (optional).1-*

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