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**Business Statistics in Practice Seventh Edition Authors: Bowerman / O’Connell / Murphree McGraw-Hill**

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**An Introduction to Business Statistics**

Chapter 1 An Introduction to Business Statistics McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.

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**An Introduction to Business Statistics**

1.1 Data 1.2 Data Sources 1.3 Populations and Samples 1.4 Three Case Studies that Illustrate Sampling and Statistical Inference 1.5 Ratio, Interval, Ordinal, and Nominative Scales of Measurement (Optional)

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**1.1 Data Data: facts and figures from which conclusions can be drawn**

LO1-1: Explain what a variable is. 1.1 Data Data: facts and figures from which conclusions can be drawn Data set: the data that are collected for a particular study Elements: may be people, objects, events, or other entries Variable: any characteristic of an element

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**LO1-2: Describe the difference between a quantitative variable and a qualitative variable.**

Data Continued Measurement: A way to assign a value of a variable to the element Quantitative: the possible measurements of the values of a variable are numbers that represent quantities Qualitative: the possible measurements fall into several categories

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**LO1-3: Describe the difference between cross-sectional data and time series data.**

Cross-sectional data: Data collected at the same or approximately the same point in time Time series data: data collected over different time periods

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**Time Series Data Table 1.2 and Figure 1.1**

LO1-4: Construct and interpret a time series (runs) plot. Time Series Data Table 1.2 and Figure 1.1

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LO1-5: Describe the different types of data sources: existing data sources, experimental studies, and observational studies. 1.2 Data Sources Existing sources: data already gathered by public or private sources Internet Library Private data sources Experimental and observational studies: data we collect ourselves for a specific purpose Response variable: variable of interest Factors: other variables related to response variable

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**Examples of Public Economic and Financial Data Sites**

LO1-5 Examples of Public Economic and Financial Data Sites Table 1.3

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**1.3 Populations and Samples**

LO1-6: Describe the difference between a population and a sample. 1.3 Populations and Samples Population The set of all elements about which we wish to draw conclusions (people, objects or events) Census An examination of the entire population of measurements Sample A selected subset of the units of a population

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**Descriptive Statistics and Statistical Inference**

LO1-7: Distinguish between descriptive statistics and statistical inference. Descriptive Statistics and Statistical Inference Descriptive statistics: the science of describing the important aspects of a set of measurements Statistical inference: the science of using a sample of measurements to make generalizations about the important aspects of a population of measurements

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**LO1-8: Explain the importance of random sampling.**

1.4 Three Case Studies That Illustrate Sampling and Statistical Inference Estimating Cell Phone Costs The Marketing Research Case: Rating a New Bottle Design The Car Mileage Case: Estimating Mileage

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**Estimating Cell Phone Costs**

LO1-8 Estimating Cell Phone Costs Considering using a company to manage their cellular resources Random sample of 100 employees on 500- minute plan Many overages and underage

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**The Cell Phone Case: The Data**

LO1-8 The Cell Phone Case: The Data Table 1.4

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**The Marketing Research Case: Rating a New Bottle Design**

LO1-8 The Marketing Research Case: Rating a New Bottle Design Studying to see if changes should be made in the bottle design for a popular soft drink Using “mall intercept method” Sample size of 60

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**The Marketing Research Case: The Form and the Data**

LO1-8 The Marketing Research Case: The Form and the Data Figure 1.2 and Table 1.5

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LO1-8 Terms Process: a sequence of operations that takes inputs and turns them into outputs Finite population: a population of limited size Infinite population: a population of unlimited size

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**The Care Mileage Case: Estimating Mileage**

LO1-8 The Care Mileage Case: Estimating Mileage Study of tax credit offered by the federal government for improving fuel economy Automaker has introduced a new model and wishes to demonstrate it qualifies for the tax credit Sample of 50 cars

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**The Care Mileage Case: The Data**

LO1-8 The Care Mileage Case: The Data Table 1.6 and Figure 1.3

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**LO1-9: Identify ratio, interval, ordinal, and nominative scales of measurement (optional).**

Quantitative variables Ratio variable: a quantitative variable measured on a scale such that ratios of its value are meaningful and there is an inherently defined zero value Interval variable: a quantitative variable where ratios are not meaningful and there is no defined zero Qualitative variables (categorical) Ordinal variable: a qualitative variable for which there is a meaningful ranking of the categories Nominative variable: a qualitative variable for which there is no meaningful ranking of the categories

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