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Chapter 1 - An introduction to business statistics. After mastering the material in this chapter, you will be able to: Define a variable, describe the difference between a quantitative variable and a qualitative variable, describe the difference between crosssectional data and time series data, construct and interpret a time series (runs) plot,. | Chapter 1 An Introduction to Business Statistics Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin 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) 1- 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 LO1-1: Explain what a variable is. 1- 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 LO1-2: Describe the difference between a quantitative variable and | Chapter 1 An Introduction to Business Statistics Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin 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) 1- 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 LO1-1: Explain what a variable is. 1- 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 LO1-2: Describe the difference between a quantitative variable and a qualitative variable. 1- Cross-Sectional 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 LO1-3: Describe the difference between cross-sectional data and time series data. 1- Time Series Data LO1-4: Construct and interpret a time series (runs) plot. Table 1.2 and Figure 1.1 1- 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 LO1-5: Describe the different types of data sources: existing data sources, experimental studies, and observational studies. 1- 1.3 Populations and Samples Population The set of all elements about which we wish to draw conclusions (people, objects or events) Census An .
