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

2. 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.

3. 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)

4. 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

5. 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

6. 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

7. 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

8. 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

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

10. 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

11. 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

12. 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

13. 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

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

15. 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

16. 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

17. 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

18. 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

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

20. 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