1. MS 205 Quantitative Business Modeling
Winter Introduction
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.

2. Basic Concepts of Statistics
Statistics is concerned with:
Processing and analyzing data
Collecting, presenting, and transforming data to assist decision makers
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

3. Key Definitions
A population (universe) is the collection of all members of a group
A sample is a portion of the population selected for analysis
A parameter is a numerical measure that describes a characteristic of a population
A statistic is a numerical measure that describes a characteristic of a sample
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

4. Population vs. Sample Population Sample a b c d b c ef gh i jk l m n
o p q rs t u v w
x y z
b c
g i n
o r u y
Measures used to describe a population are called parameters
Measures computed from sample data are called statistics
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

5. Two Branches of Statistics
Descriptive statistics
Collecting, summarizing, and presenting data
Inferential statistics
Drawing conclusions about a population based only on sample data
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

6. Descriptive Statistics
Collect data
e.g., Survey
Present data
e.g., Tables and graphs
Characterize data
e.g., Sample mean =
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

7. Inferential Statistics
Estimation
e.g., Estimate the population mean weight using the sample mean weight
Hypothesis testing
e.g., Test the claim that the population mean weight is 120 pounds
Drawing conclusions about a population based on sample results.
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

8. Collecting Data Primary Secondary Data Collection Data Compilation
Print or Electronic
Observation
Survey
Experimentation
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

9. Types of Data Examples: Marital Status Political Party Eye Color
(Defined categories)
Examples:
Number of Children
Defects per hour
(Counted items)
Examples:
Weight
Voltage
(Measured characteristics)
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

10. Levels of Measurement and Measurement Scales
Differences between measurements, true zero exists
Highest Level
(Strongest forms of measurement)
Ratio Data
Differences between measurements but no true zero
Interval Data
Higher Levels
Ordered Categories (rankings, order, or scaling)
Ordinal Data
Lowest Level
(Weakest form of measurement)
Categories (no ordering or direction)
Nominal Data
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

11. Levels of Measurement and Measurement Scales
EXAMPLES:
Ratio Data
Differences between measurements, true zero exists
Height, Age, Weekly Food Spending
Temperature in Fahrenheit, Standardized exam score
Interval Data
Differences between measurements but no true zero
Service quality rating, Standard & Poor’s bond rating, Student letter grades
Ordinal Data
Ordered Categories (rankings, order, or scaling)
Marital status, Type of car owned
Nominal Data
Categories (no ordering or direction)
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

12. Business Statistics Begin as Data!
Sales for all 50 McSorley’s stores for December 31, 2005.
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

13. Visualizing Data: the Histogram
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

14. Summarizing & Conveying Data
Minimum
Maximum
Range
Mean
Median
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

15. Inferring from a Sample
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

16. Sampling Distributions & Interval Estimatesx
If means of random samples of size 10 were compiled, they would have their own histogram.
This indicates a sampling distribution, and leads to an interval estimate for the population:
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

17. Inferring from Samples from Two Populations
Sales for all 50 Wonder’s stores for December 31, 2005.
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

18. Are you 95% sure that Wonder’s mean sales exceed McSorley’s?
Ho: M  W; McSorley’s mean sales is no less than Wonder’s
Ha: M < W; McSorley’s mean sales is less than Wonder’s
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..

19. Are you 95% sure that Wonder’s mean sales exceed McSorley’s?
Compare test statistic z= to critical value z.05=
Conclusion: Reject Ho
Area = .95
Reject Ho
Do not reject Ho z
z=-4.867
z.05=-1.645
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc..