Statistics for Business and Economics
Chapter 1
Statistics, Data, &
Statistical Thinking
Learning Objectives
1. Define Statistics
2. Describe the Uses of Statistics
3. Distinguish Descriptive & Inferential Statistics 4. Define Population, Sample, Parameter, and
Statistic
5. Define Quantitative and Qualitative Data
6. Define Random Sample
What Is Statistics?
1. Collecting Data
Why?e.g., Survey
2. Presenting Data
e.g., Charts & Tables
3. Characterizing Data
e.g., Average
Data Analysis
Decision- Making
© 1984-1994 T/Maker Co.
© 1984-1994 T/Maker Co.
Application Areas
• Economics
– Forecasting – Demographics
• Sports
– Individual & Team Performance
• Engineering
– Construction – Materials
• Business
– Consumer Preferences – Financial Trends
Statistical Methods
Statistical Methods
Descriptive Statistics
Inferential Statistics
Descriptive Statistics
1. Involves
• Collecting Data
• Presenting Data
• Characterizing Data
2. Purpose
• Describe Data
X = 30.5 S
2= 113
0 25 50
Q1 Q2 Q3 Q4
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1. Involves
• Estimation
• Hypothesis Testing
2. Purpose
• Make decisions about
population characteristics
Inferential Statistics
Population?
Key Terms
1. Population (Universe)
• All items of interest
2. Sample
• Portion of population
3. Parameter
• Summary measure about population
4. Statistic
• Summary measure about sample
• PP in PPopulation
& PParameter
• SS in SSample
& SStatistic
Types of Data
Types of Data
Quantitative
Data Qualitative
Data
Quantitative Data
Measured on a numeric scale.
• Number of defective
items in a lot.
• Salaries of CEO's of oil companies.
• Ages of employees at
a company. 3
52
71
4
8 943
120 12
21
Qualitative Data
Classified into categories.
• College major of each
student in a class.
• Gender of each employee
at a company.
• Method of payment
(cash, check, credit card).
$$ Credit
Random Sample
Every sample of size n has an equal chance of
selection.
Statistical
Computer Packages
1. Typical Software
• SAS
• SPSS
• MINITAB
• Excel
2. Need Statistical Understanding
• Assumptions
• Limitations
