education

1. Basic Statistics for Business

2. What Is Statistics?
• Science of collection, organization, analysis and interpretation of
numerical facts
Gathering Analyzing
•Drawing Inferences
• Originally associated with government data (e.g., census data), the subject now has
applications in all the areas

3. Types of Data
 Qualitative and Quantitative
 Discrete and Continuous
 Univariate and Bivariate
 Raw and Tabulated

5. Quantitative and Qualitative Characteristics
• Quantitative characteristic – one which can
be measured numerically (variable)
• Example: Height, Weight, Number of
Patients
• Qualitative characteristic – one which
cannot be measured numerically
(attribute)
• Example: Intelligence, Beauty

6. Discrete and Continuous Variable
• Discrete variable
• A variable which assumes only some specified values in a given range
• Example: Number of children per family, Number of seeds per bean pod
• Continuous Variable
• A variable which assumes all the values in the range
• Example: Height of persons, Weight of apples
1. Skin color of a person Quantitative/Qualitative
2. Age Continuous/Discrete
3. Number of children in a family Continuous/Discrete
4. Years of education Continuous/Discrete
5. Family Status Quantitative/Qualitative
6. Sales value of a drug Continuous/Discrete
7. # of Calls to the particular doctor….. Continuous/Discrete
8. Characteristic of a population Statistic/Parameter

7. Scales of Measurement
Measurement Scales
Nominal
data
Ratio data
Ordinal data Interval data

9. Nominal Scale
• Named categories
• Examples: Gender, Race, Party Identification, Place of Birth, Major Department
• Question: Before I begin, can I verify what is your specialty?
1. General Practice, or
2. Family Practice, or
3. Primary Care, or
4. Internal Medicine
5. Other
• Measure used: Mode

12. Ordinal Scale
•All observations are ordered (ranked) from lower to higher, but we can’t
assign any meaningful uniform distance between the ranks
•Examples: job prestige, social class, high school class rank
•Question: Did the rep present the full information of the product to you?
• 1 = Very poor information coverage 5 = Very good information coverage
•Measure used: Median, Mode

15. Interval Scale
•We can specify equal distance between levels, but there is no fixed and meaningful zero
point
•Examples: IQ scores, degrees Fahrenheit, degrees Centigrade (Celsius), GREscores
•Measure used: Mean

18. Ratio Scale
•There is some meaningful zero point, allowing us to form ratios of one value relative to
another value
•Examples: income, census counts, years of education
•Question: Cost of treatment in a government hospital
•Measure used: Mean

21. Data based on variables
 Univariate – 1 Measured & 1 Category dataset
 Bivariate – 2 datasets –both measured
 Multivariate – More than 2 datasets –all measured
 Measured Data =Continuous Data – Interval/Ratio
 Categorical Data = Nominal /Ordinal Data