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
• Scales of Measurements – 4
4.
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. Quantitative
• Makes use of all the statistical data collected by the firm and by other firms/organisations
to help inform decision making
• Surveys
• Sales data
• Impact on sales
• Primary data – collected by the firm themselves
• Secondary data – collected /purchased through already used / published sources.
ex: GFK data, Nielson Data, Bloomberg data and D & B data.
7. 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
11. 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
13. 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
14. 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
15.
16. Identify the scales of measurement
• Drug sales
• Prescriptions given by the any doctor
• Specialty of the doctor (GP/GY)
•Drug performance in the market……………1 – High 3 - Low
• Family status………………1 – Higher class 5 – Lower middle class
• Time at which patient get admitted to the hospital
• Ratio Scale
• Nominal Scale
• Nominal Scale
• Ordinal Scale
• Ordinal Scale
• Interval Scale
17. Nominal Num
bers
Assig
ned
to
Runn
ers
333 8 7
Ordinal Rank
Orders
of
Winners
3rd 2nd 1st
Interval Perfor
mance
rating
8.2 9.1 9.6
Ratio Time to Finish 22.03 21.02Sec 19.19Sec
Athletics
