2. DATA AND DECISIONS FOR MANAGERS
Unit 1: Introduction to Statistics – Class#1
Dr. Nayana N
Asst. Professor
FOMC
3. Topics Covered
INTRODUCTION TO STATISTICS
Meaning and Definition of Statistics
Features of Statistics
Functions of Statistics
Importance of Statistics
Limitations of Statistics
Basic Concepts
4. Meaning of Statistics
INTRODUCTION TO STATISTICS
Statistics is concerned with scientific methods for collecting, organising,
summarising, presenting and analysing data as well as deriving valid
conclusions and making reasonable decisions on the basis of this
analysis. Statistics is concerned with the systematic collection of
numerical data and its interpretation.
The word ‘ statistic’ is used to refer to
1. Numerical facts, such as the number of people living in particular area.
2. The study of ways of collecting, analysing and interpreting the facts.
5. Definition of Statistics
INTRODUCTION TO STATISTICS
Statistics may be defined as the Science of collection, presentation,
analysis and interpretation of numerical data.
- F. E. Croxton and D.J. Cowden
6. Definition of Statistics
INTRODUCTION TO STATISTICS
“Statistics may be defined as the aggregate of facts affected to a marked
extent by multiplicity of causes, numerically expressed, enumerated or
estimated according to a reasonable standard of accuracy, collected in a
systematic manner, for a predetermined purpose and placed in relation
to each other”.
- Prof. Horace Secrist
7. Characteristics and Features of Statistics - By Horace Secrist
INTRODUCTION TO STATISTICS
1. Statistics are aggregate of facts
2. Statistics are affected to a marked extent by multiplicity of causes
3. Statistics are numerically expressed
4. Statistics are enumerated or estimated according to a reasonable
standard of accuracy
5. Statistics are collected in a systematic manner
6. Statistics are collected for a pre-determined purpose be placed in
relation to each other
8. Functions of Statistics
1. It presents the facts in a definite form
2. It simplifies and condenses the size of the data
3. It facilitates comparison
4. It enriches our knowledge and widens our experience.
5. It helps in formulating policies
6. It helps in Business forecasting
7. It helps in framing and testing of hypothesis
9. Statistics in Planning.
Statistics in Economics.
Statistics in Business and Management.
Statistics in Industry.
Statistics in Astronomy.
Statistics in Physical Sciences.
Statistics in Social Sciences.
Statistics in Medical Sciences.
Importance of Statistics in Different Disciplines
10. 1. It does not deal with individuals
2. It does not deal with qualitative data
3. Statistical laws are true only on an average
4. Only experts can make the best possible use of statistics
5. For statistical analysis, uniformity and homogeneity of data
is essential
Limitations of Statistics
11. • Units or Individuals: The objects whose characteristics are
studied in any statistical survey are called units; or Individuals.
• Population or Universe: The totality of units under consideration
is called population or universe. There are two types of
population:-
Finite population: A population which contains finite (countable)
number of units is called a finite population. Ex: students of a
college, population of a city etc..
Infinite population: A population which contains infinite
(uncountable) number of units is called an infinite population.
Ex: number of stars in the sky, integers, the number of people
seeing the Television programmers’ etc.,
Some Basic Concepts
12. • Sample: The representative units of a population is called
sample
• Quantitative Characteristics: The characteristics which are
numerically measurable are called Quantitative Characteristics.
• Qualitative Characteristics: The characteristics which are not
numerically measurable are called Qualitative Characteristics.
• Variable: A quantitative characteristics which varies from unit to
unit is a variable. Example: Height, Weight, Thickness, Length
etc.
• Attribute: A qualitative characteristics which varies from unit to
unit is an attribute. Example: Skin colour, Taste, Intelligence,
Ability etc.
Some Basic Concepts
13. • Discrete Variable: A variable which assumes only specified
values within a given range is a discrete variable. Ex : Number
of benches in a class room, Number of road accidents in a day
etc.
• Continuous Variable: A variable which assumes all the
possible values within a given range is a continuous variable.
Ex: Income of persons, Weight of students etc.
• Quantitative data: the data which can be numerically
expressed are called Quantitative data. Ex: price of
vegetables, weight of person etc..
• Qualitative data: The data which are not numerically
expressed are called Qualitative data. Ex: intelligence, beauty,
honesty etc..
Some Basic Concepts
14. Measurement of quantitative data is very easy but, measurement
of qualitative data requires different type of scale of measurement.
The two scales of measurement are:
Nominal scale: Number assigned for every unit for identification
of different categories is called a nominal scale. Ex: Roll numbers
assigned to students of a college, Among male population married
assigned number 0 and unmarried assigned 1.
Ordinal scale: Numbers assigned to observations that can be
arranged in ascending or descending order is called an ordinal
scale. Ex: Ranks given to students according to their performance,
In a shop three varieties of rice are assigned 1, 2 and 3 according
to their quality.
Some Basic Concepts
