Meaning of statics and introduction to Biostatics

1. 1
MEANINGS OF STATISTICS
Numerical Facts Systematically Arranged.
e.g. Statistics of prices, Statistics of road accidents,
Statistics of crimes, Statistics of birth, Statistics
of deaths, Statistics of educational institutions etc.
 Subject.
Statistics is the mathematical science of making
decisions and drawing conclusions from data in
situations of uncertainty. It includes collection,
organization and analysis of numerical data.

2. 2
INTRODUCTORY STATISTICS
OR
Statistics is a science, pure and applied, of
creating, developing and applying techniques
such that uncertainty of inductive inferences
may be evaluated.
Statistic.
A numerical quantity calculated from a sample.

3. 3
INTRODUCTORY STATISTICS
Observation/Datum
The numerically recording of
information is called observation/datum.
Data:
The set of observations is called data.

4. 4
INTRODUCTORY STATISTICS
Biostatistics:
When the data analyzed are derived from
the biological sciences and medicine, we use
the term biostatistics to distinguish this
particular application of statistical tools and
concepts
Example:
It was observed that out of 500 rabbits caught, 300
were females. Is there evidence that more rabbits in this
country are females?

5. 5
Population:- The collection of all possible
observations whether finite or infinite, relevant
to some characteristic of interest is called a
population. The number of observations in a
finite population is called size of the population
and is denoted by N.
INTRODUCTORY STATISTICS
Sample:-A sample is a part of a population.
Generally it consists of some of the
observation. The number of observations in a
sample is called size of the sample and is
denoted by n.

6. 6
INTRODUCTORY STATISTICS
Parameter:
It is a quantity computed from a
population if the entire population is available.
Parameters are fixed or constant quantities and not
usually known.
Statistic:
It is a quantity computed from sample.
Statistics are variables b/c they vary from sample
to sample

7. INTRODUCTORY STATISTICS
Ratio:
A ratio is a fraction. The ratio of A to B is A/B. and
ratio of B to A is B/A.
With reference to the example
The ratio of male to female rabbits ‗ 200 ‗ 2
300 3
The ratio of female to male rabbits ‗ 300 ‗ 3
200 2
7

8. Proportion:
A proportion is a special ratio, the ratio of a part to a
total.
In the above example,
Proportion of male rabbits ‗ 200
500
Proportion of female rabbits ‗ 300
500
8
INTRODUCTORY STATISTICS

9. INTRODUCTORY STATISTICS
Percentage (%):
If a proportion is multiplied by 100, then it is called
the percentage (%). For example
Percentage of male rabbits ‗ 200
500
Percentage of female rabbits ‗ 300
500
9
= 40%× 100
× 100 = 60%

10. Example:
It was observed that out of 500 rabbits caught, 300
were females. Is there evidence that more rabbits in this
country are females?
Population:
Rabbits all over the country.
Sample:
500 rabbits caught.
Parameter:
Ratio, Proportion, Percentage etc of male and
female rabbits all over the country rabbits
10
INTRODUCTORY STATISTICS

11. Statistics:
The ratio of male to female rabbits ‗ 200 ‗ 2
300 3
The ratio of female to male rabbits ‗ 300 ‗ 3
200 2
Proportion of male rabbits ‗ 200
500
Proportion of female rabbits ‗ 300
500
Percentage of male rabbits ‗ 200 × 100 = 40%
500
Percentage of female rabbits ‗ 300 × 100 = 60%
500 11
INTRODUCTORY STATISTICS

12. Types of Statistics
Descriptive Statistics: Methods of
organizing, summarizing, and
presenting data in an informative
way.
Inferential Statistics: A decision,
estimate, prediction, or generalization
about a population, based on a sample
12

13. 13
Basic concepts
Descriptive Statistics
Presenting the numerical information in the form
of number, graphs and tables.
Inferential Statistics
To estimate the population parameter on the basis
of the sample statistic.
Population
The aggregate of units under discussion.(N)
Sample
A subset / part of the population.(n)

14. 14
Primary and Secondary Data

15. 15
INTRODUCTORY STATISTICS
Secondary Data
Data that have undergone any sort of
treatment by statistical methods at
least ONCE, i.e. the data that have
been collected, classified, tabulated or
presented in some form for a certain
purpose, are called SECONDARY
data.

16. 16
COLLECTION OF PRIMARY DATA
One or more of the following methods are employed to
collect primary data:
i) Direct Personal Investigation.
ii) Indirect Investigation.
iii) Collection through Questionnaires.
iv) Collection through Enumerators.
v) Collection through Local Sources.

17. 17
INTRODUCTORY STATISTICS
Variable:
A characteristics that varies from individual
to individual is called a variable. For example age, plant
height, weight, no of plants per plot etc are variables as
they vary from individual to individual.
Constant:
Quantity which do not vary from individual to
Individual is called constant. e.g. e= 2.71828 , = 3.145

18. 18
INTRODUCTORY STATISTICS
Types of variables:
Fixed or Mathematical Variable:
A variable may be fixed
or Mathematical when its value can be determined before
hand. e.g. amount of fertilizer to be applied to a plot,
amount of insecticide applied to control insect pests.
Random Variable:
A variable may be random when its
value cannot be exactly determined. e.g. yield from a plot

19. 19
INTRODUCTORY STATISTICS
Types of variables:
(1):- Quantitative variable (2):- Qualitative variable.
Quantitative variable:- A variable is called Quantitative
variable when a characteristic can be expressed numerically
such as weight, income, number of children.
Qualitative variable:- If a characteristic is non-numerical
such as sex, colour, general knowledge, honesty, beauty, etc
the variable is called Qualitative/ Categorical variable or
attribute.

20. 20
INTRODUCTORY STATISTICS
Types of Quantitative variable
1:- Discrete variable 2:- Continuous variable .
Discrete variable:- A variable which can assume some
specific values within a given range is called a discontinuous
or discrete variable. e.g. number of trees in a field, number
of leaves in a tree. A discrete variable takes on values which
are integers or whole numbers.
Continuous variable:- A variable which can assume any
value (fractional or integral) within a given range is called a
continuous variable. For example Height of a plant, the
temperature at a place.

21. 21
Variable
Characteristic that varies form individual to individual
a) Fixed variable b) Random variable
Types of Variable
Quantitative variable
Capable of assuming a numerical value
Continuous variable
Can take all possible values in an interval
Discrete/Discontinuous variable
Can take only specified values
Qualitative/Categorical variable
Not capable of taking numerical measurements
 Constant
Don’t vary from individual to individual

22. 22
INTRODUCTORY STATISTICS
Scales of Measurement
Measurement: Measurement refer to “Assigning of number to
observations or objects.
Scaling: Scaling is a process of measuring.
Four Scales of Measurements
1. Nominal Scale
2. Ordinal Scale
3. Interval Scale
4. Ratio Scale

23. 23
INTRODUCTORY STATISTICS
Nominal Scale (Weakest form of measurement)
The classification or grouping of the observations into
mutually exclusive qualitative categories or classes is said
to constitute a nominal scale.
e.g. Sex , Race, Religion, Country
Rainfall may be classified as
• Heavy
• Moderate
• Light

24. 24
INTRODUCTORY STATISTICS
Ordinal Scale (When numbers are allocated in some order)
It includes the characteristics of nominal scale and in addition
has a property of ordering or ranking of measurements.
• Attitude scale Strongly agree, agree, disagree
• Social scale Upper, middle, lower
• Performance of players Excellent, good, fair, poor

25. 25
INTRODUCTORY STATISTICS
Interval Scale
It has separate categories, like nominal scales and also has
ordered categories like ordinal scales. But the interval
measurements has no true zero point.
 Temperature ( 80oF and 40oF is 26.7oC and4.4oC)
Ratio Scale
In this scale the intervals are consistent along the entire
scale. The ratio measurements has true zero point.
• Height of plant, weight of students, volume, length,