Presentation on Statistics

1. Applications of Statistics in Agriculture
- Sunny Kumar
Asst. Professor
Mathematics
and Statistics

2. Introduction
⚫In the modern world of computers and
information technology, the importance of
statistics is very well recogonised by all the
disciplines. Statistics has originated as a
science of statehood and found applications
slowly and steadily in Agriculture,
Economics, Commerce, Biology, Medicine,
Industry, planning, education and so on. As
on date there is no other human walk of life,
where statistics cannot be applied.

3. Origin and growth of statistics
The word ‘ Statistics’ and ‘ Statistical’ are all
derived from the Latin word Status, means a
political state. The theory of statistics as a
distinct branch of scientific method is of
comparatively recent growth. Research
particularly into the mathematical theory of
statistics is rapidly proceeding and fresh
discoveries are being made all over the
world.

4. Meaning of statistics
Statistics is concerned with
methods for collecting,
scientific
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 Numerical facts, such as the
number of people living in particular area.
The study of ways of collecting, analysing
and interpreting the facts.

5. Statistics and agricultural
⚫In agricultural research, for example, there are
different statistical techniques for crop and animal
research,
genevic
Although
and physiological research, and so
this diversit" indicates the ability
for laboratory and field experiments, for
on.
of
appropriate statistical techniques for most research
problems, it also indicates the difficulty of matching
the best technique to a specific experiment. Obviously,
thisdifficulty increases as more proceduresdevelop.
⚫Choosing the correct statistical procedure for a given
experiment must be based on expertise in statistics
and in the subject matter of the experiment. Thorough
knowledgeof onlyoneof the two is notenough.

6. ⚫For most agricultural research institutions in the
developing countries, the presence of trained statisticians
is a luxury. Of the already small number of such
statisticians, only a small fraction have the interest and
experience agricultural research necessary for effective
consultation. Thus, we feel the best alternative is to give
agricultural researchers a statistical background so that
they can correctly choose the statistical technique most
appropriate fortheirexperiment.
⚫For research institutions in the developed countries, the
shortage of trained statisticians may not be as acute as in
the developing countries. Nevertheless, the subject matter
specialist must be able to communicate with the consulting
statistician. Thus, for the developed-country researcher,
this volume should help forge a closer researcher-
statistician relationship.

7. EXAMPLE
 In the early 1950s, a Filipino journalist, disappointed
with the chronic shortage of rice in his country,
decided to test the yield potential of existing rice
cultivars and the opportunity for substantially
increasing low yields in farmers' fields. He planted a
single rice seed-from an ordinary farm-on a well-
prepared plot and carefully nurtured the developing
seedling to maturity. At harvest, he counted more than
1000 seeds produced by the single plant. The journalist
concluded that Filipino farmers who normally use 50
kg of grains to plant a hectare, could harvest 50 tons
(0.05 x 1000) from a hectare of land instead of the
disappointingly low national average of 1.2 t/ha.

8.  In agricultural research, the key questions to be
answered are generally expressed as a statement of
hypothesis that has to be verified or disproved through
experimentation. These hypotheses are usually
suggested by past experiences, observations, and, at
times, by theoretical considerations. For example, in
the case of the Filipino journalist, visits to selected
farms may have impressed him as he saw the high
yield of some selected rice plants and visualized the
potential for duplicating that high yield uniformly on a
farm and even over many farms. He therefore
hypothesized that rice yields in farmers' fields were
way below their potential and that, with better
husbandry, rice yields could be substantially increased.

9. What do we mean by agricultural
statistics
 The terms data, statistics and information are often used
interchangeably but there are important distinctions. Data,
statistics and information • What are they? • Why are they
important? • Where do they come from? • What is the
scope of agriculture stats and information? Data are the
basic part of a broader information system. When
statisticians produce data, they are trying to measure or
count phenomena (things or activities) that are part of the
real world. Data may be viewed as a lowest level of
abstraction from which information and knowledge are
derived. Examples of data: Number of cows on a farm
,Number of people in a household Number of children in a
family In these cases, the data are derived by counting.

10.  If the question were: “How many dollars did you spend
last year on improved seed?” the answer must be
provided by a respondent who would look at records,
or simply cite the number from memory. This is
another example of measurement.

11. Statistics and data
⚫Statistics is also a mathematical science that focuses
on the collection, analysis, interpretation or
explanation, and presentation of data. 1We often think
of statistics as being produced by National Statistical
Organizations (NSOs) but in fact they can be
generated by any number of people. They can come
from
⚫• Opinion polls
⚫• Surveys
⚫• Censuses
⚫• Administrativedata (e.g., importsand exports)

12. Agricultural data and information are required to support the
following types of processes:
⚫• underpinning the planning processes;
⚫• compiling national accounts;
⚫• informing public policy analysis, debate and
advice;
⚫• observing sectorperformance;
⚫• monitoring and evaluating the impact of
policies and programmes and
⚫• enlightening thedecision-making processes.

13. Examples of agriculture development objectives
⚫• Improving food supply (cereals, cashew nut, sugar,
cotton)
⚫• Improving seeds
⚫• Providing access to fertilizer
⚫• Monitoring and controlling pestsof basiccropsand
reducing animal mortality

14. Purpose of statistics
⚫statistics are produced and valued because they help
decision makers and program managers make
decisionsand evaluateprogress. It is these needs that
must be kept in mind when planning and designing
agriculturesurveys.

15.  Some of examples of the use of statistics are related to: crop
farming (wheat, maize, sugar beet, sunflower, soy, fodder
crops, other industrial crops etc), vegetable crops
(potatoes, tomatoes, beans, peas, onions, peppers etc), fruit
growing (apples, pears, plums, cherries, sour cherries,
apricots, peaches, walnuts etc), viticulture (grapes),
horticulture plants, perennials, livestock breeding (cattle
breeding, pig breeding, sheep breeding, poultry breeding),
exploitation of agricultural machines and transport means,
utilization and protection of waters, consumption of
mineral fertilizers, consumption of plant protection
preparations etc. Problems related to agricultural
economics are: agricultural population, cultivable area,
agricultural enterprises and cooperatives, individual
(private) holdings, workers in agricultural enterprises and
cooperatives, costs, sources of income etc

16.  Some examples of the application of statistical methods in
problems through research processes at the Agricultural
Faculty of Novi Sad are: genetics and plant breeding, crop
production concerning different conditions of agrotechnics
and plant protection, type of soils, localities, varieties,
sorts, hybrids, conditions of irrigation, use of herbicides,
plant physiology, plant biochemistry, genetics and livestock
breeding, animal physiology, livestock production
concerning different races, different conditions of animal
nutrition, protection ,etc. Some other examples of the use
of statistics are related to: the method of production
functions in wheat, maize and sugar beet production, etc,
the influence of particular factors on agricultural
production, measuring of contribution of production
factors and technical progress to the growth of national
product, tendencies of production lines in agriculture, etc.

17.  The aim of statistical education for the students is
oriented to obtaining an understanding of statistical
concepts and principles and to make efficient
applications of statistical techniques to various data in
agriculture. If these students had more statistical
education they would widely use appropriate
statistical procedures. Better statistical knowledge
would allow medical students to read and appraise the
research literature most of which now includes
statistical results