The ppt describes the definition of various terminology used in biostatistics. Significance of biostatistics, important development

1. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
skhot1976@gmail.com
Paper XIV
Unit. 2. Biostatistics
2.1 Introduction, definition, terminology
Dr. Sudhakar Sambhaji Khot
M.Sc., Ph.D., SET
Assistant Professor in Botany
Y. C. Warana Mahavidyalaya, Warananagar

2. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
Dr. S. S. KHOT 2
B.Sc. Part- III Botany
Paper- XIV DSE –F26
Bioinformatics, Biostatistics and Economic Botany
Unit 2: Biostatistics (11)
2.1 Introduction, definition, terminology.
2.2 Collection and presentation of data:
Types of data, techniques of data collection- Census method,
sampling method- simple random, stratified and systematic sampling.
Classification, tabulation, graphical representation- Histogram and polygon.
2.3 Measures of central tendency and Dispersion:
Arithmetic mean, Mode, Median,
Range, Deviation, Mean deviation, Standard Deviation, Coefficient of Variation.
2.4 Statistical methods for testing the hypothesis’
i) Students’ T-test
ii) Chi-square test

3. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
Dr. S. S. KHOT 3
• Introduction
Statistics: Deals with numbers
Used by Emperor to keep records of population, economy (Tax, income, budget etc)
Adolphe Quetelet (1796-1874): generalized use of statistics for biology and medicine
Francis Galton (1822 – 1911): ‘Father of Biostatistics and Eugenics’
(contributed in Heredity, eugenics, psychology, anthropometry, Correlation etc)
Karl Pearson (1857 – 1906): foundation for descriptive and correlational statistics
R. A. Fisher (1890 – 1962): contributed in small sample theory.
Definition: “Branch of science that deals with collection, organization, presentation, analysis
and inference of biological data.”
a) Descriptive biostatistics: collection, organization, summarization and presentation of data
b) Inferential biostatistics: generalization of conclusion, hypothesis testing, making prediction
2.1 Introduction, definition, terminology.

4. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
Dr. S. S. KHOT 4
Why statistics? :
The earth is full of diversity.
We want the best.
What is best?
How to identify it?
How to believe the products/ services?
Living organisms are dynamic.
To understand effect of
medicine on animals / plants.
supplements / fertilizers on growth, etc.
2.1 Introduction, definition, terminology.

5. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
Dr. S. S. KHOT 5
Learning the arcane method and jargon ?
Population (N) : Universe / defined group of individuals under observation/ (study).
e.g. Botanical Garden
Sample (n): small, selected group of population under investigation.
a) Random sample: each individual gets equal chance of being selected.
b) Biased / non-random samples: selection of samples with purpose.
Unit (x): smallest object or individual under investigation.
e.g. individuals of the species in quadrat
Variable: characteristics by which individuals differ among themselves. e.g. age, gender
a) Quantitative variable: Numerical observations
i) Discrete variables: integral numbers in a range e.g. number of children
ii) continuous variable: all possible values in range e.g. length of leaf
b) Qualitative variable: non-numerical observations e.g. gender, colour, honesty.
2.1 Introduction, definition, terminology.

6. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
Dr. S. S. KHOT 6
Learning the arcane method and jargon ?
Constant: quantity that does not vary within particular set of conditions.
e.g. no. of students/ class at given time
Parameter: numerical property/ characteristics that is descriptive of population.
e.g. mean, median, mode etc.
Data: a set of facts expressed / recorded in quantitative form.
a) Primary data: collected by investigator e.g. data collected from experimental site.
b) Secondary data: Obtained from secondary sources e.g. newspapers, journals magazines
Inference: the conclusion about population
Accuracy: closeness of a measured value to its origin
Precision: closeness of repeated measurements of the same quantity.
2.1 Introduction, definition, terminology.

7. skhot1976@gmail.com B.Sc.-III Paper- XIV (DSE –F26) Bioinformatics, Biostatistics and Economic Botany
Dr. S. S. KHOT
Thank You
2.2 Types and methods of data Collection
2.1 Introduction, definition, terminology
2.3 Classification of data: Tabulation
2.4 Graphical representation- Histogram and polygon
2.5 Measures of central tendency Mean, Median, Mode (for Ungrouped data)
2.6 Measures of central tendency Mean, Median, Mode (for grouped data)
2.7 Measures of Dispersion Range, Mean Deviation, Std. Dev., Coe. Variation (for Ungrouped data)
2.8 Measures of Dispersion Standard Deviation and Coefficient of Variation (CV) (for grouped data)
2.9 Test of Significance Student’s t-test (for paired samples)
2.10 Test of Significance Chi-Square Test (x2)
Index of Videos on this Chapter
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