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BIOLOGICAL RESEARCH

BIOLOGICAL RESEARCH. Anil M. Mungikar Biological Research Communication Academy, Aurangabad. Refresher Course in Life Sciences. Participants : Botany, Zoology, Microbiology, Biotechnology Ph . D. Completed Ongoing Planning.

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BIOLOGICAL RESEARCH

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  1. BIOLOGICAL RESEARCH Anil M. Mungikar Biological Research CommunicationAcademy, Aurangabad

  2. Refresher Course in Life Sciences Participants : Botany, Zoology, Microbiology, Biotechnology Ph. D. Completed Ongoing Planning

  3. Biological Research in Colleges or University Departments Ph. D. degree oriented Hence : Time Bound Therefore: May limit Original Research However : Generates new young scientists with awareness of Research methodology , who can perform research in the colleges or other places. Thus : Talent generating process

  4. Time required for Research leading to Ph.D. degree in Life Sciences Full time : Approximately 3 Year Part Time : 3 -5 Years Depending on : Nature of the Research work Scope of Subject Funds and Facilities available Working place ( Field / Laboratory ) Socio-Economic condition Efficiency of Guide as well as Student ……. And other related factors

  5. Data EitherfromField and / or Laboratory By observation and / or through Experiments May be qualitative and / or quantitative If quantitative : Measurement or Count Nature : Continuous or Discrete Variables : multivariate Require : proper documentation

  6. PRESENTATION OF DATA • Tables : self explanatory, neat and suitable • Illustrations : Line drawings, Camera Lucida, free hand sketches • Graphs : Histograms, curves, multiple curves • Figures : to summarisedata • Flow Charts : Sequential arrangement of data • Photographs : Important B.W / Colored Photos from the Field or Microphotographs

  7. BIO-STASTICAL ANALYSIS Most Important for : Proper interpretation of the data and to draw valid conclusions. To put fourth findings / conclusions more effectively and confidently To avoid may be, might be, it is felt that, it appears that , probably, in author’s opinion , most likely etc.

  8. CENTRAL VALUE Value located in the center, and around which the observations are Scattered : Represented as : Mode : Frequently appearing value Median : Value located in the center Mean : Arithmetic average THE USE OF MEAN IS MOST ACCEPTABLE

  9. SPREAD, DISPERSION OR SCATTER For understanding the pattern in which observations are scattered around central value : Represented by : Range Mean Deviation Standard Deviation USE OF STANDARD DEVIATION ( S.D.) IS MOST ACCEPTABLE

  10. COEFFICIENT OF VARIATION (C.V.) Gives idea regarding the intensity of variation among observations . Expressed as Standard Deviation as per cent of mean. Example : Length of Fish ( N = 15 ) : Mean =7.8 cm, S.D. =1.02, C. V. = 13.0 Weight of Fish ( N = 15 ): Mean = 86.5 g, S.D. = 4.8, C. V. = 5.5 MOST USEFUL FOR COMPARING VARIABILITY

  11. FREQUENCY DISTRIBUTION When number of observations are more, the data is classified in various classes and number of observations in each class or frequency of each class is calculated. Useful for summarizing data in the form of frequency distribution Table, Histogram or frequency curve ALSO SUITABLE FOR FURTHER CALCULATIONS

  12. SAMPLING For Large Number of Observations A part of the population is randomly drawn It is known as Sample. Randomly drawn Sample represents population Mean of Sample means = Population Mean S. D. of Sample Means = Standard Error (S.E.)USEFUL TO HANDLE LARGE POPULATION

  13. NORMAL CURVE POPULATION SAMPLE MEANS Symmetrical , Bell Shaped Mean + S. E. = 68 % Sample means Mean + 2 S.E. = 95 % Sample Means Mean + 3 S.D = 99 % Sample Means Symmetrical , Bell Shaped Mean + S.D. = 68 % observations Mean + 2 S.D. = 95 % Observations Mean + 3 S.D. = 99 % Observations

  14. CONFIDENCE LIMIT AND t TEST Mean + 2 S.E. = Confidence Limit The difference between two Sample means within this limit is statistically Non - Significant . The difference between two sample means beyond confidence limit is statistically Significant at p = 0.05 The difference between two sample means beyond Mean + 3 S.E. is Statistically Significant at p = 0.01 t Test is used to find out whether the difference is Significant or Non-Significant If Significant = Consider If non Significant = Ignore USEFUL FOR COMPAIRING TWO SAMPLE MEANS

  15. CORRELATION It is relationship between two variables. Increase in one variable = increase in other = Positive Correlation Increase in one variable = Decrease in other = negative correlation Both variables do not affect each other = No Correlation

  16. Chi Square Test Useful while comparing observed values with the expected. Allow testing of Hypothesis. Particularly useful in genetic Research

  17. CORRELATION COEFFICIENT Correlation Coefficient gives intensity of Correlation between two parameters. Designated by r It ranges between : – 1 to0to +1 r = 1 : Perfect Correlation r = 0 : No correlation r = Near 1 : Strong Correlation r = Near 0 : Loose Correlation r = + : Positive, r = - : Negative Correlation USEFUL IN EVALUATING RELATIONSHIP BETWEEN DIFFERENT VARIABLES

  18. REGRESSION EQUATION Represents relationship between two parameters in an equation : Linear : Y = a + b X Various types of equations for different relationships. USEFUL IN REPRESENTING DATA MATHEMATICALLY

  19. ANALYSIS OF VARIANCE ( ANOVA ) ANOVA is employed to find out total variance ( Square of S.D. ), as well as variance due to various factors. It is represented in the form of ANOVA Table. The variance ratio or value of F denotes significance of variation. USEFUL IN FINDING OUT VARIATION DUE TO MORE THAN ONE FACTORS

  20. ANOVA TABLE Effect of pesticides on Lipid contents of Kidney, Liver and Muscles of rat ANOVA Source d.f. S.S. M.S.S. F Treatment 3 4.085 1.361 2.11 NS Organ 2 16.716 8.358 12.97 ** Error 6 3.866 0.644 Total 11 24.667

  21. RESEARCH PAPER *Apart from submitting thesis publication of Research papers is equally important *Status in Marathwada ---- ( excuse me please !! ) *Poor desire of publication of paper *Complete dependency on Research Guide. *Very less knowledge about research paper writing *Fear of publishing – lack of confidence *Poor information about Scientific Journals *Financial limitations.

  22. SELECTION OF PROPER JOURNAL Status : International. National, Regional Registrar of News papers of India (RNI) International Standard Serial Number (ISSN) Periodicity : Monthly, Quarterly, Half yearly Abstractingin various abstracting agencies viz. ISA, MAPA, ABA, ZR, BA, IPNI, PA, BA etc. Annual / Life membership Circulation : Online, Print, Both Scopeof the Journal Regularityand Promptness

  23. VERY IMPORTANT POINTS • Impact Factor ( IP ) : National Institute of Science Communication And Information Resources (NISCAIR), CSIR,New Delhi, Zoological Records ( ZR ), Thompson Reuters (UK) • I P f0r 2011 : Number of articles published in 2009-2010 which were cited in journals during 2011 / Number of articles published in 2009-2010

  24. VERY IMPORTANT POINTS If related to thee Agricultural Sciences : National Academy for Agricultural Sciences ( NAAS ) rating. It is being given by NAAS, New Delhi on the basis of overall performance of the Journal

  25. P - Index P – Index = ( C * C / P ) ^ (1/3) WhereC = Number of Citations P = Number of Publications Represents combination of the size and quality of journal for comparison with other journals. USEFUL IN ASSESSMENT OF THE JOURNAL

  26. Citation index Meant for individual Research papers and not for a particular journal. It indicates the Number of citations of your paper by other authors in their research paper. USEFUL TO EVALUATE INDIVIDUAL PUBLICATION

  27. BIOLOGICAL RESEARCH COMMUNICATION ACADEMY • Established in the year 2009 • Help Research workers to statistically analyze, their data. • Encourage budding researchers to publish papers. • Publish a quarterly Journal “ BIOINFOLET” ( RNI :MAHENG/2004/14907, Print ISSN : 0973- 1431, Online ISSN : 0976-4755, Abstracting : ISA, MAPA, ABA, ZR, IPNI, IF (2010) : 0.064; P-Index : 0.165; NAAS Rating : 4.2 )

  28. BIOLOGICAL RESEARCH COMMUNICATION ACADEMY Other Services : *Statistical Analysis along with interpretation *Basic Course in Bio-statistical Analysis : Duration : 10 Days. : 2 Hours / Day = 20 Clock Hours Timings : Morning 7-30 to 9-30. CONTACT : (0240) 2354532, 8805546220

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