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‘There are three types of lies: lies, damn lies, and statistics!’ Benjamin Disraeli

Biostatistics. ‘If your experiment needs statistics, you should have done a better experiment.’ Ernest Rutherford. ‘There are three types of lies: lies, damn lies, and statistics!’ Benjamin Disraeli. ‘ In God we trust. All others must bring data.’.

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‘There are three types of lies: lies, damn lies, and statistics!’ Benjamin Disraeli

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  1. Biostatistics ‘If your experiment needs statistics, you should have done a better experiment.’ Ernest Rutherford ‘There are three types of lies: lies, damn lies, and statistics!’ Benjamin Disraeli ‘In God we trust. All others must bringdata.’

  2. BIOSTATISTICSApproaches to teaching and future perspectives of e-learning SOFIA UNIVERSITY ‘ST. KLIMENT OHRIDSKI’ FACULTY OF BIOLOGY Dr. Elena Tasheva-Terzieva

  3. BIOSTATISTICS • Information about the course • Syllabus • Resources • Laboratory tutorials • Structure • Good practices – applets, calculators, icons, various examples, detailed instructions, programming • Monitoring and discussions • Assessment • Assessment system • Current assessment and Grading • Analysis of the results • Future perspectives • Question time

  4. Information about the course

  5. Syllabus Information about the course

  6. Syllabus • Introduction to biostatistics • Scope, goals and objectives • Applications of biostatistics • History of biostatistics • Computer programs for computation and graphs • Major terms • Populations • Samples – requirementsand characteristics • Methods of sampling • Variables, types of variables • Data presentation Department of zoology and anthropology Elena Tasheva

  7. Syllabus • Frequency distribution • data arrangement - why the data have to be arranged? - statistical arrays • Types of frequency tables • Presenting data • Descriptive statistics • Sample statistics • Means (arithmetic, geometric, harmonic, root mean square, median, mode) • Measures of variability  (range, variance, STD, CV) • Graphic presentation Department of zoology and anthropology Elena Tasheva

  8. Syllabus • Introduction toProbability theory • Major terms • Probability - definition • Probability of compound events • Conditional probability • Applicationsin biology • Probability distribution • Introduction • Binomialdistribution • Poissondistribution • Negativebinomialdistribution • Applications Department of zoology and anthropology Elena Tasheva

  9. Syllabus • Normalprobability distribution • Propertiesof normaldistribution • Normal distribution functions • Skewness and Kurtosis • Applications • Estimation of population parameters • Sample statistics v. population parameters • standard errors • confidence limits Department of zoology and anthropology Elena Tasheva

  10. Syllabus • Tests for difference • Hypotesis testing, null and alternative hypotheses • significance level, p-value, types of error, power of test • Parametric and non-parametric statistics Student t-test, paired t-test, Fisher F-test, Mann-Whitney U-test, Wilkoxon’s test for matched pairs • Analysis of Frequencies • Kolmogorov-Smirnov test • X2-test Department of zoology and anthropology Elena Tasheva

  11. Syllabus • Introduction to analysis of variance • Basic terms, applications • One-way and two-way ANOVA • Nonparametric Kruskal-Wallis test • Correlation • Purpose of correlation analysis • Coefficients of correlation • correlation and causal relationships Department of zoology and anthropology Elena Tasheva

  12. Syllabus • Regressionanalysis • Regression andcorrelation • Linear Regression Coefficients ofregression , regression equationandregression lines • Method of least squares • Non-linear Regression • Graphic presentation Department of zoology and anthropology Elena Tasheva

  13. Syllabus • Planning of experiments • Formulation of biological problem • Choice of suitable biostatistical method • Determination of sample size • Interpretation of results • Graphic presentation Department of zoology and anthropology Elena Tasheva

  14. Resources Information about the course

  15. Resources • Textbooks • On-line e-books • Presentations of the lectures

  16. Textbooks • Sokal, R. & JamesRohlf. 1997. Biometry. - W.H.Freeman & Co., New York.,887. • Zar, Jerrold H. 1997. Biostatistical analysis. – Prentice-Hall, Inc., 663. • Lakin, G.F. 1990. Biometry. - М.: Vissh. Shk., 352. [in Russian] • Fowler, Jim. 1997. Practical statistics for field biology. – John Wiley & Sons Ltd., 223. • Pentecost, Allan. 1999. Analysing enviromental data. – Longman, 214.

  17. On-line e-bookshttp://davidmlane.com/hyperstat/index.html

  18. Presentations of the lectures • All slides, used in the lectures are available on the internet • synopsis • current information

  19. Laboratory tutorials

  20. Laboratory tutorials Structure

  21. Structure of exercises

  22. Good practices • Applets and calculators • Icons • Variousexamples • Detailed instructions • Programming

  23. Laboratory tutorials Applets

  24. Appletshttp://www.statisticalengineering.com/histogram.htm

  25. Calculatorshttp://davidmlane.com/hyperstat/z_table.html

  26. Laboratory tutorials Icons

  27. Icons Remind Examine Check

  28. Icons calculate draw a graph make a decision save the results

  29. Laboratory tutorials Examples

  30. Introduction to a problem The effective population size is the size of an ideal population, one that meets all the Hardy-Weinberg assumptions. In case of populations, which size fluctuates in time, the effective population size is calculated as a harmonic mean. Examine the graph for fluctuation in the size of a population ofTroglodytes troglodytesinthe UK.

  31. Harmonic mean Example: Calculate the effective size of a population given the following sizes for four different periods of time: 200, 150, 50 и 300.

  32. Introduction to a problem Phenilketonuria is an autosomal recessive disease. The locus lies on chromosome 12. phenylalanine hydroxylase Such individuals are unable to synthesizean enzyme, named phenylalanine hydroxylase (PAH) which catalyses catabolism of phenylalanine.

  33. Bayes’ theorem Example: An individual is known to have parents which are both heterozygous for allels at a locus which causes Phenylketonuria. This individual has a normal phenotype. What is the chance that she is the carrier for the disease? Remember Bayes’formula Calculatethe conditional probability: P (carrier I normal phenotype)

  34. проста дъга t-образна дъга примка симетрична спирала завита сложна спирала спирала Introduction to a problem Dermatoglyphicsis the scientific study of finger-prints. There are three major groups of dermal ridge patterns: arches, loops, and whorls. The ridge count is obtained by joining the points from the center of the pattern to the triradius and counting the ridges crossed by this line. Total ridge count (TRC) is the sum of ridge counts on all fingers of both hands. simple arch T arch loop whorl - symmetrical whorl - spiral whorl – double loop

  35. Wilkoxonpaired-sample test Example: In order to examine the inheritance of dermatoglyphiccharacters, TRC of mothers and their daughters were counted. Which test for differences would you use and why? Calculate test statistics!

  36. Introduction to a problem Almost all species of ground beetles (fam. Carabidae) arebeneficial predators in agroecosystems. However there are some mixophagous species such asPseudoophonus griseus. Seeds are only a part of the adult beetles diet but in some cases they are reported as polyphagous agricultural pests. The feeding preferences of the adult individuals to different types of cultivated and wild plant seeds could be established experimentally.

  37. Kruskall-Wallistest Example: Test design: Beetles were kept for 48 h without feeding. Preferences for seven types of seeds were then tested (choice test): alfalfa, pea, winter wheat rye-grass, common bent grass, cock’s foot and timothy-grass. The average number of attacked seeds per day was counted. Analyze the obtained data by nonparametric testKruskall-Wallis! Draw a graph to illustrate the test! What is your conclusion about beetles preferences to the different seed types?

  38. Laboratory tutorials Lab instructions

  39. Lab instructions • Detailed lab instructions for work with computer programs They are available on the internet and can be read in advance to optimize class work.

  40. Lab instructions

  41. Laboratory tutorials Programming

  42. Computer programs Softwarefor data analysis Software for creation of graphs Department of zoology and anthropology Elena Tasheva

  43. User-defined data transforms Programs for optimization set up of frequency tables and calculation of class intervals, class limits, marks and frequencies.

  44. User-defined data transforms Program for calculation of mean, p, q, Binomial coefficients, probabilities and theoretical frequencies

  45. Laboratory tutorials Monitoring & discussions

  46. Assessment

  47. Assessment • Assessment system • Grading • Current assessment - tests • Analysis of the results

  48. Assessment systemin Bulgaria 6 5 4 3 2

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