Biostatistics — end. Syllabus of the major practicum section “Statistical Data Analysis in Zoology and Ecology”
Main topics covered in the practicum section and requirements for the final pass/fail assignment.
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D.A. Shabanov, M.A. Kravchenko. Statistical Analysis of Data in Zoology and Ecology
Topic 11. Some Methods Characteristic of Zoology and Ecology
Appendix. Program for the section of the major practical course "Statistical Analysis of Data in Zoology and Ecology"
Biostatistics-15
Biostatistics-16
Program for the section of the major practical course "Statistical Analysis of Data in Zoology and Ecology" Working with the Statistica Program Organization of a data file in the Statistica program. Operations (adding, deleting, moving) of rows and columns. Transposing blocks and files. Editing row names and column headers. Entering formulas in column headers, calculations based on them. Sorting rows. Double entry of text and numerical values, establishing correspondences between them using the label editor. Standardization (normalization) of features. Editing graphs generated in the Statistica program. Description of samples and data Sample statistics and their calculation. Scatter plots (including with differently highlighted points and categorized by certain features); simple and categorized. Histograms: simple and cumulative; simple and categorized. Box plots (if necessary – changing the sample statistics reflected by the "box" and "whisker"). Relationship between features Pearson correlation (parametric). Spearman correlation (non-parametric). Feature association ("Tables and headers"). Comparison of samples and distributions To choose between parametric and non-parametric methods – comparison of distributions by Kolmogorov-Smirnov, etc. Comparison of distributions using Pearson's chi-square method (in particular, in the "Tables and headers" dialog). Parametric comparison of samples using Student's and Fisher's criteria. Non-parametric comparison of samples using Mann-Whitney U test. One-factor and two-factor analysis of variance, interpretation of its results. Using the "quick" significance counter for comparing means and correlation coefficients (Difference tests in the Basic Statistics and Tables menu). Multivariate analysis Cluster analysis (agglomerative methods with "tree" construction). Principal component analysis. Discriminant analysis and canonical variables. Requirements for the credit assignment task Completed credit assignment – a file created using a text editor (e.g., Microsoft Word), containing the following elements: 1. Text of the assignment itself. 2. Results of data processing: graphs, tables, inserted (at least using Ctrl+A – Ctrl+V) into the text from the Statistica program. 3. Interpretation of results in an arbitrary but understandable form. File name – Ivanov.doc or similar.