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BCMB 307: DATA HANDLING & INTERPRETATION

Credits: 
1

Data types; Discrete and ordinate data.

Simple definitions and Descriptive Statistics; mean, standard deviation, standard error of mean etc.

Statistical principles:  Importance of statistics; sampling from populations; Gaussian and non-Gaussian distributions; confidence intervals; p-value; statistical significance; statistical power; Baysian perspective on interpreting statistical significance;

Data presentation tools: Tables, graphical types such as histograms, scatter plots, bar graphs, box plots etc

Data analysis: Multiple comparisons; analysis of one group; analysis of two or more groups; Analysis of variant (ANOVA); Analysis of survival data; Categorical data (contingency tables); odds ratios and proportions tests; correlation and linear regression; choosing the right statistical test.

Experimental Design:  Response variables (measurements of interest); factors or treatments (influencing variables); number of replicates; type of randomization; time and place of the measurements; sources of error.

Statistical packages and their applications: Excel, Minitab etc.