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TOPICS COVERAGE

Lectures

  1. Study designs.
  2. Sampling Techniques, Sample size determination
  3. Data structure:
    1. Understanding variable
    2. Measurement scale of variables
    3. Types of variables
    4. Method of data entry in softwares
  4. Basic idea of probability and probability distributions.

Lectures supported by MS-Excel and SPSS:

  1. Univariate data summary
    1. Graphical descriptors: Construction and use
      1. Different kind of Bar Graphs
      2. Graphs for quantitative data
      3. Box and whisker plot.
    2. Numerical descriptor: calculation and interpretation.
      1. Proportion, odds, odds ratio
      2. Measuring central value
      3. Measurement of dispersion, spreadness, peakness.
  2. Bivariate data summary
    1. Graphical understanding of data ( scatter diagram)
    2. Measurement of strength of relationship between variables.
      1. Correlation
      2. Correlation matrix
      3. Association,
      4. Basics of Regression
  3. Estimation & Hypothesis testing
    1. Construction of confidence interval with selected confidence
    2. Parametric test (t- test, Chi square test, F test, ANOVA)
    3. Non Parametric test (Mann-Whitney test, Wilcoxon test, Kruskal -Wallis test, Friedman’s Rank test)
  4. Exposure to Analysis of Multivariate data
    1. Regression analysis (simple and multiple)
    2. Logistic regression analysis
    3. Analysis of covariates(ANCOVA)
    4. Dimension reduction technique: Factor analysis
 
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