1

Definition of statistics and biostatistics, basic statistical definitions such as: population, sample, statistic, parameter, variable, data, types of data etc.

2

Descriptive statistics: classification of data, measures of central tendency, measures of dispersion.

3

Descriptive statistics: classification of data, measures of central tendency, measures of dispersion.

4

Tables and graphics: single dimensional table (marginal table) and graphics: histogram, bar graph, stem & leaf graph, box-plots, error graphs etc.

5

Two/Multi-dimensional tables and graphs; Cross tables, multivariate applications of basic graphics, scatter plots etc.

6

Theoretical distributions: Normal distribution, binomial distribution, Poisson distribution. Tests and graphs of normality.

7

Sampling, sampling distributions and confidence intervals: sampling distribution of mean and ratio, confidence intervals.

8

Sampling, sampling distributions and confidence intervals: sampling distribution of mean and proportion, standard error and confidence intervals.

9

Introduction to hypothesis tests: Definition and stages of hypothesis tests, possible types of errors, p and alpha values, decision making process, parametric and nonparametric hypothesis tests.

10

Hypothesis tests (single sample tests, two dependent/independent samples tests, k dependent/independent samples tests.)

11

Hypothesis tests (single sample tests, two dependent/independent samples tests, k dependent/independent samples tests.)

12

Hypothesis tests (single sample tests, two dependent/independent samples tests, k dependent/independent samples tests.)

13

Hypothesis tests (single sample tests, two dependent/independent samples tests, k dependent/independent samples tests.)

14

Correlations and regression analysis