Introduction/ review, data types, probability and laws of probability. Random data types. Statistics, data and statistical thinking.
Data visualization.  Measures of central tendency.

Comparing two population means: independent and paired sampling

Estimating a proportion
Comparing groups on categorical data
Chi-square tests
Large sample confidence interval for a population proportion

Measures of Quality of Estimators. MLE/ MOM
Central Limit Theorem and sampling distribution
Large-Sample Confidence Interval for a Population Mean and Proportions
t-Statistics and small sample confidence intervals for a population mean

Introduction to hypothesis testing
Inference based on a single sample: test of hypothesis
Introduction to Theory of Statistical Tests
Likelihood Ratio Tests

Small sample test, Yates’ correction, Fisher Exact test
Measures of association: Relative Risk and Odds Ratio

Association between measurement variables. Correlation and regression. Simple Linear Regression. Multiple linear regression. Regression diagnostic. Data transformation

Non-Parametric tests
Non-parametric test about population mean, comparing two populations paired test, Sign test, Non-Parametric test for correlation

Logistic Regression

Midterm Exam

Analysis of Variances (ANOVA), basic assumptions and inference

Simulation of data. Bootstrap and Jackknife. P-value tests.

Randomized models in statistics. Method of Moments.

More on non-parametric methods: KS & AD tests. Time series and statistical methods.

Final Evaluation Test (using advanced computations)