1. Statistics, Statistical Data – Classification, Collection, Data Sources,
Population Versus Sample, Stem and Leaf Diagram
2. Data Presentation, Set of Values of One Variable - Range, Frequency
Distribution, Cumulative, Relative, Relative
Cumulative Frequencies and Its Graphs
3. Descriptive Measures for One Dimensional Statistical Set of Data,
Exploratory Data Analysis
4. Algebra of Events, Concept of Probability
5. Probability Theory, Succession of Independent Events, Total Probability,
Bayes´ Rule
6. Random Variable (Types of Random Variables, Distribution Function,
Probability Function, Density Function) and Discrete
Probability Distributions (Uniform, Binomial, Hypergeometric, Pascal´s,
Poisson´s).
7. Continuous Probability Distributions (Uniform, Exponential, Normal,)
Approximation of Binomial Distribution
8. Statistical Inference, Sampling Theory, Limit Theorem, Estimation Theory
(Point Estimates, Interval Estimates)
9. Tests of Hypotheses, One Sample Parametric Tests for Mean and Variance
10. Bivariate Data and Correlation Analysis, Correlation Coefficient
11. Simple Linear Regression, Determination Coefficient
12. Time Series Analysis, Components, Combining the Components
13. Index Numbers, Price and Quantity Indexes