Syllabus:
Chapter 1: Descriptive Statistics
-Population/sample;
-Variable Classification and measure scales.
-Creation of databases in SPSS;
- Frequency tables of unidimensional/ bidimensional variables;
-Graphic representations;
- Measures of central tendency, dispersion, skewness, and kurtosis;
Chapter 2: Correlation and Simple Linear Regression
- Pearson correlation coefficient;
- Scatter Plot;
- Least squares regression line;
Determination coefficient.
Chapter 3: Probability Theory;
- Random experiments, sample spaces, events;
- Axiomatic definition of probability and respective properties;
- Conditional probability;
- Real random variables (discrete/continuous);
- Distribution function, probability function and probability density function);
- Expected value and variance of a random variable;
- Binomial distribution;
- Poisson distribution;
- Normal distribution.