Sumários

Central Limit Theorem. Corrolary of de Moivre Laplace.

5 Dezembro 2014, 15:30 Graça Leão Fernandes

exercises from the book- chapter 6 - nºs: 6.75, 6.77, 6.79

exercises for chapter 5 - nºs: 26, 27, 28, 37


Normal distribution (cont.)Central Limit Theorem. De Moivre Laplace Corolary. Correction of continuity.

2 Dezembro 2014, 13:30 Graça Leão Fernandes

Normal distribution (cont.):

   - Relationship between the notmal and the standard normal distribution and the Chi-square distribution.

Central Limit Theorem:

   - De Moivre Laplace Corolary. Correction of continuity.

Examples


Normal distribution

1 Dezembro 2014, 13:30 Graça Leão Fernandes

Normal distribution:

- Probability density, cumulative distribution and momente generating functions;

- The standard normal distribution

         - How to standardize a normal distribution;

         - Probability density, cumulative distribution and momente generating functions;

         - how to use the tables of the cumulative distribution function and its inverse.

- Using the calculator to compute probabilities.

- Theorem of aditivity for the sum of independent random variables

- Examples


Some important distributions of continuous random variables: Uniform, Exponencial, Gamma,Chi-Square

28 Novembro 2014, 15:30 Graça Leão Fernandes

Resolution of the 4th mini test.

 

Solving exercises from:

 

book - nºs 6.1, 6.54, 6.56, 6.59;

 

Exercises for chapter 5 - nºs 1, 3, 14, 17, 19

 


Some important distributions of continuous random variables: Gama and Chi-Square

25 Novembro 2014, 13:30 Graça Leão Fernandes

 Gama:

        - The relation between the Exponential and Gamma distributions;

        - Probability density and cumulative distribution functions;

        - Moment generating function, mean and variance;

        - theorem of aditivity

  Chi-Square distribution:

        - The relation between the Gamma and Chi-Square distributions;

        - Probability density and cumulative distribution functions;

        - Moment generating function, mean and variance;

        - theorem of aditivity