Metodos Cuantitativos Para Los Negocios Anderson Pdf 14 ((EXCLUSIVE))
Metodos Cuantitativos Para Los Negocios Anderson Pdf 14
In the non-parametric bootstrap alternative inference is obtained using a standard percentile confidence interval. We use a bootstrap of each distribution with k samples. We need a separate bootstrap distribution for each of the distributions. This means that the null hypothesis can not be rejected using a confidence level of 95 percent.
Each of the probabilistic approaches in this course can be used to estimate risk; therefore, this section introduces two methods for estimating risk: A Monte Carlo simulation can be used to estimate this probability.  For Monte Carlo analysis a bootstrap is used to develop an empirical distribution from which the confidence interval is computed. This method is applied to risk estimation by other methods, as well as by Monte Carlo.  Monte Carlo simulation is easy to apply. In addition, it is one of the few methods that can show clearly how the accuracy of the parameter estimates is affected by the sample size. Monte Carlo has two advantages over the other two methods. First, because the number of samples is small, Monte Carlo analysis is relatively inexpensive to perform and the parameters can be accurately estimated using linear regression. Secondly, Monte Carlo allows us to obtain the probability of a specified value of a parameter. This feature is really important, since it means that if the probability is less than 0.5, the risk cannot be calculated. Consequently, Monte Carlo enables us to answer the question about risk using a very simple method. This is of great importance, since most of the concepts learned in the statistical analysis courses in the college are related to risk. Finally, Monte Carlo analysis is widely used in industry to determine product quality and safety. This is why it is more than a statistical method, but it is an analytical method. The three other techniques only estimate risk, but do not determine whether the risk is greater or less than a specified value. ]