When there are many people who don't need to expect something more than the benefits to take, we will suggest you to have willing to reach all benefits. Be sure and surely do to take this introduction to engineering statistics and six sigma that gives the best reasons to read. When you really need to get the reason why, this introduction to engineering statistics and six sigma book will probabl...

Objectives x Describe central tendency and variability x Summarising datasets containing two variables In covering these objectives we will deal with the following terms: x Mean, median and mode x Percentiles x Interquartile range x Standard deviation x Standard error of the mean In the first article of this series, we discussed graphical and tabular summaries of single datasets. This is a usef...

One crucial aspect of study design is deciding how big your sample should be. If you increase your sample size you increase the precision of your estimates, which means that, for any given estimate / size of effect, the greater the sample size the more “statistically significant” the result will be. In other words, if an investigation is too small then it will not detect results that are in fac...

Building on ideas from probabilistic dynamic epistemic logic, the aim of this workshop contribution is to present the practical details of how to build and use Bayesian models that can represent multi-agent uncertainty, including probability distributions over (other people’s) probability distributions. The key insight that underlies the approach taken here is that probabilities like PA(φ) are ...

The eld of statistics can be divided into two branches, descriptive statistics and inferential statistics. Descriptive statistics, as its name suggests, is concerned with describing a population, or a sample from that population, in terms of numerical measures that are computed from data. Such a numerical measure is called a statistic. If the data used in the computation comes from the whole po...