ABSTRACT
Descriptive statistical techniques are very useful, but ultimately they only summarize and communicate the information contained in our samples. Very often we wish to go beyond these samples. For example, instead of only being able to say that, on average, the 50 employees in an organizational attitude survey have high levels of job satisfaction, we might want to generalize this finding, and say something about the average job satisfaction in the organization as a whole. With inferential statistical analysis this is made possible, and the purpose of this chapter is to introduce some of the main principles on which inferential statistical analysis is based. The first part of the chapter introduces samples, populations and probability, and the second part is concerned with associations, differences, statistical significance, effect sizes and statistical power.
