Selecting a Statistical Test
The hypothesis in the second research question proposes that there exists no difference in the mean number of training hours for the employees after and before the training program. The study will involve all the 925 drivers in order to assess the training program’s effectiveness. The data collected will be classified into three main categories; performance, demographic and assessment data. Demographic data will be information about the drivers such as identity, gender, salary and area based. Performance data will be used in assessing effectiveness of the training. Assessment data is the information about the drivers’ opinion about the training’s effectiveness.
The second hypothesis can be addressed by comparing the average number of hours before the training and the average training hours after the study. The two will then be compared to establish the difference. In order to accomplish this task, the researchers will need to use various kinds of information from the performance data. These include the skill levels, hours of training, jobs assigned, days at work on the road and the years a driver has been at the company. To test the hypothesis, the researcher can use a t-test because the investigation is about one independent variable, training which has two levels, before and after then there is one dependent variable, effectiveness of the training. Descriptive statistics can help in deciding the statistical test to use. The use of the standard deviation and average, which can be easily calculated from the available data, will be important in choosing the t-test as the preferred statistical procedure for the research.
Reference
Greene, J., & D'Oliveira, M. (2005). Learning To Use Statistical Tests In Psychology (3, revised, reprint ed.). New York: McGraw-Hill International.
