Introduction
Research is usually carried out to determine or examine a relationship between two or more variables. The variables may be related to each other or may not have any relationship at all. When a variable is related to the other, statistically they are said to have a correlation. Correlation may be positive or negative. For a negative correlation, that means that the two or more variables are not strongly related to each other, while for a positive correlation, then it means that they depend on each other in a strong relationship.
In this essay discussion, a discussion will be based on looking at the two samples that depend to one another. For dependence samples that mean that, the outcome of the other sample is influenced the other characteristic. For instance, taking the example of college students, in that their performance at the end of the semester will be considered and a relationship investigated.
The performance one the students depend on the availability of the lecturers. If the college does not hire qualified lecturers, then the likelihood of students performing poorly is high. The reason as to why this discussion is appropriate is because learning is a continuous process and the data can easily be obtained since it is the primary source. In addition, the t-test is appropriate to use as it is a measure used to compare means in two related samples to determine whether there is any statistical difference between the means of the date.
The hypothesis of such data to be tested can be represented in either null or alternative hypothesis. This t-test is represented by students from Economics class and the Engineering class. The aim is to investigate whether there is any statistical difference in their means of performance. Take an example as economics students scored an average mark of 80 while the engineering students scored an average of 92 marks.
Hypothesis Illustrated
H0:µ1= µ2 (The mean score of the students from economics and engineering are the same)
H1: µ1≠ µ2 (The mean score of the students from economics and engineering are not the same)
H0: 80 Marks= 92 Marks
H0:80≠ 92 Marks
