One of interesting research directions is to determine whether the EI (emotional intelligence coefficient) of psychology students is significantly different from the EI of all university students. Emotional intelligence is determined as the ability to identify, reach and control own emotions, emotions of other people and group emotions. It is reasonable to suppose that there is a difference between EI value for psychology students and for all population of students, because psychologists often possess higher levels of empathy and higher sensitivity to other people already at the start of their career. The research question is: “Does EI value of psychology students significantly differ from mean EI for all university students?”.

Measurement of emotional intelligence will be performed using Emotional Intelligence Scale developed by Hyde (Ravichandra, Beena & Regani, 2007). Mean value of EI for the whole population of the university is supposed to be 170.0. A random sample of 200 psychology students will be selected from the whole population of students in order to determine mean value of EI for psychology students. Independent variable in this research is the specialization of the student (psychology or not specified specialization), and the dependent variable is the mean value of the EI.

For this research question, two-tail hypothesis should be used, because the research question is non-directional (it does not suppose the direction of difference between two mean EI coefficients, but is focused on the existence of this difference). Null statistical hypothesis for this research question states that there is no difference between mean EI value of all students and mean EI of psychology students: . Alternative statistical hypothesis for this research question is the following: there is a statistically significant difference between mean EI value for all students and mean EI value for psychology students: Alpha level will be selected at 0.05, as this value allows to reach a reasonable balance between the risk of type I error and type II error (Healey, 2011), which are both undesirable. Higher alpha value will lead to greater probability of rejecting a true null hypothesis, and lower alpha value will result in higher probability of failing to reject a false null hypothesis.

References

Healey, J.F. (2011). Statistics: A Tool for Social Research. Cengage Learning.

Ravichandra, K., Beena, C.& Regani, R. (2007). Psychological Well-being: Correlational and Intervention Studies. Global Vision Publishing Ho.