With this information, it might be tempting to generalize it that the hours of sleep causes variations to individual student’s general weighted average. At first, it may be good sounding and significant. However, the actual data has to be considered first prior to giving a generalized conclusion of the relationship between the dependent and independent variables. The actual result perhaps might prove that each individual has specific hours of sleep everyday. This might further shows that a five-hour sleep every night is enough for person A while exactly seven-hour sleep proves to be very important to be obtained by person B to do well at his or her daily tasks. Sounds intriguing but these are probabilities and this should be considered in making assumptions prior to investigating direct relationship between variables. From these assumptions alone, whatever they may be, it is important to consider that the hours of sleep cannot be directly explained to affect students’ general weighted average. Extensive data exploration can be applied to this.
Relationship can be manifested through association or causation. As humans, we are directly fascinated with finding for the cause of everything. However, it is a common practice that an association is always considered causation. In fact, this is the most common practice especially in exploratory data analysis in which a specific pattern is observed and then tested through inferences of an observed data. If relationship exists, then the data is considered significant up to the extent that it can be misleading since it is usually considered as the direct cause of something else.
One of the most common statistical tools used in defining relationship between variables is regression analysis. Regression analysis comes in different forms depending on the nature or type of data to be tested. In this analysis, it is important to consider ...Show more