# paired t-tests and interpretation of results

My study is about comparing the scores a group of students (sample, N=14) in two different conditions. They play the same game in a tablet and using a computer. They were administered with a questionnaire to evaluate the dependent variable (experience), which is made up of five different components. I found out that the mean value of each component is slightly greater in the tablet game. However, the p-value was greater than the standard alpha level of 0.05 in each case. which leads us to fail to reject the null hypothesis. The null hypothesis, Ho: Difference of the Means is zero. Alternative Hypothesis H1: Difference of the Means is not equal to zero.

How do we interpret this result? Can we say that they had the same experience in both Tablet and Computer environment, since the p-value was not significant. But how do we interpret the fact that the Mean Value was slightly greater for each component in the Tablet vs. Computer Game. For instance, component A: (µTablet:3.64 and µComp: 3.54); component B (µTablet:3.95 and µComp: 3.23); component C (µTablet:3.73 and µComp: 3.71); component D (µTablet:3.80 and µComp: 3.63); component E (µTablet:3.75 and µComp: 3.50).

Is it that N=14 (is not normally distributed), and is too small of a sample?

• Regarding "is too small of a sample"... that's what pilot studies and power calculations are for - to help you find a suitable sample size. In some situations, 14 might be plenty big enough to pick up the size of difference that might be interesting to you; in others it might fall well short. One thing that's not clear from your description is whether you considered the potential for order effects (e.g. that people tended to prefer whatever they played first). Jan 12, 2015 at 1:38
• Yes, order effects were taken into consideration Jan 12, 2015 at 14:21