What statistical analysis do I use? My topic was: Are there significant multitasking differences between males and females.
I had a total of 90 subjects (45 males and 45 females) play an online game. The game consisted of levels, and their final score was in the form of a number (for example: 49 or 105 or 65, etc. I also had each subject play the game four times (for four trials) and report the score each time.
So a typical "Score Sheet" looked like this:
Practice Trial 1: 18
 Trial 1: 34
 Trial 2: 58
 Trail 3: 42
I was thinking, for each subject, of taking the average of their THREE HIGHEST SCORES and counting that as their "Final Score" For example, the "Final Score" of the above subject would be: 44.6666 ...that would be his/her "Final Score".....then, I use all subjects' Final Scores and use a T- test independent sample to  see if there are any significant difference...
Is this allowed, to take the average of each persons 3 highest scores or is there some other statistical test I have to do before moving on to the T-Test. By the way, I've never taken a statistics class in my life....this is for my Research class and our teacher somehow expects us to know about statistical analysis (I just found out what a T-test was a couple of minutes ago through Google and Youtube....I have no clue how to even begin or carry out a T-test, but I'll just have to figure it out )
Thank you! What do you think I should do?
 A: Given your level of expertise, your suggestion of averaging (some) of the scores and then carrying out a t-test to compare the groups is reasonable. Rather than select the 3 highest scores I think you should average all four, or perhaps average the last 3 (assuming that people get better at playing the game over time). Plotting the average of each trial by gender would help you see if that first trial is perhaps not representative of an individuals performance. 
What you have is called a "repeated measures design", and to analyze it properly is not an introductory level task. Search for "mixed models" on this site. The main issue is that although you have $90 * 4  = 360$ observations many of those observations are not independent of each other, because individuals differ in their game playing ability. Thus treating all the observations independently inflates your sample size. Averaging the observations within each individual solves this problem, albeit at the cost of throwing away other useful information like how much people improve as they play the game more times, and how much people vary in game playing ability. 
