Introduction The main objective of this exercise is to use two sets of data; smoking 1.sav and grades 2.sav to develop and test hypothesis. The data will be used separately to answer three different questions. Ideally independent samples T-test is used when one wish to determine whether the difference between means for two sets of scores is significant. Dependent variable will be carried out in part two. It is worth noting that the type of data used as test variable should be interval or ratio while the grouping variable is categorical. Using Grades2.sav Section 1 The variables to be used in this case are gender as the grouping variable and percent as test variable. Hypotheses:   * H 0 : The gender of an individual influences the grade obtained.   * H 1 : The gender of an individual does not influence the grade obtained It is my assumption that females due to the fact that they have more household responsibilities than their male counterparts, they have less time to do personal studies at home. For this reason, they will have lower grades compared to male students. Table 1: Group Statistics          gender  N      Mean    Std. Deviation  Std. Error Mean percent  FEMALE  64     81.55   11.105          1.388           MALE     41      78.46  13.517  2.111           Table 2: Independent Samples Test                                                       Levene’s Test for Equality of Variances  t-test for Equality of Means F                            Sig.                     t                                        df                            Sig. (2-tailed)  Mean Difference  Std. Error Difference  95% Confidence Interval of the Difference Lower                        Upper                   percent                      Equal variances assumed  1.588                                    .210                          1.274            103              .206                   3.083                                      2.420   -1.717  7.884 Equal variances not assumed                                                                    1.220                         73.365           .226             3.083                  2.527                                      -1.951  8.118   An independent sample t-test was undertaken to determine whether there was a significant mean difference in the grade in terms of percent between males and females. The results from the analysis indicates that there was no statistical significance, (t=1.220, DF=73.365, p=0.226). However the finding shows that the mean for male was 81.55 while that of the female was 78.46. This means that more male got slightly higher percents that female. This may mean that there are other factors that determine the percent one gets. To this end, the hypothesis that “The gender of an individual influences the percent obtained” is not supported and thus I fail to accept it. Based on this result I can conclude that the gender of individual does not influence the percent one gets in tests. There might be other factors other than gender that dictates what one gets in terms of percent. Figure 1: Graphical representation of differences between the groups From figure 1 it is evident that there were differences in percent based on the gender. Section 2 T