nation, were tabulated. Results of this tabulation showed that students admitted according to their average mark in school and their test score achieved, on average, showed the best total score on the examination. The second best score was related to those who had been admitted due to their test result alone. Students who were admitted on the bases of their entrance interview or to the time they had been queuing, showed the poorest scores on the examination. Correlation coefficients were as follows: .45 for the relationship between total test score and total exam score, .47 for the relationship between average mark in school and total exam score, and .54 for the relationship between combination of test score and average mark and total exam score. These findings are shown in Table 1.
Terms used in hypothesis testing include: null hypothesis (H0), a statement of zero or no change which always includes the equal sign (the decision is based on the null hypothesis); alternative hypothesis (H1 or Ha), a statement which is true if the null hypothesis is false; level of significance; probability value (P-value) or the probability of getting the results obtained if the null hypothesis is true; critical region or the set of all values which would be cause to reject H0 ; critical value(s) refers to the value(s) which separate the critical region from the non-critical region; and significance level (alpha) or the probability of rejecting the null hypothesis when it is true (alpha = 0.05 and alpha = 0.01 are commonly used) (Witte, 1980).
To make a decision regarding a hypothesis, a statement is made based on the null hypothesis. The statement either rejects the null hypothesis or fails to reject the null hypothesis. When the level of significance is the area beyond the critical values, then the probability value is the area beyond the test statistic (the sample statistic used to decide whether to reject or fail to reject the null hypoth...