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Testing criteria:

If this test use significance level  and the statistic t obtained from (T2)

or (T4), then

a. Testing criteria for the two-tailed test hypothesis (T1) as follows:

H0 is accepted if  t-actual   t/2-table , or

Pr = [ P ( t  -t actual ) + P ( t  t actual) ]   , otherwise

H0 is rejected if  t-actual  > t/2-table , or

Pr = [ P ( t  -t actual ) + P ( t  t actual) ] < .

To test whether the means of the first population is smaller than the mean

of second population, one-tailed test was used, with the following formulation of
the test hypothesis

b. Testing criteria for the one-tailed test hypothesis (T2) as follows:

H0 is accepted if t -actual  - t-table or Pr ( Z  tactual )   , otherwise

H0 is rejected if t -actual < - t-tabel or Pr ( Z  tactual ) <  .

Worked Example 4.6 :

Data on the test scores of direct and cooperative learning models

successively recorded at columns 2 and 3 in Table 4.2. Test the hypothesis that

the two models of learning (a) did not differ, (b) the cooperative model is better

than the direct model.

Worked Solution :

25 25
 X i  X i
Means: X = i= 1 = 1600 = 64 X = i= 1 = 1918 = 76 . 72
1
25 25 2 25 25

~~* CHAPTER 4 TESTING HYPOTHESIS *~~