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182      5 Non-Parametric Tests of Hypotheses


           these intervals, under the “z-Interval” heading,  which can be  obtained from the
           tables of the standard normal distribution or using software functions, such as the
           ones already described for SPSS, STATISTICA, MATLAB and R.
              The corresponding interval cutpoints,  x cut, for the random variable  under
           analysis, X, can now be easily determined, using:

              x cut  =  x +  z cut  s ,                                     5.9
                          X

           where  we use the sample  mean and standard  deviation  as well as the cutpoints
           determined for the normal distribution,  z cut. In the present case, the  mean and
           standard deviation are 137 and 43, respectively, which leads to the intervals under
           the “ART-Interval” heading.
              The absolute frequency columns are  now easily computed.  With SPSS,
                                                      *2
           STATISTICA and R we now obtain the value of χ = 2.2. We must be careful,
           however, when obtaining the corresponding significance in this application of the
           chi-square test. The problem is that now we do not have  df =  k – 1 degrees of
           freedom, but df = k – 1 –  n p, where n p is the number of parameters computed from
           the sample. In our case, we derived the interval boundaries using the sample mean
           and sample standard deviation, i.e., we lost two degrees of freedom. Therefore, we
           have to compute the probability using df = 5 – 1 – 2 = 2 degrees of freedom, or
           equivalently, compute the critical region boundary as:

              χ 2  . 0 , 2  95  =  . 5  99 .

                                         *2
              Since the computed value of the χ  is smaller than this critical region boundary,
           we do not reject at 5% significance level the null hypothesis of variable ART being
           normally distributed.

           Table 5.7.  Observed and expected  (under the normality assumption) absolute
           frequencies, for variable ART of the cork-stopper dataset.
                                                           Expected   Observed
             Cat.     z-Interval  Cumulative p ART-Interval
                                                          Frequencies Frequencies

              1  ]−  ∞, −0.8416]     0.20      [0, 101]      10         10

              2  ]− 0.8416, −0.2533]   0.40   ]101, 126]     10          8
              3  ]− 0.2533,  0.2533]   0.60   ]126, 148]     10         14

              4  ] 0.2533,  0.8416]   0.80    ]148, 173]     10          9

              5  ] 0.8416, + ∞ [     1.00       > 173        10          9
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