Both Table 1 and Table 2 value will be then used in determine the frequency table
of inter-arrival time and service time of the patients. Then, the observed and expected
value of the frequency of inter-arrival times and service timeswere obtained using
Chi-Square Test Goodness of Fit (CSTGF). This test was carriedout using SPSS.
The expected values obtained are important in deciding on whether the null hypothesis
is rejected. For our study, the null hypothesis is equal to the probability of expected
value of the frequency. The hypothesis testing is as follows:
Null Hypothesis 1: The inter-arrival time of the patients occur with equal
probabilities.
Alternate Hypothesis 1: The inter-arrival time of the pConflicting views had greeted the use of systematic sampling for sample selection and estimation
in stratified sampling in terms of the precision of the population mean base on the inherent characteristics
of the population. These conflicting views were analyzed using Cochran data (1977, p.
211) [1]. When the population units are ordered, variance of systematic sampling for all possible
systematic samples provides equal, non-negative and most precise estimates for all the variance
functions considered i.e. Vy Vy Vy 123 ( sy ) = = ( sy ) ( sy ) , unlike when a single systematic sample is
used and when variance of simple random sampling is used to estimate selected systematic samples.atients do not occur with equal
probabilities.
Null Hypothesis 2: The service time of the patients occur with equal probabilities.
Alternate Hypothesis 2: The service time of the patients do not occur with equal
probabilities.
Table 3 shows the summary of test statistics for inter-arrival times while Table 4
indicates the summary statistical test for service time. Both tables are carried out
using CSTGF using SPSS software.
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