The use of job costing as a tool for the pricing and cost control decisions in the printing industry: the case of Société de Presse et d'Editions (SOPECAM)
par Christian Kuiate Sobngwi
University of Buea - Bachelor of Science 2003
Data will be collected from primary and secondary sources.
In this study we will pay a particular attention to the evolution of the unit cost of the newspaper Cameroon Tribune and its effects on the pricing and cost control policies.
Data will be analysed using both qualitative and quantitative models. But much of the analysis will be done using quantitative tools.
In this study, we will make use of the Student's-t distribution in order to test our hypothesis.
The Student's-t-distribution is a probability distribution used to test the research hypothesis for situations involving the comparison of two means when the sample size is small or when the variances are not known.
As stated by Grais23(*) (2000), the model assumes that there are two populations P1 and P2 from which two samples are collected:
· A sample X11, X12...X1n of size N1 taken from P1
· A sample X21...X2n of sizeN2 taken from P2
In our case, the populations will be represented by the monthly production of the newspaper and we will draw a sample production week from that month. Let us assume that ì1and ì2 are the respective mean unit costs of the week obtained by applying absorption and variable costing respectively and ó²1 and ó²2 are the respective unknown variances whose sample estimates suggest relatively equal variances that is S²1=S²2.
The sample sizes, represented by the number of production days per week, that is 5, being known and less than 30, there is a need to estimate a pooled weighted variance denoted S²
(N1-1) S²1 +(N2-1) S²2
S² = ........equation 3.1
? (X1i-A1) ²+? (X2i-A2) ²
= ...........equation 3.2
It appears that the difference in means A1-A2 is normally distributed with mean and variance expressed as follows:
(N1-1) S²1 + (N2-1) S²2
A1-A2 ~N [ì1-ì2, .eq.3.3
From this information, it is now possible to state our hypothesis in mathematical terms such that it can be tested using the afore-mentioned test.
Ho: (Null hypothesis) A1-A2=0, there is no difference between the sample means and both can be used for the same purposes.
H1: (Alternative Hypothesis) A1-A2?0 the two sample means are different and cannot be used for the same purposes.
It is now necessary to start with the analysis of the data collected and the test of the research hypotheses; this will be done in the next chapter, which is mainly about the presentation and the analysis of the results of the study.
* 23 Grais, B.(2000), Méthodes Statistiques (3rd edition), Dunod, Paris.