Libertad Digital, publicado el 26 de septiembre de 2013.

This study was conducted with ethical considerations in mind (Khoza, 2004). Participants were selected on a voluntary basis and informed consent was obtained. The measuring instruments were considered based on their validity and reliability. Data was secured and considered highly confidential during this whole research project. A letter requesting consent, the letter of approval from the Department of Education and the questionnaires were handed to the principals of the schools. These were then issued to the teachers after thorough explanation by the examiner. The present research conformed to the code of ethics prescribed by the Board of Psychology of the Health Professions Council of South Africa.

102 3.8 DATA ANALYSIS

The research was conducted on (n=129) teachers from five high risk secondary schools from the Northern and Eastern Metropoles in the Western Cape. The statistical analysis was done using the SPSS computer package, version 17. The analysis involved obtaining inferential results, investigating the psychometric properties for the various questionnaires used as well as determining the inter-correlations between the different scales used. An analysis of the data of each instrument used were undertaken to determine the reliability of the test items. The hypotheses were constructed and the research was based on determining the significant relationships between the constructs. Statistical techniques namely, Pearson Product Moment, ANOVA, T-test and Multiple Regression Analysis were used. These are briefly explained to highlight their significance in the present study.

3.8.1 Pearson Product Moment

The Pearson Product Moment was considered suitable for use in this study, since it determined whether a statistically significant relationship existed between job stress, job satisfaction, job overload and job control of teachers. The Pearson correlation procedure measures the strength of association between variables (Josias, 2005) and is suitable for measuring interval and ratio scaled variables (Paulse, 2005). A positive relationship indicates that when occupational stressors increase, teacher stress also increases. An inverse relationship indicates that when occupational stressors increase, teacher stress decreases (Foxcroft & Roodt, 2005).

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The Pearson Product Moment was used to determine the hypothesis Ha, which states that job

satisfaction is not related to stress of teachers at high risk secondary schools in the Western Cape, Hb, which states that job overload is not related to stress of teachers at high risk secondary

schools in the Western Cape and Hc, which states that job control is not related to stress of

teachers at high risk secondary schools in the Western Cape.

3.8.2 Analysis of Variance (ANOVA)

The ANOVA deals with differences between sample means and has no restriction on the number of means (Howell, 1999 in Oosthuizen, 2005). Coolican (1999 in Paulse, 2005, p. 73), maintains that “analysis of variance procedures are powerful parametric methods for testing the significance of differences between sample means where more than two conditions are used, or even when several independent variables are involved.” ANOVA produces an F-statistic, which compares the amount of systematic variance in the data to the amount of unsystematic variance (Fields, 2000). It also tests for an overall experimental effect and provides information about the general success of the experimental manipulations; however it does not provide specific information about the affected groups (Oosthuizen, 2005). ANOVA creates feasibility in appraising the separate or combined influences of several independent variables on the experimental criterion. In this study, ANOVA was used to establish whether a statistical significant difference exists between the levels of stress based on the biographical details and the variables namely job satisfaction, job overload and job control.

104 3.8.3 T-Tests

T-tests are used to determine whether the sample was experiencing significant levels of stress or not. T-tests allows for the comparison of the means of two groups to analyze their unique differences based on the assumption that the two groups belong in the same population or two populations who possess the same population mean. The significant differences in the levels of stress of teachers based on their gender, was determined by using the T-test method (Oosthuizen, 2005).

3.8.4 Multiple Regression Analysis

In general, regression refers to the prediction of one variable from knowledge of one or more other variables, according to Howell (1999 in Oosthuizen, 2005). Babbie and Mouton (2007, p. 466) regard multiple regression as a means of analyzing how “a given dependent variable is affected simultaneously by several independent variables.” Foxcroft and Roodt (2005) view multiple regression as a technique that allows additional factors to enter the analysis separately so that the effect of each can be estimated.

The multiple regression analysis is suitable for use in the present study, since it provides a description of the relationship between teacher stress, job satisfaction, job overload and job control of teachers at high risk secondary schools in the Western Cape. The Multiple Regression Analysis was also used to determine the extent to which biographical factors explain the variance in the stress of these teachers.

105 3.9 SUMMARY OF THE CHAPTER

This chapter provided an explanation of the research design or research method employed in the study. The sample and procedure used in the study was explained. The measuring instruments and targeted population were discussed briefly. An explanation of the reliability, validity and justification of the instruments used were also provided. The stratified random sample of 129 teachers from five high risk schools in the Western Cape was chosen. The statistical analysis provided descriptive and inferential information. It included the Pearson Product, ANOVA, Multiple Regression Analysis and T-tests as well as a justification for each of their use in the study.

106 CHAPTER 4