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The general objectives of this study were to determine the work-home interaction of South African working females, to investigate the prevalence of work-home interaction and to determine if differences concerning work-home interaction exist between different demographical groups. An availability sample (n = 500) was taken from working females within six provinces of South Africa. The SWING and a demographical questionnaire were administered. Structural equation modelling (SEM) showed that a four-factor model, that measures both the direction (work-home interaction and home-work interaction) and the quality (positive or negative) of interaction, fitted the data best. All four factors were reliable, according to the Cronbach alpha coefficients. Multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) were used to establish differences between work-home interaction and different demographic characteristics. Statistically significant differences exist between demographic groups based on race, language, occupation, parental status, household situation and freedom to arrange circumstances. Recommendations were made for further research / Thesis (M.Com. (Industrial Psychology))--North-West University, Potchefstroom Campus, 2007.

The general objectives of this study were to determine the work-home interaction of South African working females, to investigate the prevalence of work-home interaction and to determine if differences concerning work-home interaction exist between different demographical groups. An availability sample (n = 500) was taken from working females within six provinces of South Africa. The SWING and a demographical questionnaire were administered. Structural equation modelling (SEM) showed that a four-factor model, that measures both the direction (work-home interaction and home-work interaction) and the quality (positive or negative) of interaction, fitted the data best. All four factors were reliable, according to the Cronbach alpha coefficients. Multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) were used to establish differences between work-home interaction and different demographic characteristics. Statistically significant differences exist between demographic groups based on race, language, occupation, parental status, household situation and freedom to arrange circumstances. Recommendations were made for further research / Thesis (M.Com. (Industrial Psychology))--North-West University, Potchefstroom Campus, 2007.

During the last year of World War I (1918), a second deadly foe was causing mortality around the world. Spanish Influenza killed an estimated 50-100 million people worldwide, including 50,000 people in Canada during the 1918-1919 pandemic. This thesis examines the impact of Spanish Influenza on people living in Vancouver, British Columbia, Canada between June of 1918 and June of 1919. Statistical analysis with SPSS was used to determine the association between influenza-caused deaths and socio-demographic characteristics such as age, gender, immigration status, and employment. In Vancouver, those who were between the ages of 19 to 39, and those who were employed, showed higher odds of dying from influenza during the epidemic. / Graduate

Darbe teoriniu lygmeniu išanalizuoti ir apibendrinti sprendimai, ugdantys vartotojų lojalumą, parengtas vartotojų lojalumo ugdymo struktūrinis modelis ir jis empiriškai patikrintas „Zara“ prekės ženklo pavyzdžiu. Pirmoje darbo dalyje atskleista vartotojų lojalumo konceptualioji esmė, išanalizuoti ir apibendrinti sprendimai, ugdantys vartotojų lojalumą bei pagrįstos vartotojų demografinių charakteristikų ir lojalumo sąsajos. Antroje darbo dalyje atlikta vartotojų lojalumo ugdymo teorinių modelių analizė. Remiantis teorinių tyrimų rezultatais, parengtas vartotojų lojalumo ugdymo struktūrinis modelis. Parengta vartotojų lojalumo ugdymo tyrimo metodika. Trečioje darbo dalyje atliktas vartotojų lojalumo ugdymo empirinis tyrimas ir apibendrinti jo rezultatai. Remiantis tyrimo rezultatais, empiriškai patikrintas vartotojų lojalumo ugdymo struktūrinis modelis. / The results of the theoretic and empiric research showed that brand and relationship marketing develops satisfaction and satisfaction creates consumer loyalty. The final work for Master consists of three parts. The first part reveals the conceptual nature of consumer loyalty. Also it consists of analyze and summary of consumer loyalty development decisions. The second part presents and analyzes the theoretical model of consumer loyalty development decisions. And based on results of the theoretical research the structured model of consumer loyalty development is presented. The third part consists analysis of results of empirical study and validation of theoretical model of consumer loyalty development decisions.

This is a descriptive study of functional specialization in cities and its relation to certain social, economic and demographic variables.

Magister Philosophiae - MPhil / This thesis examines the distribution of African migrants across the different segments of the labour force in South Africa. The specific objective of this study is to demonstrate that there has been structural changes from 2001 to 2011 in the deployment of African immigrants in terms of occupation, employment sector, income groups just to name a few. Studies that have been recorded using the 2001 population census suggest that the South African labour market attracts majority of African migrants that are not highly qualified. The proposed study makes use of the 2011 population census to evaluate the extent to which the situation has changed or whether it remained the same between the two periods. The assumption underlying this study is that, over time the magnitude of qualified migrants has improved. As far as African migration is concerned, to capture the structural changes during the ten-year period (2001 to 2011) this study focuses on variables such as demographic and socioeconomic characteristics. To profile changes in the participation of African migrants, this study makes use of the 2001 and 2011 national population census data. Furthermore, statistical packages are used to test the relationship between variables. Policy document about migration are also used to provide the legislated framework with regards to the involvement of foreign labour in the South African labour force. The geographical scope of the study is national meaning it covers all nine provinces of South Africa.

A dissertation submitted to the Faculty of Education in fulfilment of the requirements for the Degree of Master of Education (Research Methodology) in the Department of Educational Psychology at the University of Zululand, 2017 / Given the need to employ effective reading strategies in the primary school, this article sets out to address the question of primary school educators’ experiences with the National Reading Strategy (NRS). The study focuses on six (6) primary schools in the Mbabane Circuit at Ingwavuma in UMkhanyakude District of South Africa. Forty (40) primary school educators from the selected schools within the circuit took part in a quantitative survey. Pearson’s chisquare was employed to explore the relative effects of teachers’ biographical data and their experiences with the NRS. The findings suggest that teachers’ gender, job title, teaching phase, experience in years and qualifications had an influence on their experiences with the NRS. On the other hand, teachers’ age was shown to have no relationship with their experiences with the NRS. The study confirms the appropriateness of understanding how teachers’ biographical data relate to and impact on reading intervention strategies.

This research addresses the novel application of design of experiment, artificial neural net-works and logistic regression to study the effect of demographic characteristics on the risk of acquiring HIV infection among the antenatal clinic attendees in South Africa. The annual antenatal HIV survey is the only major national indicator for HIV prevalence in South Africa. This is a vital technique to understand the changes in the HIV epidemic over time. The annual antenatal clinic data contains the following demographic characteristics for each pregnant woman; age (herein called mother's age), partner's age (herein father's age), population group (race), level of education, gravidity (number of pregnancies), parity (number of children born), HIV and syphilis status. This project applied a screening design of experiment technique to rank the effects of individual demographic characteristics on the risk of acquiring an HIV infection. There are a various screening design techniques such as fractional or full factorial and Plackett-Burman designs. In this work, a two-level fractional factorial design was selected for the purposes of screening. In addition to screening designs, this project employed response surface methodologies (RSM) to estimate interaction and quadratic effects of demographic characteristics using a central composite face-centered and a Box-Behnken design. Furthermore, this research presents the novel application of multi-layer perceptron’s (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees. A review report was produced to study the application of neural networks to modelling HIV/AIDS around the world. The latter report is important to enhance our understanding of the extent to which neural networks have been applied to study the HIV/AIDS pandemic. Finally, a binary logistic regression technique was employed to benchmark the results obtained by the design of experiments and neural networks methodologies. The two-level fractional factorial design demonstrated that HIV prevalence was highly sensitive to changes in the mother's age (15-55 years) and level of her education (Grades 0-13). The central composite face centered and Box-Behnken designs employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa, demonstrated that HIV status of an antenatal clinic attendee was highly sensitive to changes in pregnant mother's age and her educational level. In addition, the interaction of the mother's age with other demographic characteristics was also found to be an important determinant of the risk of acquiring an HIV infection. Furthermore, the central composite face centered and Box-Behnken designs illustrated that, individual-ally the pregnant mother's parity and her partner's age had no marked effect on her HIV status. However, the pregnant woman’s parity and her male partner’s age did show marked effects on her HIV status in “two way interactions with other demographic characteristics”. The multilayer perceptron (MLP) sensitivity test also showed that the age of the pregnant woman had the greatest effect on the risk of acquiring an HIV infection, while her gravidity and syphilis status had the lowest effects. The outcome of the MLP modelling produced the same results obtained by the screening and response surface methodologies. The binary logistic regression technique was compared with a Box-Behnken design to further elucidate the differential effects of demographic characteristics on the risk of acquiring HIV amongst pregnant women. The two methodologies indicated that the age of the pregnant woman and her level of education had the most profound effects on her risk of acquiring an HIV infection. To facilitate the comparison of the performance of the classifiers used in this study, a receiver operating characteristics (ROC) curve was applied. Theoretically, an ROC analysis provides tools to select optimal models and to discard suboptimal ones independent from the cost context or the classification distribution. SAS Enterprise MinerTM was employed to develop the required receiver-of-characteristics (ROC) curves. To validate the results obtained by the above classification methodologies, a credit scoring add-on in SAS Enterprise MinerTM was used to build binary target scorecards comprised of HIV positive and negative datasets for probability determination. The process involved grouping variables using weights-of-evidence (WOE), prior to performing a logistic regression to produce predicted probabilities. The process of creating bins for the scorecard enables the study of the inherent relationship between demographic characteristics and an in-dividual’s HIV status. This technique increases the understanding of the risk ranking ability of the scorecard method, while offering an added advantage of being predictive.

This research addresses the novel application of design of experiment, artificial neural net-works and logistic regression to study the effect of demographic characteristics on the risk of acquiring HIV infection among the antenatal clinic attendees in South Africa. The annual antenatal HIV survey is the only major national indicator for HIV prevalence in South Africa. This is a vital technique to understand the changes in the HIV epidemic over time. The annual antenatal clinic data contains the following demographic characteristics for each pregnant woman; age (herein called mother's age), partner's age (herein father's age), population group (race), level of education, gravidity (number of pregnancies), parity (number of children born), HIV and syphilis status. This project applied a screening design of experiment technique to rank the effects of individual demographic characteristics on the risk of acquiring an HIV infection. There are a various screening design techniques such as fractional or full factorial and Plackett-Burman designs. In this work, a two-level fractional factorial design was selected for the purposes of screening. In addition to screening designs, this project employed response surface methodologies (RSM) to estimate interaction and quadratic effects of demographic characteristics using a central composite face-centered and a Box-Behnken design. Furthermore, this research presents the novel application of multi-layer perceptron’s (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees. A review report was produced to study the application of neural networks to modelling HIV/AIDS around the world. The latter report is important to enhance our understanding of the extent to which neural networks have been applied to study the HIV/AIDS pandemic. Finally, a binary logistic regression technique was employed to benchmark the results obtained by the design of experiments and neural networks methodologies. The two-level fractional factorial design demonstrated that HIV prevalence was highly sensitive to changes in the mother's age (15-55 years) and level of her education (Grades 0-13). The central composite face centered and Box-Behnken designs employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa, demonstrated that HIV status of an antenatal clinic attendee was highly sensitive to changes in pregnant mother's age and her educational level. In addition, the interaction of the mother's age with other demographic characteristics was also found to be an important determinant of the risk of acquiring an HIV infection. Furthermore, the central composite face centered and Box-Behnken designs illustrated that, individual-ally the pregnant mother's parity and her partner's age had no marked effect on her HIV status. However, the pregnant woman’s parity and her male partner’s age did show marked effects on her HIV status in “two way interactions with other demographic characteristics”. The multilayer perceptron (MLP) sensitivity test also showed that the age of the pregnant woman had the greatest effect on the risk of acquiring an HIV infection, while her gravidity and syphilis status had the lowest effects. The outcome of the MLP modelling produced the same results obtained by the screening and response surface methodologies. The binary logistic regression technique was compared with a Box-Behnken design to further elucidate the differential effects of demographic characteristics on the risk of acquiring HIV amongst pregnant women. The two methodologies indicated that the age of the pregnant woman and her level of education had the most profound effects on her risk of acquiring an HIV infection. To facilitate the comparison of the performance of the classifiers used in this study, a receiver operating characteristics (ROC) curve was applied. Theoretically, an ROC analysis provides tools to select optimal models and to discard suboptimal ones independent from the cost context or the classification distribution. SAS Enterprise MinerTM was employed to develop the required receiver-of-characteristics (ROC) curves. To validate the results obtained by the above classification methodologies, a credit scoring add-on in SAS Enterprise MinerTM was used to build binary target scorecards comprised of HIV positive and negative datasets for probability determination. The process involved grouping variables using weights-of-evidence (WOE), prior to performing a logistic regression to produce predicted probabilities. The process of creating bins for the scorecard enables the study of the inherent relationship between demographic characteristics and an in-dividual’s HIV status. This technique increases the understanding of the risk ranking ability of the scorecard method, while offering an added advantage of being predictive.