According to Florence Nightingale statistics is considered to be the most important science in the world as every other science from a social, political and educational perspective is dependent on it (Ridgeway, Nicholson & McCuster, 2007, p. 44). Statistical methods is a subject that organizes information and provides the necessary means for all other disciplines to deal with this particular information by taking the issue of variability into consideration. It therefore forms an essential part of most studies in the academic sphere (Coetzee & van der Merwe, 2010, p. 1). The objective of this methodological discipline is to provide students with the fundamental knowledge and skills to have an understanding of research to subsequently review
It is obvious that paradigm used in this research is quantitative as the data set and results of the data analysis are expressed in numbers. The researcher mentioned who are his sample group, and where they come from. He mentioned the tool used to analyze the data which is Item and Test Analysis Program (ITEMAN). The procedures are explained well, and he gave detailed information about the questions of the ACI. He mentioned the sources from which each question is taken.
Methodology This chapter presents the research design that was used in this study. It included the sample selection, instrument construction, pilot study, methods of data collection and data analysis 3.1. Design of The Study: A quasi-experimental design study is carried out through the
Under inferential statistics, reliability analysis and a logistic regression has been done. Descriptive statistics are used to represent analyzed data in a meaningful and a clear way. 4.2 Reliability Test. Reliability analysis for this research allowed studying the properties of measurements and scales and the items that compose scales. Reliability analysis calculates number of commonly
An example of this would be the study of an area that would benefit from qualitative research would be the style of a student’s learning ability along with his or her approaches to how they study. How they relate to the human services field is for one quantitative methodology refers to number / statistics area which in turn refers to the opinion polls, surveys, etc. of a number of people. Qualitative research methodology refers to a human service worker trying to understand a person who is needing help and by this the human service worker then understands the experiences of this person as well as their ideas, values and beliefs. It is like the scientific method only a bit more personal because the human service worker really gets to know the person / people he or she is helping in any case they deal with.
Simple Linear Regression Model Simple linear regression analysis was used to test hypotheses 1, 2 and 3. The influence of either advertising, word of mouth or sales promotion on consumer brand preference for mobile phone services was tested using simple linear regression. As pointed out by Field (2009), simple regression analysis shows how the criterion variable is explained by one dependent variable. Namada (2013), for instance, had used this method to indicate how the change in a firm performance is explained by strategic planning systems. In regression analysis, the coefficient of determination (R2) was used to show the change in consumer brand preference explained by either advertising, word of mouth or sales promotion.
1978. The contingency model and the dynamics of the leadership process, In Berkowitz, L., Advances in experimental social psychology, New York：Academic Press. Fisher, C.D.& Gitelson, R. 1983. A meta analysis of the correlates of role conflict and ambiguity, Journal of Applied Psychology, 68(2), 320-333. Fleishman, E.A.& Harris, E.F. 1962.
CHAPTER THREE METHHODOLOGY 3.0 Introduction This chapter focuses on the methodology that will be used in the study. The methodology was divided into two parts which is empirical model and econometric methodology. The econometric methodologies that have used include ordinary least square method and diagnostic test. Diagnostic test include stationarity test, multicollinearity test, test for model specification and significance of the model, heteroscedasticity test and correlation test. First, we check for stationary for each variable, if running an OLS regression on non-stationary series results in spurious regression.