The last section details statistical treatment of data. 4.1 Research Method Used In this study, descriptive research is used to investigate how e-loyalty is influenced by several factors. Descriptive research is defined by Zikmund (2003) as the research designed to describe characteristics of a population or a phenomenon and is aims to “determine the answers to who, what, when, where and how questions.” Also it is stated that descriptive research can be used to evaluate the proportion of people in a specified population who behaves in a certain way (Churchill, 1999). The research has applied the survey technique, distributing the questionnaires to collect data from respondents. A sample survey was used in such a way that sample of respondents would be representative of a specific population.
Initially we test that two variables are associated or not. If two variables are associated then we find strength of this association by appropriate statistic. Cross tabulations can be produced by a range of statistical packages, including some that are specialized for the task. By using the cross tabulation technique, in this section we will analyze the association between variables. We will also test the correlation among them.
This trait is was found to correlates to one’s subjective discounting, degree of materialism and ability to delay gratification. The aim of this assignment is to assess whether someone’s subjective discounting, degree of materialism and ability to delay gratification can be accurately measured and generalised. The assignment will used data from 64 filled-in questionnaires that concerns subjective discounting, degree materialism, and delay of gratification. The assignment starts by discussing on the cleansing of the data to decide the number of respondents that will be included in the analysis. Next, it outlines how principal component analysis (PCA) is computed on three model of impatience (HD, ED, Count F) to find the measure of the models.
Ghozali (2001) stated a variable is reliable if the responds from the respondents are consistent across the research. The purpose of the reliability test is to measure the consistency of the measurement items. Writer are going to measure the variable‘s cronbach alpha to measure the internal consistency of variables. Ghozali (2001) added that if the cronbach alpha value of a variable is higher than 0.6 it means that the variable is reliable. Statistical Method Classic Assumption Test When a research uses multiple regressions as the statistical tool, that research directly use several assumption (Lind and Marchal and Whaten, 2008).
It can also be used to summarize or describe any outfit whether it is a population or a sample, as in the preliminary stage of statistical inference the elements of a sample known. Statistical Inference refers to the process of making generalizations about the properties of the whole population, based on the specific, which shows their implicit a number of risks. To these generalizations are valid sample must be representative of the population and the quality of information should be controlled , as well as the conclusions and lessons I are subject to errors, you need to specify the risk or probability that one can commit those mistakes. Inferential statistics is the set of techniques used to draw conclusions that go beyond the limits of the knowledge provided by the data, looking for information of a collective through a methodical process of managing sample data. DESCRIPTIVE STATISTICS: It is the branch of statistics that deals with the collection, presentation, description, analysis and interpretation of a dataset.
The primary factors that are important in conducting statistical test are variables (categorical or quantitative) and the number of (IVs) independent variables and (DVs) dependant variables. To facilitate the identification process the chapter provides two decision- making tools so that it is easier to make a decision. The chapter presents the decision making tools and gives an overview of the statistical techniques addressed in this text as well as basic univariate test, all of which will be organized by the four types of research questions: degree of relationship, significance of group differences, prediction of group membership, and structure. Statistical test that analyze the degree of relationship include bivariate correlation and regression, multiple regression and path analysis. Research questions addressing degree of relationship all have quantitative variables.
(Holmes-Smith, Coote, & Cunningham, 2004) On specification the model is then tested for plausibility based on the sample data that comprise all observed variables in the model. The main task in model testing is to determine the goodness-of-fit between the hypothesized model and the sample data. Fit Indices There is abundance of fit indices and wide variety of disparity in agreement on which indices to report and also the cut-offs for various indices, (Hooper, Coughlan, & Mullen, 2008) because dif... ... middle of paper ... ...are the options to verify the dimensionality of the measurement or to verify the model fit. The modification of the model is aided by modification indices (MIs) sometimes in conjunction with parameter estimates statistics. (Lei & Wu, 2007) These indices were examined during evaluation of model fit to get the direction of modification, for example whether freeing or incorporating parameters either between or among unobserved variables is required in obtaining better model fit.
Numerical summaries which can either measure the central tendency of a given set of data or which describe the spread of a given data. They use ... ... middle of paper ... ...he data. It will be also paramount to investigate the results using evaluative means like the ANOVA test, which uses variance and makes sure that averages exists within every variable test group. There is also need to set a regression, which is a general statistical tool, which sees how variables are interconnected. Finally, there is the need to analyze the qualitative element of the analysis (Chance et al, 2005).
Descriptive Statistics Tools and Histograms Descriptive statists provide a description of the the central properties of data obtained from observations. In quality management, the central properties can provide basic information concerning the amount of variance from a desired norm, which is a major advantage of using descriptive statistics. For example, descriptive statistics can provide information about the frequency of variance in desired tolerance that is greater than 10%, with less than 10% as the desired norm. In quality management, the descriptive statistical data that is of greatest interest is the central tendency, the dispersion, and the frequency (Madan, 268). In ad... ... middle of paper ... ...pes of information.
It was concluded that a number of statistical techniques such as factor analysis, t-test, ANOVA, ,X 2 test, discrisminant analysis, linear and logistics regression analysis are found to be utilized to test the survey instrument for data analysis purposes. This chapter also describes about the qualitative and quantitative analysis using N Vivo software and Excel spread sheet. This chapter thoroughly covered the three essential components of survey research approach. 'Instrument development and its validation' was briefly introduced. The next Chapter 6 will describe the ‘development and validation of the survey instrument’ which is considered to be important and essential for a reliable data collection.