Question

Evaluate the scope of quantitative research methodology comparing each method and critique each technique, model, metaphor, and paradigm. Select the best quantitative method and assess the strengths and weaknesses of that selected method defending why the selected quantitative method is the best. Compare various quantitative methods and how each method enables researchers to design the correct series of questions and eventually hypotheses to prove the theories. Recommend best methods to solve different types of analysis and provide a table that outlines each method, what type variables are used, best applications, and what findings to expect. Critique different regression analysis methods and determine what methods fit each analysis type. Assess the best procedure to develop a new construct starting from using a text analysis method, provide each stage of the process proposing what objective must be met for each stage developing a final best quantitative construct. Estimate the importance of data types in the selection and performance of measurements, the creation of survey instruments, and the application of specific findings coupled with best methodology. Assess the progress of structural equation modeling (SEM) and the new applications that SEM now offers researchers in the creation of improved constructs and theories. Judge the value of latent variable measures and how SEM is able to evaluate path analysis using conventional measures such as factor analysis, regression, correlation, and comparative means techniques.

Answer 1

Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Things to keep in mind when reporting the results of a study using quantitative methods:

Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
When using inferential statistics, provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level

Its main characteristics are:

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.Particular paradigms may be associated with certain methodologies. For example, as will be discussed in more detail later in this chapter, a positivistic paradigm typically assumes a quantitative methodology, while a constructivist or interpretative paradigm typically utilizes a qualitative methodology. This is not universally the case, however; there are instances in which one may pursue an interpretative study using a quantitative methodology. No one paradigmatic or theoretical framework is ‘correct’ and it is your choice to determine your own paradigmatic view and how that informs your research design to best answer the question under study. How you view what is real, what you know and how you know it, along with the theoretical perspective(s) you have about the topic under study, the literature that exists on the subject, and your own value system work together to help you select the paradigm most appropriate for you to use

On the question of what is the nature of reality, positivists hold that there is a single, tangible reality that is relatively constant across time and setting (known as naïve realism). Part of the researcher’s duty is to discover this reality. Positivists believe that reality is objective and independent of the researcher’s interest in it. It is measurable and can be broken into variables. Post-positivists concur that reality does exist but maintain that it can be known only imperfectly because of the researcher’s human limitations (known as critical realism). The researcher can discover reality within a certain realm of probabilityScholars paint theoretical canvases, using words, without always making transparent the logic of inquiry embedded within their writing. This is especially so when writing for their own epistemic communities, whose members share a set of usually unspoken methodological presuppositions concerning the `reality status' of what they study and its `know-ability'. When research topics engage scholars across epistemic communities, as in organizational studies, arguments may be difficult to parse precisely because these presuppositions remain implicit, unnoted and, perhaps, unnoticed. By enabling new ways of seeing familiar things, metaphors can facilitate such encounters by making the implicit less so. We turn to painting to enable metaphoric understanding of methodological differences in organizational and other social science scholarship, drawing on examples from the organizational identity literature. Much as artists look at the world around them and render things on canvas using a range of techniques, so researchers use methods reflecting ontological and epistemological presuppositions about their research worlds. Contrasting Rembrandt with Pollock presents, through metaphor, our case for seeing differences between realists and interpretative, whether they paint or do research