The scientific method as the underlying basis. Elements of the scientific method: concepts, definition, hypotheses theory. Statistical analysis as the process through which data becomes knowledge. Alternative models for statistical analysis. Procedures in classical statistics analysis. Samples, validity, reliability. Uses of statistics.
STATISTICAL ANALYSIS: THEORIES, CONCEPTS, AND PROCEDURES — A REVIEW Introduction The underlying basis of statistical analysis is the... more
STATISTICAL ANALYSIS: THEORIES, CONCEPTS, AND PROCEDURES — A REVIEW Introduction The underlying basis of statistical analysis is the scientific method. The foundations of the scientific method are (1) concepts, (2) definition, (3) hypotheses, and (4) theory. Concepts are basic to all thought and communication. The application of concepts provides the basis for the development of hypothesis statements. The success of scientific research depends upon (1) how clearly the investigator conceptualizes the problem and (2) how well others understand the concepts used by the researcher. A construct is a concept designed specifically for a particular research purpose or theory-building purpose (Pfaffenberger & Patterson, 1999).
Uses of statistics. Collecting, organization, analyzing and presenting data. Two basic types of data: categorical and Quantitative. Various approaches to organizing data and approaches to other tasks. Averages and variations. Theory of probability. Normal and Binomial distribution. Sampling distribution. Estimation. Hypothesis testing. Chi Square & ANOVA. Regression and correlation. Non-paramatric statistics.
INTRODUCTION TO STATISTICS Introduction The term “statistics” to many (perhaps most) people implies a collection of numerical data about... more
INTRODUCTION TO STATISTICS Introduction The term “statistics” to many (perhaps most) people implies a collection of numerical data about a topic. The extent to which most people have confidence in the validity of such a collection of data depends upon the topic, the source of the data, and the extent to which they think the data are measurable. As an example, most people are more likely to accept the accuracy of major league baseball statistics than are likely to express confidence in the accuracy of the failure rate of Firestone tires on Ford Explorers. The term “statistics” to a smaller proportion of the population refers to the processes of collecting, organizing, analyzing, and presenting data is forms usable for policy analysis, decision-m
Reviews elements of research. Defining the research approach; measure of association between two variables. Identifying an organizational situation amenable to study through correlational research. Establishing a causal relationship. Managerial questions appropriate for investigation. Describing data collection methods appropriate for correlational research.
CORRELATIONAL RESEARCH Introduction This paper reviews correlational research. The points of focus in the review are (1) defining of the... more
CORRELATIONAL RESEARCH Introduction This paper reviews correlational research. The points of focus in the review are (1) defining of the research approach, (2) identifying an organizational situation amendable to study through correlational research, (3) stating managerial questions appropriate for investigation through correlational research, and (4) describing data collection methods that are appropriate for correlational research. Defining Correlational Research Correlation quite literally is a measure of association between two variables. Correlational research more specifically refers to a measure of linear association between two variables. The range of the linear relationship between the variables, represented by a coef
Compares & contrasts the 2 methods in 3 basic areas: epistemological foundations, data collection & data analysis methods.
COMPARISON OF QUANTITATIVE AND QUALITATIVE RESEARCH METHODS Introduction This paper compares and contrasts qualitative and quantitative... more
COMPARISON OF QUANTITATIVE AND QUALITATIVE RESEARCH METHODS Introduction This paper compares and contrasts qualitative and quantitative research methods in three basic areas. These are the of their: epistemological foundations, data collection methods, and data analysis methods. The paper ends with a brief summary of the primary points made. Comparison Gall, Borg and Gall (1996) discuss several similarities and differences between qualitative and quantitative research methods. With respect to similarities, both kinds of research formulate epistemological positions regarding the nature of causation and reality and both comprise a set of methods for designing research, collecting data, analyzing data, and
Examines the approach of seeking to rule in plausible causes related to integrity of scholarly research, focusing on comparison of paradigms (exploratory vs. confirmatory, rational vs. naturalistic, quantitative vs. qualitative, more).
THE EMPIRICAL TRADITION IN HUMAN SCIENCE RESEARCH Introduction Empiricism holds that all knowledge is the product of personal experience... more
THE EMPIRICAL TRADITION IN HUMAN SCIENCE RESEARCH Introduction Empiricism holds that all knowledge is the product of personal experience (Slife & Williams, 1995). Philosophical behaviorism extends this idea to state that personal experience is the product of the between an organism and its physical and social environment. Materialism further extends the concept, stating that all behavior grows out of the interaction between physical objects and/or events (Slife & Williams, 1995). Empiricism contends, with respect to knowledge, that a class of purely conceptual propositions exist that are necessarily true because of the meanings of the words with which the propositions are expressed (Polkinghorne, 1983). The opposite of empiricism is rationalism. Rationalism denies the accept
Multiple regression analysis of demographics & proportion of population older than 16 included in labor force. Charts.
LABOR PARTICIPATION AS A FUNCTION OF SELECTED VARIABLES: A MULTIPLE REGRESSION ANALYSIS This research assesses the labor participation rate in... more
LABOR PARTICIPATION AS A FUNCTION OF SELECTED VARIABLES: A MULTIPLE REGRESSION ANALYSIS This research assesses the labor participation rate in the United States as a function of selected demographic factors. The labor participation rate is the proportion of the non institutionalized population aged 16 and over that is included in the civilian labor force, i.e., the proportion of that population segment that seeks paid employment (Bureau of Labor Statistics, 1994). The demographic factors selected for the assessment of the labor participation rate were as follows: 1. The proportion of African Americans in the total population. The U.S. Department of Labor publications refer to African Americans as “blacks.” Thus, the term “blacks” is used in the remainder of this research report.
Assesses this methodology, benefits & drawbacks, role of subjects, reliability, use in education, example (childhood sexual abuse).
Introduction Simply put, narrative research consists of studies in which the primary data source is some type of subject provided narrative; for... more
Introduction Simply put, narrative research consists of studies in which the primary data source is some type of subject provided narrative; for example, as in a discourse between one or more people on a particular subject, or a conversational storytelling (Mishler, 1995). According to Mishler (1995), narrative studies are essentially of three types: (1) those in which the research focus is upon the time between when the event occurred and the narrative in which it is discussed; (2) those in which the focus is upon strategies used to tell the story and/or the textual and structural elements of the narrative; and (3) those in which the function of the narrative is
Critical review of essays on gathering, assessing & interpreting historical evidence.
Historical Research and the Philosophy of History Most of the essays in the book, The Historian as Detective, approach history from a somewhat... more
Historical Research and the Philosophy of History Most of the essays in the book, The Historian as Detective, approach history from a somewhat scientific outlook. The authors of these essays deal with the problems of historical research and constructing a puzzle from a pool of tiny pieces, which are not all present. In this sense, the authors look at historical research as a scientific problem which must be solved by gathering and examining all of the evidence. Some of the authors deal with gathering these pieces, looking for hidden objects. Other authors deal with interpreting the evidence properly, keeping the valuable items while throwing out the worthless ones. The title of the book reflects the editor's bent: looking to the detective's vocation in fashioning an approach to historical evidence gathering and interpretation. Th
Describes & compares theories & techniques of two approaches to analyzing research data.
FACTOR ANALYSIS AND MULTIVARIATE ANALYSIS Introduction This research presents an overview of factor analysis and multivariate analysis... more
FACTOR ANALYSIS AND MULTIVARIATE ANALYSIS Introduction This research presents an overview of factor analysis and multivariate analysis procedures. Additionally, the advantages and disadvantages of each set of procedure are identified. Factor Analysis Many research studies generate vast quantities of data. These data more often than not are multidimensional and are characterized by multicollinearity (Summers, Peters, and Armstrong, 1993, p. 555). In most instances, if the data are to be used effectively, it is necessary to reduce the number of explanatory variables to more manageable proportions. Factor analysis is a general descriptor for a group of specific computational procedures (Emory, 1992, p. 559). Each of the pro
Defines & examines this distribution curve & its role in statistical analysis. Tables, graph.
Statisticians work with large masses of data. Before any conclusions can be drawn from such data, it must be condensed and arranged in a usable form.... more
Statisticians work with large masses of data. Before any conclusions can be drawn from such data, it must be condensed and arranged in a usable form. One of the most common ways to summarize and describe a mass of data is to arrange a frequency distribution table. These tables can then be graphed with the frequency scale on the y-axis and the interval being graphed on the x-axis. Above each interval a horizontal line is drawn which corresponds to the frequency of the interval, resulting in a stair-step histogram pattern. Connecting the midpoints of these class intervals produces a frequency polygon and an interval curve. Distribution curves which can be "folded" vertically so that the two halves of the curve are essentially the same are said to be bilaterally symmetrical. Perfectly symmetrical curves which have a bell shape are said to be normal curves, or Gaussian curve