Abstract This document discusses a series of descriptivestatistics questions. These range from the four types of errors related to measurement as well as response and non-response related errors. Finally, the paper makes several statistical calculations in order to establish the efficacy and practicality of descriptivestatistics. Specifically, these problems rectify issues of accuracy and estimation.
From the Paper "The four major sources of measurement error are respondent, situation, measurer, and instrument. Respondent errors might occur through respondent misinterpretation of a given question or, in the case of a written survey or questionnaire, actual response error (Lomax, 2001, pp.29-31). A situational error would occur when, for example, a political survey for a given district was being taken in another district. Measurer originated errors can occur in several ways from construction and design of the actual study to poor selection of participants as well as misinterpretation of study results or actual errors in compilation of results. Instrument, such as surveys or questionnaires, often occur because they question or respond to something other than what is being tested or researched. "
Abstract The paper discusses the qualitative versus quantitative issue in educational research. The paper describes the four main purposes to using statistics in educational research. The paper also looks at four types of descriptivestatistics and at inferential statistics. The paper addresses the counterbalancing of data.
From the Paper "Where educational research is concerned, the qualitative versus quantitative issue likely plagues every study that has ever been done, regardless of whether it is qualitative or quantitative in nature, because there are concerns about how each study was carried out. This is largely due to the fact that there are always various arguments and differing opinions as to which one method is better for which type of study. Since most educational studies focus on the qualitative side of things, they do not address statistical figures as much as they would if they were quantitative. Some will see this as a problem with these types of studies, and will want hard and fast data that they can analyze."
Abstract This paper discusses statistical analysis as a dynamic form of study that evolves over time to meet developing needs and to exploit developing capabilities and technologies. The author points out that statistical analysis is the process through which data becomes knowledge and is a science to assist one in making decisions under conditions of uncertainty. The paper relates that the most appropriate logic bases for the discipline of statistical analysis in the contemporary period are rational, quantitative, positivist and causality.
Table of Contents
Introduction: Reflections on Statistics Reviewing Statistical Analysis
Defining Statistical Analysis
Alternative Logic Bases for Statistical Analysis
Rational Model versus Naturalistic Model.
Quantitative Model versus Qualitative Model.
Positivist Model versus Normative Model.
Causality Model versus Plausibility Model
Exploratory Model versus Confirmatory Model.
Randomization Model.
Conclusion: Reviewing Statistical Analysis.
Examining the Classical Model of Statistical Analysis
DescriptiveStatistical Analysis
Exploratory Statistical Analysis
Inferential Statistical Analysis
Probability Theory and Classical Statistical Analysis
Conclusion: Classical Statistical Analysis
From the Paper "Descriptive statistical analysis describes the performance or activity of one group or class, without attempting to generalize about other groups or classes. Classification, description, and measurement are activities applicable to variables associated with social research. The classification of variables is based on an assumption that social units are comparable within the context of specific definitional criteria. A social researcher attempts to control variation through the classification of variables. The description of variables is an effort to assign some degree of uniqueness to each variable, in order to provide a basis for the establishment of relationships among variables. The measurement of the extent of the uniqueness of variables generates the quantitative indicators of the strength of the relationships between variables. The process of classification, description, and measurement facilitates the development of causal explanations for both regularities and variations in empirical phenomena. Comparisons are made according to the degree of differentiation of structure in data in relation to a common and less differentiated point of origin. Such comparability is dependent upon both the classification of the social unit and the dimension of that social unit that is being measured. The dimension is the variable being measured."
Abstract This paper focuses on statistics by explaining the statistical process and the primary purpose of statistical processes and then outlining the best practices for statistical procedures. The paper also explains the purpose of statistics and how they are used for product research.
Introduction
Statistics and Their Importance to Research Investigation
Correct Statistical Processes
Summary
From the Paper "Before there can exist any intelligent discussion with respect to the topic of statistics one must understand that a statistical process does not stand alone nor does it function without being a part of a much larger plan, namely, research investigation as a whole. Statistics and their accompanying processes are only one such part of the research plan and, as such, must be viewed in totality of purpose over single identification. Without a formidable research plan a statistical process is without merit and akin to discussing how many angles can be placed on the head of a pin. In general, and from a philosophical perspective, the research plans and statistical analysis, according to Ohlson (1998) "...are not unlike an artist's canvas, as they strive to capture forever the intrinsic and observable subject placed before it" (10)."
Abstract This paper identifies a research issue, opportunity or problem that uses a data set consisting of at least 10-20 absolute zero measurements. In particular, the paper details primary and secondary data obtained from the Internet and other resources that expound upon the issue of declining teen pregnancy rates in the US. The paper further describes the methods used to collect the data along with calculations for the measures of central tendency and dispersion. The paper then displays the descriptivestatistical data using graphic and tabular techniques along with an explanation of the data. The paper concludes with an action plan for the teenage pregnancy issues based on the data.
Outline:
Abstract
Introduction
Literature Review
Hypothesis
Methodology
Data Analysis
Conclusion
From the Paper "The pregnancy rate of teenagers in the United States continues to be an issue of high social concern. "While teenage birthrates have declined significantly in the past decade, they remain high and still impose a social and individual cost" (King, 2005). Knowing the rates have declined, a relevant question is; what factors facilitated the decline and can the factors be used to continue the decline? Two reasons accredited for the decrease in trend include the increased accessibility and use of family planning services and the exposure given to the dangers of unprotected sex by the mainstream media. Additionally, this report will provide details on the collection of primary data associated with the hypotheses."
Tags: data, teenage, pregnancy, family, planning, counseling, sex, health
Abstract This paper studies how graduate students perceive the study of statistics and the impact that their anxiety about the subject matter has on their overall performance. The paper cites several research studies which indicate that statistics anxiety is quite high. Furthermore, the paper proves that this anxiety significantly erodes the overall quality and level of the students' research projects. The paper then offers suggestions to improve the teaching of statistics, as well as other suggestions to strengthen students' skills at statistical analysis.
From the Paper "Statistics anxiety has been defined simply as anxiety that occurs as a result of encountering statistics in any form and at any level (Onwuegbuzie, DaRos, & Ryan, 1997), and has been found to negatively affect learning (Onwuegbuzie & Seaman, 1995). Many researchers (Lazar, 1990; Lalonde & Gardner, 1993; Onwuegbuzie, 2000b) suggested that learning statistics is as difficult as learning a foreign language. On the other hand, statistics anxiety sometimes is not necessarily due to the lack of training or insufficient skills, but due to the misperception about statistics and negative experiences in a statistical class. For instance, students often think they do not have enough mathematics training so that they cannot do well in statistical classes. With fear of failing the course, they delay enrolling in statistics courses as long as possible, which often leads to failure to complete their degree programs (Onwuegbuzie, 1997). The lack of self-efficacy and higher anxiety in statistics keep many students away from engaging in research work or further to pursue an academic career. Therefore, statistics becomes one of the most anxiety-inducing courses in their programs of study (Blalock, 1987; Caine, Centa, Doroff, Horowitz, & Wisenbaker, 1978; Schacht & Stewart, 1990; Zeidner, 1991)."
Abstract The practice of statistics in a manufacturing facility is incredibly important for two key reasons: Statistics help to address economic concerns and the functionality of equipment. This paper examines these two specific areas in respect to how statistics are necessary to promote the best interests of the manufacturing facilities. This paper takes the form of an applied knowledge report, where the materials are examined and are then demonstrated in their practice.
Abstract This paper in business statistics examines the usage of statistical methods in corporate performance measurement. It concludes that statistics have a central place in measuring corporate performance.
Abstract This paper examines some of the ways to teach statistics that will best overcome some of the main problems that students encounter while learning statistics and offers solutions to these problems.
From the Paper "Students do not normally encounter statistics until they are in college--at least not on any kind of practicable level--unless they are in extremely advanced mathematics classes at their high school. Even so, not every high school offers statistics as a course, while almost every college does. Teaching and learning statistics is problematic for most college students and teachers because to learn and understand statistics, it is necessary to first have a grasp of some of the properties and features of higher mathematics. Many college students do not have these skills upon entering college, and many professors assume that they do have these skills when beginning to teach a statistics course."
Abstract This paper discusses the application of statistical concepts. Most importantly it focuses on the use of normal distribution and central limit theorem as it relates to statistics.
From the Paper "The normal distribution is the most important pattern of data that occurs in statistics. It is a common distribution modelling the heights of people, the weights of similar animals, the number of bushels of peas produced per acre per year etc. Rongrong Xie writes in The American Statistician that the reason the normal distribution is interesting is that it has an important use in the statistical theory of drawing conclusions from sample data about the populations from which the samples are drawn..."
Tags:statistics, normal distribution, central limit theorem, distribution, sample data
Abstract The area of statistical data gathering on which this paper focuses is that of patients from OB units, or mothers who have recently undergone care during labor, delivery and the postnatal period. Various statistical information that can be gathered from OB patients is discussed, suggestions are made for additional information that could be collected, some concerns are discussed regarding issues of privacy that come along with information collection, and the advantages of improving decision making by collecting information are looked at.
From the Paper "There are many reasons for health care providers to collect and interpret data taken from their outgoing patients. Some of these might include bettering the facility's ability to provide care and services, to better avoid infections or complications that may be common occurrences, and to give the patient/consumer a say in the quality and development of their care and the health care system, as a whole. The area of statistical data gathering on which this paper will focus is that of patients from OB units, or mothers who have recently undergone care during labor, delivery, and the postnatal period."
The following paper is a statistical analysis of the results of the 2000 presidential election, through regression analysis and hypothesis testing to call into question the validity of the results.
Abstract The following paper draws into question the results of the vote in Florida in the 2000 presidential election. The data set is drawn from the Florida Department of State. The purpose of this paper is not to address a value judgement, rather it is an attempt to investigate whether the differentials in the recount are statistically significant, indicating the presence of some sort of irregularity.
From the Paper "19th century elections were characterized by accusations of dirty politics and election fraud. Increasingly in the 20th century, counting procedures became more accurate, communication improved and, seemingly, election results should be reported expeditiously and without question of accuracy. However, several weeks after our nation's most critical election, a gamut of irregularities, particularly in Florida, whose electoral votes will determine the outcome of the election, has delayed the recognition of a winner. With George W. Bush's lead vacillating well under one thousand votes, an adjustment of a decidedly small proportion of the votes could change the outcome of the election. This paper discusses two of the irregularities that render Bush's seeming victory in the state uncertain."
Tags: election, statistics, bar, graph, county, net, differential, results, initial, count, first, recount, axis, represent
Abstract This paper is about global trade statistics. It looks at the role of the WTO and discusses direction and trends in trade, structure of world trade, Egypt in world trade, and major exporters and importers.
From the Paper "Sluggish import demand in Western Europe and a sharp contraction of Latin America's imports constituted a drag on global trade expansion. The World Trade Organization WTO suggests that developments in ..."
Tags: Global trade, balance of trade, export, import, statistics, egypt, trends, deficit, egypt
Abstract The paper discusses the two statistical analysis forecast methods. The paper explains how they can both be used to trend market areas, one on a broad basis, while the other can be extremely detailed and therefore, more accurate.
From the Paper "Although there are many approaches to determining accurate forecasting there is one approach, which can be used when little data is available on a local level. This approach is known as the "build up" method and when applied is used to gain basic market information (i.e. market population, product market share and product demand percentage). This data is used to determine market size potential within a given area and is based on the entire market, not segments (Barnett, 1988, p. 28). In addition to this the "build up" method does not take into consideration the initial goals of the company but takes into consideration market conditions only. An example of build up forecasting would show total consumer sales on automobiles across the nation."
Abstract This paper presents a number of statistical calculations related to death rates for cancer and heart disease from 1985 through 2006. The raw data is plotted and graphed. The resultant lines are then analyzed as functions and predictions are made for future rates according to the data. Several word questions are answered related to the data and graphs.
