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Practical Statistics, 2002.
A look at the development of statistics and how they are used.
1,328 words (approx. 5.3 pages), 9 sources, MLA, $ 44.95
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Abstract
This paper discusses the way the study of statistics has developed over time and how it is used in a practical manner today. It looks at the history of this topic and how scholars have helped it progress into an independent academic study. Examines some of the famous statistics that are used in everyday life - divorce rate, GDP, high school drop-out rate, poverty rate, literacy rate etc.
From the Paper
"Statistics is a branch of mathematics dealing with the collection, organization and analysis of numerical data the application of this information to make informed decisions in a variety of applications. Statistical results may be used to forecast business trends, define the extent of prevailing opinion throughout a given population, changes in availability of resources or assets, and provide quantifiable answers to questions in almost every type of business, social or political area. Professor Edwards of the Andover Theological Seminary defined statistics as ?the ascertaining and bringing together of those facts which are fitted to illustrate the conditions and prospects of society.? "
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Statistics in a Manufacturing Facility, 2002.
Looks at the importance of statistics to a manufacturing facility when addressing economic and performance concerns.
2,150 words (approx. 8.6 pages), 2 sources, $ 80.95
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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.
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Descriptive Statistics, 2006.
A discussion regarding the use of descriptive statistics and various common errors.
675 words (approx. 2.7 pages), 3 sources, $ 26.95
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Abstract
This document discusses a series of descriptive statistics 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 descriptive statistics. 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. "
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Statistics, 2005.
A definition of statistics and explanation of the statistical process.
4,594 words (approx. 18.4 pages), 5 sources, MLA, $ 119.95
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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)."
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Statistics, 2002.
Examines a variety of statistical procedures and shows how statistics analysis company, Polk Company, applies some of them for their analytical objectives.
6,284 words (approx. 25.1 pages), 4 sources, APA, $ 146.95
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Abstract
Statistics refers to the processes of collecting, organizing, analyzing and presenting data in forms usable for policy analysis, decision-making and other important tasks confronting people and organizations in contemporary society. It is within this framework that Polk Company, one of America's oldest and largest consumer marketing firms, operates.
This study considers the application at the Polk Company of 11 tasks associated with the processes of collecting, organizing, analyzing and presenting data. In each instance, the data management or statistical analysis function is defined, the learning process is explained within the context of the Kolb Model, and an illustration of the application of the data management or statistical analysis function is presented. The 11 data management or statistical analysis functions are (1) organizing data, (2) averages and variations, (3) elementary probability theory, (4) normal distribution, (5) binomial distribution, (6) sampling distribution, (7) estimation, (8) hypothesis testing, (9) regression and correlation, (10) chi square and analysis of variance (ANOVA) which is based on the F statistic and (11) non-parametric statistics.
From the Paper
"Type 1 learners, when working with hypotheses, tend to review available data without bias and study and consider the data from a variety of perspectives to develop workable hypotheses related to analytical objectives. Type 2 learners would approach the task by developing theoretical models upon which to base hypotheses, and then study and consider the data from a variety of perspectives in which model best supports the development of workable hypotheses. Type 3 learners would approach the task by developing theoretical models upon which to base hypotheses, and then experiment with alternative hypotheses to determine how best to achieve analytical objectives. Type 4 learners would review available data without bias, and then experiment with alternative hypotheses to determine how best to achieve analytical objectives."
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Statistics Anxiety, 2006.
A research paper on how statistics anxiety affects graduate students in the social sciences.
2,790 words (approx. 11.2 pages), 45 sources, APA, $ 83.95
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Abstract
Statistics anxiety has been defined simply as anxiety that occurs as a result of encountering statistics in any form and at any level. The paper shows that higher anxiety in statistics keep many students away from engaging in research work to pursue an academic career. Statistics becomes one of the most anxiety-inducing courses in their programs of study. The paper examines the problem and shows how it affects students.
Paper Outline:
Introduction
Empirical Research on Statistical Anxiety
Three Common Factors of Statistical Anxiety
Framework/Model to Reduce Statistical Anxiety in Counselor Education
Conclusion
Impact/Benefits for Students Seeking Ph.D.
From the Paper
"A variety of peer learning environment designs to support effective collaborative learning has been attempted or proposed. The backbone of collaborative learning is the willingness of the peers to participate in collaboration in a constructive sense. This has been studied by a number of educational psychology researchers [Madden & Slavin1983,Slavin1978] who confirm that the peers in collaborating classes felt that their peers wanted them to learn. Slavin [Slavin1990] reports studies that confirm the willingness of peers to make the collaborative learning efforts succeed and the improvement in social status of the peers who achieved better than other peers."
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Inferential Statistics, 2005.
This paper discusses the field of inferential statistics and its application.
2,435 words (approx. 9.7 pages), 15 sources, APA, $ 74.95
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Abstract
This paper explains that psychologists use statistics to make sense of the human behaviors; through observation measurement and statistical inference, researchers are able to take the abstract and make it more understandable. The author points out that, in inferential statistics, researchers use probability to make generalizations about the entire population based on the results from the research sample. The paper relates that statistics can be used to dictate public policy; thereby, it is especially important that mis-measurements do not occur particularly by drawing samples from non-normative or incomplete populations; while seemingly straightforward, statistics require judicious application of ethical behavior. 2 figures. 6 tables.
Table of Contents
History
Descriptive and Inferential Statistics
Samples and Populations
Probability
Data
Measures of Central Tendency
Central Limit Theorem
Hypothesis Testing
Related Samples
Correlation of Pre and Post Test
What Does Is All Mean?
From the Paper
"Some of the earliest work in statistics was done by Sir William Perry in 1532, when he began to record the number of deaths in London on a weekly basis. Later in the 1600, James Bernoilli, a Swiss mathematician, begin using probability to predict outcomes. In the 1700s, it was Thomas Bayer who gave birth to the concept of inferential statistics. The normal distribution was discovered in 1733 by a Huguenot refugee de Moivre as an approximation to the binomial distribution when the number of trials is too large. Today, not only do scientists but also many professions rely on statistics to understand behavior and ideally make predictions about what circumstances relate to or cause these behaviors."
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Statistics: An Essay on its Use in Everyday Life, 2001.
This paper defines statistics and shows the numerous ways statistics is applied to everyday life and why it is useful.
1,500 words (approx. 6.0 pages), 9 sources, $ 49.95
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From the Paper
"Statistics is a branch of mathematics dealing with the collection, organization and analysis of numerical data the application of this information to make informed decisions in a variety of applications. Statistical results may be used to forecast business trends, define the extent of prevailing opinion throughout a given population, changes in availability of resources or assets, and provide quantifiable answers to questions in almost every type of business, social or political area. (Encarta) Professor Edwards of the Andover Theological Seminary defined statistics as ?the ascertaining and bringing together of those facts which are fitted to illustrate the conditions and prospects of society."
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Statistics Anxiety, 2006.
An analysis of the imapct of statistics anxiety on graduate students.
1,200 words (approx. 4.8 pages), 43 sources, MLA, $ 41.95
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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)."
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Official Statistics, 2002.
A look at the use and misuse of "official statistics" in the public and private spheres.
1,400 words (approx. 5.6 pages), 5 sources, $ 53.95
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Abstract
This paper explores the use and availability of official statistics, particularly for business. The phrase "official statistics" is thoroughly defined, and the paper gives examples of industries and departments in which official statistics are commonly used.
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Business Statistics, 2006.
A discussion on the importance of statistics in business.
1,508 words (approx. 6.0 pages), 6 sources, MLA, $ 49.95
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Abstract
This paper begins with the reasons why statistics are crucial to running a successful business. It continues to review statistical terms through example and graphic representation. The paper also defines probability and distribution and examines how they can be used to the advantage of an organization.
Table of Contents:
Part 1 - Business Statistics
Part 2 - Mean, Median Mode & Standard Deviation Dayton OH Temperatures
Part 3 - Permutations and Combinations
Part 4 - Probability
Part 5 - Probability Distributions
Part 6 - Normal Distribution
References
From the Paper
"Probability can be used in business to help determine the likelihood that certain future events will occur (Arsham, 1994). It can also help executives base decisions on the most probable positive outcome given multiple scenarios to choose from. Probability analysis is a widely used business tool for evaluating scenarios in a business environment.
Probability is the act of determining the likelihood that given phenomena will occur without relying solely on random guessing. Probability thus helps managers and other business executives determine the best course of action given multiple alternatives (Arsham, 1994). Probability can also be used to determine the likelihood that adverse events will happen, such as the likelihood that certain threats to corporate assets will be realized within a designated time frame. "
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Why Are Statistics So Alluring?, 2002.
A description the different ways that statistics can be skewed to sway public opinion and also the ways that people misinterpret them.
1,576 words (approx. 6.3 pages), 6 sources, MLA, $ 51.95
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Abstract
This paper discusses how people, in general, like to get a visual picture of what they are hearing about and how, through the media and constant representation of statistical data as hard fact, numbers can control people's opinions on issues. It shows how one of the largest issues regarding statistics and their appealing nature is the fact that most of us are innumerate. It also shows how, in addition to innumeracy, the public?s opinion of ideas often leads to skewed views on issues; statistics can become so alluring to activists that they can say something that will change a large group of people's minds on an issue, and then they will get what they want.
From the Paper
"Although even though some statistics are wrong, people want to believe them so bad that they will ignore all logic just so that they will have a numerical view of the situation. Perhaps the biggest real life example of this is a social statistic that Joel Best-in his book Damned Lies and Statistics-describes as "The worst social statistic ever... Every year since 1950, the number American children gunned down has doubled" (Best 1). To anyone using this statistic to promote gun control, this statistic is gold, and it sounds believable too. But if you analyze it you'll find otherwise."
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Darrell Huff's "How to Lie with Statistics", 2005.
This paper is a book review of Darrell Huff's classic 1954 text "How to Lie with Statistics".
905 words (approx. 3.6 pages), 1 source, MLA, $ 32.95
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Abstract
This paper explains that Darrell Huff in his text "How to Lie with Statistics" relates that, because there is a fear of numbers in our culture and a great deal of misunderstanding or incomprehension about what number mean, combined with a paradoxical impulse to trust science as objective, people are apt to become confused by the use of numbers, regardless of what the numbers actually say. The author points out that the math is usually computed correctly but is rhetorically twisted and used to suggest an erroneous conclusion, hence Huff's rightful characterization of such misleading evidence as a lie. The paper stresses that perhaps the most relevant information in the book for today's reader pertains to interpreting potentially divisive statistics such as crime rates in cities.
From the Paper
"Such an example is not unlike the spurious study cited by Huff that smokers have significantly lower grades in college than nonsmokers. Ergo, said the researcher, smokers wishing to improve their grades should quit smoking! Of course, a statistical study showing that there's a "significant" relation between smoking and low grades doesn't show that smoking is the cause of lower grades -- perhaps educational failure draws people to smoke, suggests Huff, or more seriously, demographic factors such as poorer individual's tendency to smoke as a culturally accepted coping mechanism or to have come from less well-funded and rigorous school districts might also come into play."
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Business Statistics, 2005.
Examines the use of statistics in the business world.
1,327 words (approx. 5.3 pages), 7 sources, MLA, $ 44.95
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Abstract
Business statistics can be considered a branch of science that enables one to make the right decisions. This paper shows that business statistics have uses in many areas, including financial analysis, econometrics, auditing, production, and operations, such as the improvement of services and marketing research.
From the Paper
"Acquiring skills in Business Statistics enables one to make analysis of data and take decisions using a gamut of statistical analysis packages or programming environments. Business Statistics wields a high level of influence in high-level, strategic analysis of real-world areas of difficulty across the boundaries of disciplines. We see a lot of collective actifity in fields such as risk in financial markets, the modelling of the choice of consumers and behaviour of corporates, and in the creation of indices to measure political risk. Such activities have only enhanced the importance of Business Stattistics. (Welcome to the Discipline of Econometrics and Business Statistics)"
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