Statistics and Their Importance to Research Investigation. Although all research activities do not require the use of statistical data analysis when an investigator wants to report upon the differences, effects and/or relationships between and amongst groups or phenomena (i.e. variables) there must a concerted effort to measure the phenomenon with as much precision and accuracy as possible (Mendenhall & Ramey, 1973). This is, of course, accomplished through the use of statistics. Situations wherein statistical processes are not required are generally reserved for qualitative types of research such as historical, philosophical, and/or cultural trend studies.

One of man's greatest fears is that of the power of numbers. For most people numbers are nothing more than a hodgepodge of digits that are bewildering and often meaningless. As a result individuals often prefer to judge events, occurrences, phenomena, and situations from a traditionalist point-of-view wherein reason, conclusion, and inference are made on the basis…...

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Before one enters the world of statistics one must put away all their fears and illusions about statistics. The stimuli that incite mathematical panic are largely illusory. Many of the formulas used by scientists in their statistical computations present an awesome, if not terrifying, appearance, but beneath the strange symbols lurks nothing more foreboding than the simple arithmetic we all mastered in school. The uses one will make of best practice statistics require no differential equations, no calculus, and no analytic geometry. The sometimes-horrifying mathematical manipulations that fill one with ghastly anxiety as they approach a lesson in statistics ultimately reveal themselves as addition, subtraction, multiplication, and division. By becoming familiar with the statistical techniques one might possibly develop a benevolent tolerance for the tedium and possibly even a reverent respect for the almost magical things statistics allows one to do with mere numbers.

Correct Statistical Processes. Statistics is a branch of scientific mathematical methodology. It deals with the collection, classification, description, and interpretation of measurement data obtained through the testing process and observation. In consumer product research the essential purpose is to describe and draw inferences about the numerical properties of product populations as well as to compare testing procedures (Senter, 1969). In everyday language the term population is used to refer to groups or aggregates of consumer product. The consumer product researcher's concern is with properties which are descriptive of a group or aggregation itself rather than with properties of particular single product member. As consumer product researchers are primarily concerned with group issues, rather than single product unit matters, it is paramount that a complete familiarization and understanding be had as to the proper use of statistical processes. The investigator must discern when to use a particular statistical process for comparing a single unit to a group opposed to comparing two (2) or more groups to each other, or comparing a group to a wider population. Should the wrong statistical process be employed there will result contaminated statistical values and wrongful conclusions will be drawn. As a consequence of the use of improper statistical processes unsafe consumer product may be accepted; client liability will increase; and corporate profit will diminish.

The primary purpose of statistical processes is to make order out of chaos. By properly applying selected statistical processes to measurement data the consumer product engineer can determine whether or not a manufactured product is safe for distribution. However, product safety is simply a stratagem if the wrong statistical procedure is applied to measurement data. Once the researcher has collected the necessary measurement data it is then time to apply an appropriate statistical tool that will confirm or deny

Statistics and Juries
In the video "How Statistics Fool Juries," Oxford mathematician Peter Donnelly attempts to demonstrate through a number of examples how statistics, when viewed in a common manner, can be misunderstood and how this can have legal repercussions. Through a number of thought experiments, Donnelly provides the audience with examples of how seemingly simple statistics can be misinterpreted and how many more variables must be taken into account when calculating chance. Primarily he exposes the audience to the concept of relative difference, or the difference in likelihood between two possibilities in the same scenario. He then goes on to explain that without an understanding of this concept, many juries misunderstand statistics used in trials and very often convict people based on this faulty understanding.

Donnelly begins his presentation with a thought experiment involving the tossing of a coin and predicts the possibility of a certain series of results. When predicting…...

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References

Donnelly, Peter. (12 Jan. 2007). Peter Donnelly: How Stats Fool Juries. Retrieved from  https://www.youtube.com/watch?v=kLmzxmRcUTo

One of the most common fallacies is to confuse correlation with causation, but the two are actually distinct. My demonstrating that construction of snowmen and outbreak of acne occur simultaneously does not mean that snowmen produce acne. It may imply an underlying matter, such as the snow itself may contain some component that may instigate the outbreak, or the children who build the snowmen may be particularly vulnerable to acne, and during that period of the year, and so forth. Two factors happening concurrently, does not mean that one influences the other.
Readers may also take the percentage face blank unaware of the notion of margin of error. Margin of error implies that the data shows only an approximate result of the sampled population (usually 95%). There is a certain percentage of error either way, and so the end results can only be approximate, never absolutely certain.

Using statistics in writing…...

As explained earlier, statisticians in the academe and in specialist industries apply principles and techniques of statistics in different ways. Statisticians in the academe apply their knowledge of statistics in more scientific approaches: multivariate analyses, for example, are reported in a scientific manner, usually communicated in a scholarly approach through journal articles and published or unpublished research reports. Industry specialists, meanwhile, implement statistical principles and techniques more creatively, for their clients/end-users to understand the statistical techniques used and findings culled out from the analyses. Multivariate analyses that may have been reported scientifically by academicians would be converted and simplified as "maps" (e.g., perceptual maps, quadrant maps) to 'laymanize' statistical findings and make it easier for clients to relate the findings to their business needs and issues.

In effect, statisticians market their expertise in different ways, depending on the end-users of their statistical projects. For academicians, statistics is marketed as a rigorous…...

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References

Malhotra, N. (1996). Marketing Research: An applied orientation. NJ: Prentice Hall.

Weiers, R. (1984). Marketing Research. NJ: Prentice Hall.

Statistics are the tools to describe the systematic body of information that assist policy makers or managers to make decision about important issues. Statistics provide the accurate methodology to draw the accurate inference from the sample of data to the full population. Despite the benefits derived from applied statistics, there are challenges that policy makers face in measuring social issues.
Answer to Question A

In public sector, statistical approach is used to carry out the measurement. Measurement is the process of assigning number to the issue that policy makers are interested in studying or analyzing. There are various methods to go about measuring social problem. First, the attitude of the total population to a social problem could be measured by sampling the opinion of the population towards the issue. Meier et al. (2011) reveal the method in measuring complex issue such as measuring the religion preference of a particular racial group, or…...

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References

Meier, K.J. Brudney, J.L. & Bohte, J.(2011).Applied Statistics for Public and Nonprofit Administration. Cengage Learning.USA.

U.S. Census Bureau (2000). U.S. Summary: 2000 Census 2000 Profile. Department of Commerce.

In a follow-up experimentalinvestigation among female college students, Onwuegbuzie (1995) reported asignificant interaction between statistics test anxiety and type of examination (i.e.
Specifically, three types of factors are identified: (a) situational factors, such as math experience (Betz, 1978; Roberts & Bilderback, 1980; Tomazic & Katz, 1988; Zeidner, 1991; Wilson, 1997; Balo_lu, 2001; Hong & Karstensson, 2002; Balo_lu, 2003), statistics experience (Sutarso, 1992), computer experience (Zimmer & Fuller, 1996), and research experience (Trimarco, 1997); (b) dispositional factors, such as math self-concept or self-esteem (Zeidner, 1991), scholastic competence or multiple intelligences (Birenbaum & Eylath, 1994; Daley & Onwuegbuzie, 1997; Onwuegbuzie, 2000c), perfectionism (Onwuegbuzie & Daley, 1999; Walsh & gumba-Agwunobi, 2002), hope (Onwuegbuzie. 1998b), and procrastination (Onwuegbuzie, 2000a; Walsh & gumba-Agwunobi, 2002); and - personal factors, such as learning style (Onwuegbuzie, 1998a; Wilson & Onwuegbuzie, 2001), age (Baloglu, 2003), gender (Betz, 1978; Roberts & Bilderback, 1980; Demaria-Mitton, 1987; Benson, 1989; Benson & Bandalos,…...

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Unfortunately, sparse studies have been found on how to reduce the anxiety in learning statistics for graduate students in the social sciences (Onwuegbuzie & Wilson, 2000). Schacht and Stewart (1990) reported incorporating humorous cartoon examples in statistics classes were perceived by the students to helpful in statistics anxiety reduction. Journal writing was suggested to be another effective tool in reducing levels of anxiety (Smith, Miller, & Robertson, 1992; Sgoutas-Emch & Johnson, 1998). However, theses studies did not find a statistically significant decrease in anxiety levels. Forte (1995) argued for an effective teaching approach that incorporates computer usage, real-world applications, humor, statistical language practice, and group-learning principles. Additionally, Dolinsky (2001) suggested creating a collaborative environment in which using active learning strategies as the primary method to teach statistics. These teaching methods reveal promise to reduce students' statistics anxiety, yet more innovations of teaching statistics are needed (Huntley, Schneider, & Aronson, 2000). More importantly, empirical studies are needed to examine the effectiveness of these methods in reducing statistics anxiety.

Innovative teaching methods can make the difference between who is able to master statistics to go on to the PhD level. For instance, such measuress, such as optional grading system, more flexible office hours, orientation letter, and the cheat sheet, are all measures that make it easier for students to pass the course. For most students with statistics anxiety, thought of failing the course is a huge stressor; therefore, even if they have the capability to learn statistics, the fear of failure overrides their ability. The application-oriented teaching methods, on the other hand, dispel the misconception about statistics that it is useless and that it is only for people with good math skills. Applying the class contents to daily life and actual research articles makes more meaning for students, and also have them feel more comfortable and close to learning statistics.

As documented above, recently, there has been an increase in the number of researchers investigating the construct of statistics anxiety. However, there is stil lmuch that we do not know about this phenomenon. Moreover, much of the research in this area has been undertaken among undergraduate students. Yet, as noted byOnwuegbuzie (1998a), statistics anxiety is extremely prevalent among graduate students, especially among women and minorities. Furthermore, because theses and dissertations typically necessitate the use of statistics, and because a significant proportion of students do not complete their theses and dissertations, and hence their graduate degree programs (Bowen & Rudenstine, 1992; Cesari, 1990), it is possible

Statistics in News eports
According to a recent article published on The Chart, CNN.com's comprehensive medical blog authored by Dr. Sanjay Gupta and Elizabeth Cohen, the number of American children who fall victim to accidental death each year has plummeted during the last decade. The article, entitled Accidental Death ate for Children Falls, details the dramatic decrease in the "death rate from unintentional injuries among children and adolescents from birth to age 19" (Gupta M.D. & Cohen, 2012), and provides a litany of statistical evidence to support this claim. As is always the case with the media's deployment of statistics, scientific records and other numerical support, a careful reader should avoid taking supposed facts and figures at face value without first subjecting the data to careful scrutiny. Until any statistical presentation can withstand the reader's rigorous examination, any conclusions drawn from the data in question must be considered to be suspect,…...

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References

Gupta M.D., S., & Cohen, E. (2012, April 16). [Web log message]. Retrieved from   fall/?hpt=hp_t3http://thechart.blogs.cnn.com/2012/04/16/accidental-deaths-among-children -

U.S. Department for Health and Human Services, Centers for Disease Control and Prevention (2012). Vital signs: Unintentional injury deaths among persons aged 0 -- 19 years -- United States, 2000 -- 2009. Retrieved from U.S. Government Printing Office website:   1_whttp://www.cdc.gov/mmwr/preview/mmwrhtml/mm61e0416a1.htm?s_cid=mm61e0416a 

Statistics and Econometrics
ID- 4119L

2011/12 LEVEL

STATISTICS AND ECONOMETICS

Present your data in a table showing the names of the variables. Make sure the full definitions and sources of each variable are given.

Birth ates: (thousands)

Quarter1 (Q1)

Quarter2 (Q2)

Quarter3 (Q3)

Quarter4 (Q4)

GDP per capita (GDP)

The GDP data used was from http://earthtrends.wri.org/text/economics-business/variable-638.html in the table Economics, Business, and the Environment -- GDP: GDP per capita, current U.S. dollars

Current U.S.$ per person

GDP

The equation to be estimated is:

Bi = b0 + b1 GDPi+ ui (i)

(i) In terms of the literature on demand for children, what would you expect to find for the coefficient on b1 ?

is expected to have a negative value. There is an indirect negative relationship between the birth rate and GDP per capita of a country. Generally, as the GDP per capita increases, the birth rate decreases [James M. 2009].

Explain how you would modify the model, implied by this equation, if there is an 'Engel curve'…...

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REFERENCE LIST

Birth rates in the U.S., accessed 19 Apr 2012

Engel's law, accessed 19 Apr 2012

Statistics of Oil Peak
In the present times, the depletion of oil all over the world has become a major topic of concern all over, and this subject is indeed an extremely important one because of the fact that a world without oil is a frightening prospect and will hurt mankind and the very lifestyle of human beings everywhere. Since it is well-known that everywhere it is conventional oil that is being produced in large quantities today, it must be understood that the production of this oil has been dominating the oil production all over the world, in fact, about 95% of oil that has been produced so far is the conventional oil, and there is no doubt that it will continue to dominate oil supply all over the world for a great many years in the future. It was in the 1960's that the discovery of conventional oil actually peaked,…...

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References

Campbell, C.J. (December, 2000) "Peak Oil" Presentation at the Technical University of Clausthal. Retrieved From Accessed on 8 February, 2005http://www.geologie.tu-clausthal.de/Campbell/lecture.html

"Interesting facts about Oil Gas and Ocean Environment" Retrieved From

Accessed on 8 February, 2005http://www.offshore-environment.com/facts.html

"Peak Oil: Life after the Oil Crash" Retrieved From

Again, the presidential campaign acted as a catalyst for technology adoption, and led to first-time social networking users getting online. It also led to existing users creating additional profiles as well.
On the third most significant variable in determining the effects of social networks on which candidate would eventually win Q39. Do you have a single profile on each site, or do you have multiple profiles on one web site? Provides the most fascinating data from the three variables included in the analysis. Notice that the distribution of results is bifurcated from one spectrum to the other. This signals that through the use of the participative aspects of social networks, candidates were able to get the support of the top 5% of social networkers, as evidenced by having more than one profile on a given network. The mean value of this variable is 1.17 and it has a mode of…...

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References

Tim O'Reilly. (2006, July). Web 2.0: Stuck on a Name or Hooked on Value? Dr. Dobb's Journal, 31(7), 10.

Williams, C., & Gulati, G.. (1 August). Social Networks in Political Campaigns: Facebook and Congressional Elections 2006, 2008. SSRN Working Paper Series

Source of dataset for analysis:

  -- Cloud-computing-politics-and-adult-social-networking.aspxhttp://pewinternet.org/Shared-Content/Data-Sets/2008/May-2008 

DAY, YR.SMOKE, and CO.LEVEL).
f. Draw a scatterplot to illustrate the relationship between CIG.DAY and CO.LEVEL. Describe the slope of the scatterplot.

g. Is it correct to say that higher intake of cigarettes (CIG.DAY) causes higher levels of carbon monoxide (CO.LEVEL)? Based solely on your correlation coefficient, explain why or why not.

2. Use the same data and compute the following using SPSS. Be sure to enter the data accurately into the program and to print off copies of your data and output files.

a. Determine the two Pearson correlation coefficients for the data provided below.

b. If you haven't already, analyze (using correlation ( bivariate) all three variables at once so that you see a correlation matrix in your printout.

c. Have SPSS generate three scatterplots: CIG.DAY and YR.SMOKE, CIG.DAY and CO.LEVEL, and YR.SMOKE and CO.LEVEL.

SEX

YR.SMOKE

CIG.DAY

CO.LEVEL

Female

20

15

17

Male

27

40

28

Female

14

28

40

Female

20

12

15

Female

10

40

33…...

Managing to a significant reduction in variably is a key aspect of Six Sigma, which explains why statistics are used extensively throughout the quality management strategies of services companies and manufacturers alike (Bergquist, Albing, 2006).
Many organizations are creating enterprise-wide quality management systems that encompass product and service process audits, Six Sigma strategies for gaining greater performance from trimming wasted time and materials for processes, and the development of quality management levels (Elshennawy, 2004). In conjunction with all of these aspects of an enterprise quality management strategy, manufacturers are using Corrective Action/Preventative Action (CAPA) process workflows to evaluate how statistically evaluating product quality will affect preventative action taken to permanently remove variation from the sourcing, supply chain, production or services processes. Statistics are used to further analyze why a specific product or service process is out of its boundaries of performance over time. Further, statistics are also being used to…...

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References

Bjarne Bergquist, & Maim Albing. (2006). Statistical Methods - Does Anyone Really Use Them? Total Quality Management & Business Excellence, 17(8), 961.

Ahmad K. Elshennawy. (2004). Quality in the New Age and the Body of Knowledge for Quality Engineers. Total Quality Management & Business Excellence, 15(5,6), 603-614.

Camille James. (2005). Manufacturing's Prescription for Improving Healthcare Quality. Hospital Topics, 83(1), 2-8.

Spatz, Chris (2008). Basic Statistics: Tales of Distributions by Chris Spatz. Cengage Learning 9th ed. ISBN-13: 9780495502180

tatistics and Airplane Part Maintenance
When one works within the aircraft repair industry it is essential to both demonstrate the utmost technical know-how, as well as possess an uncanny ability to somehow predict any potential problems that might arise with a particular aircraft or part. Of course, the reason this is so important is because of the nature of flight, itself. After all, it is hardly wise to wait until a critical part or system related problem arises to deal with it. In mid-air, one simply does not have the luxury of pulling over to the side of the road to fix the issue.

Within my work setting as an aircraft parts repair specialist, it is my job to prepare or repair parts for the airplanes on my military base. Although I do not install the parts, it is not only up to me to fix the parts that are not up…...

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Sources:

Canaday, Henry. (2004). "Hunting for Prodcutivity Gains." Overhaul & Maintenance. September. Retrived on September 29, 2004, from, http://www.aviationnow.com/avnow/news/channel_om_story.jsp?id=news/om904cvr.xml

DSCR. Defense Supply Center, Richmond. (2004). "Critical Aircraft Parts." Retrived on September 29, 2004, from, http://www.dscr.dla.mil/vg/Flight%20SafetyCriticalAircraftParts.htm

Personality: Personality is a subtle and difficult to define aggregate of traits and qualities that define an individual. To talk about personality is to refer to the way someone communicates, thinks, and acts in the world. Differences in psychology are often due to differences in personality. When things like family background and neurology are ruled out, personality can account for why one friend is shy and another one is gregarious. Some people's personality changes, whereas others' personality remains relatively stable throughout their life.

Psychological Assessment: A psychological assessment can be based on clinical observations, interview data, or formal tests. Assessments are crucial to determine a client's needs, course of treatment, and to measure treatment outcomes. If a person experiences symptoms like extreme fatigue, that person would get assessed and the clinician may offer a diagnosis such as depression.

Social psychology: Social psychology refers to the impact of psychological factors on social interactions.…...

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Reference

Gerrig, R.J., Zimbardo, P.G., Desmarais, S., & Ivanco, T., (2009). Psychology and life. Pearson Education Canada: Toronto, Ontario.

The morphological properties of the virion are non-enveloped, with isometric Necleocapsids 27 nm in diameter. The symmetry is icosahedral, with the Nucleocapsids round in shape. Further, there are 12 capsomers per neucleocapsid (ICTV). Additionally, the virions each hold one molecule of linear positive-sense single stranded RNA, with a total genome length of 7500 nt, and a hairpin structure (ICTV).
Treatment and Prevention:

The impact of the Hepatitis a can vary from mild to serious illness. It is normally transmitted by the ingestion of contaminated food or water which has come in contact with the feces of a carrying person (again, usually through bad hand washing, or poor sewage systems). The symptoms vary, but usually result in liver involvement causing weakness, loss of appetite, nausea, fever and jaundice. Severe reactions can lead to liver damage, failure, and even death. Unfortunately, there is no specific (or effective) treatment for Hepatitis a Instead, physicians…...

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Works Cited

Carmel. Mount Carmel Medical Center. (2004). "Prevention Protocols When Traveling." Retrieved on September 29, 2004, from,  http://www.mountcarmelhealth.com/healthinfo/Adult/digest/hepa.shtml 

CBW. (2004). "Biological Toxins." Retrieved on September 29, 2004, from, http://www.cbwinfo.com/Biological/Toxins/Verotox.html

Deodhare, S.G. (2000). "Viral Hepatitis: Recent Progress." Retrieved on September 29, 2004, from, http://www.pathoindia.com/update2.html

DOH. Washington State Department of Health. (2002). "E. Coli Reporting." Retrieved on September 29, 2004, from,  http://www.doh.wa.gov/Notify/guidelines/pdf/ecoli.pdf5

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Your thesis statement should be bold, but also something you can back up with facts throughout the paper. If you say, for example, that airline travel is becoming more dangerous, you will need statistics to prove that. You might want to focus your thesis on the risks vs. benefits of air travel, instead. You could use a thesis statement like \"despite the recent disasters occurring in the field of air travel, it remains the safest way for people to get from one place to another.\" As for structure, you could have an intro, information about the most recent disasters, what....