Misleading Statistics (Tuesday-Thursday Class)

            Statistics are important tools to provide information for people. Furthermore, they are evidence that can effectively strengthen any argument and persuade the audience to change their opinions. However, statistics can be twisted into negative ways. Statistics are often used in wrong ways. Therefore, statistics should be interpreted with caution as they can be misleading; they can both lie and tell the truth. This essay will illustrate the following six main important points that lead to misleading statistics: unreliable sources, Internet surveys, misleading graphs, incomparable samples, biased questions and manipulated statistics.

EAP 5: 5:30- 8:00 (Tue-Thu)

Unreliable Sources

Statistics are crucial in many ways. However, misusing and misunderstanding statisticshave the potential to influence decision-making and the accuracy of prediction or judgment of users. Therefore, before deciding whether the statistics are reliableor not, a critical analysis is always necessary. Although the Internetis widely known to be capable of offering a great wealth of information that could be beneficial for research and assignments, users should always notethat not every site offers accurate information. Some sources are reliable and some are not.

Therefore, before going further to talk about the form of unreliable sources, the definition should be provided. Unreliable sources aredocumentsthat are written by unknown authors who have no proper status, improper background, and unknown qualifications (Austin Peay State University Academic support center writing lab, unknown year).Moreover, anyone either an expert or an amateur can post anything on the Internet. Writers just writebased on their perspectives on some particular issues such as the environmental issues, political or other issues without any precise citation. Wikipedia, blogs, Tweeter, forums, personal websites, andquestionable sites are some of the examples of unreliable sources.Furthermore, some sites like Wikipedia allow users to post or edit articles freely. Therefore, those sources are not reliable and appropriate to use for research purposes. In prior to uploading a document on the Internet does not require editors, fact checkers or reviewers to ensure the accuracy and evaluate the work (Kranendonk, 2013). Additionally, a date that can be seen on a website could be the date posted, date edited, or there might not be a date included. Hence, appropriate steps should be carefully analyzed before determining the reliability of a source.

Factually, sometimes writers just write based on their own assumption or the general assumption that could be too general or unspecific to predict the other new case study. For example, the number of cigarettes that have been sold on the market can estimate by counting the number of people smoke the cigarettes. However, sometimes the number of cigarettes has been smuggled by the illegal importer to sell in the country without paying the tax, so the government cannot control on this point. Furthermore, in some cultures, the women smoke even more than the men do, but the data tends to provide or state that the men smoke more than the women based on the general assumption.  Hence, the general information that is always right and reliable does not guarantee it is one hundred percent accurate in every case. (Pijahn, 1996)

In addition to this, some sources offer misleading information as a form of persuasive or deceptive strategy. According to Derbyshire,misleading advertisements attract people, especially housewives,to buy various kinds of products or services. For instance, Colgate claims in its advertisement that its toothpaste is highly recommended by 80 percent of dentists, and it appears to people that the toothpaste is suggested to use by 80 percent of dentists globally. While in fact, it is shown to be a false slogan, since the surveys of dentists and hygienists were based on telephones, and carried out by the manufacturers (Derbyshire, 2007). Therefore, not every advertisement and statistics shown on television, poster, or advertisement is reliable.

Onthe other hand, a reliable source that has information which is expired or not updated can also be misleading. Every source needs to be updated recently in order to keep up to precise and latest true stories. As time goes by, everything–environment, population, culture, belief, technology, society, governments and more–changes, eitherbetter or worse. If a source provides the information that was surveyed in 1999—the information would only focus on the 1999’s situation, not in the next year or next period of time. For instance, according to the United Nation website, the world population of developed regions in 1999 was 5,978,401 thousand people. However, in the next year (2000), it rose dramatically up to 6,055,049 thousand people (United Nations, unknown years). This example illustrates precisely of how big the difference between the old source and up-to-date source is.

However, some reliable sources can be misleading as well. The information that is offered could be either too exaggerated, or have half of the overalldetails omitted to achieve a certain purpose. For example, making people feel good about a particular area or deceivingpeople into doing something. Another example, the government website which reports the development of the country in a certain area would want people from all over the world to know that it is developing to attract more investors and tourists. Whereas, in the occasionswhere there is a war or disaster, authorities could also omit information to calm people down. Therefore, reliable sources can sometimesoffer inaccurate information to benefit themselves.

To sum up, statistics can be very beneficial for assignments and research. However, not all of the sources are reliable. Numbers are powerful and so are statistics. Statistics can be persuasive pieces of evidence that is used to effectively prove arguments. Therefore, if not used carefully, it can fail to make arguments on something transparent and reliable, yet ambiguous (Statistics, nd.).Hence, information users should be aware of the misleading information to avoid making wrong decision, unfair judgments and predictions.

Bibliography:

Austin Peay State University Academic support center writing lab, Reliable and Unreliable Sources. (Unknown Year) . Retrieved from http://www.apsu.edu/sites/apsu.edu/files/academic-support-center/Reliable_and_Unreliable_Sources.pdf

Author unknown, (nd.) Statistics[online].University of North Carolina. Retrieved from: http://writingcenter.unc.edu/handouts/statistics/

Derbyshire, D., (2007) ‘Colgate gets the brush off for 'misleading' ads.’ The telegraph,17 January.

Kranendonk, Kees. (2013). Unreliable Sources. Academic English.

Pijahn, Y. (1996). No smoke without some unreliable statistics. Retrieved from http://www.independent.co.uk/news/no-smoke-without-some-unreliable-statistics-1309461.html

Statistics Should Be Interpreted With Caution As They Can Be Misleading

Survey is a statistical study of a sample population by making enquiries about opinions, perspectives, preferences and the other aspects of the individuals. Conducting web survey is certainly common in everyday life, because many organizations and companies believe that they will get many responses from the global community.

Population is a major factor for inaccurate data in the Internet surveys. Errors can occur by using different sample sizes when the target population is surveyed.  The main reason for sample sizes turns out to be different is that there must be some parts of the population that were not included in the sample. For example, the Internet users’ survey that is related to personal computer usage is unlikely to be accurate while the total population is a mixture between those who own and those who do not own personal computers. In this case, it results in different sample sizes. (Ronald D.Fricker, 2008)

Additionally, another form of misleading Internet surveys is measurement errors. Surveyors must not expect honest answers from the respondents. Answering sensitive questions is a hard task for respondents. For instance, in Canada, questions related to personal background such as salary, are just too sensitive that the respondents may give dishonest answers. Misleading statistics on the Internet could happen due to the lack of work and effort of those surveyors that do not use the special programs to increase the accuracy of the survey. It means that the surveyors can get many opinions from the respondents but the answers are just multi-responses of one respondent (Ronald D.Fricker, 2008). In this situation, people who are enthusiastically interested in the results of the surveys are willingly to do the survey more than once in order to influence the results as well as the statistics. For example, some people would create multiple email accounts and do the survey several times when the website requires individuals to sign up and participate. And, if one computer cannot access to the survey more than once, they might probably use another computer to access and complete the survey as much as they want. (Duda, 2010).

Moreover, non-responses bias is introduced as another main cause of misleading statistics. Non-responses bias influenced the survey results when a large amount of people in the sample population reject or fail to respond and have relevant characteristics that are different from those who respond. According to Field Epidemiology Manual,  some people do not respond because they refuse or probably they cannot be contacted (Field Epidemiology Manual, Non-response Bias).

Furthermore, financial benefits are also regarded as one of the major factors for misleading statistics. In facts, there is no quality control in web surveys. As Responsive Management team stated, profits are offered if people volunteer to participate in the survey for an organization or a company (Duda, 2010).  Those profits include monetary, special rewards or incentives, discount on purchases and gift certificates. By using this procedure to encourage people to participate, the data information from web survey results are completely misleading.

Typically, after the surveys are conducted, the results are calculated and presented to the public by using diagrams like tables, graphs and also charts. In this case, misleading graphs can also be another huge impact on misleading statistics. Many companies often use graphs to indicate or impress the customers with their productivity and stock prices. Therefore, they need to make their graphs look more interesting and attractive.

According to Dr. Haney from Calvin College, approximately 73 years ago, some businessmen created a type of graph called Gee-Wiz graph which is also known as a misleading graph. A misleading graph is defined as a type of graph which is converted from a normal graph to a more attractive one. In business, people normally try to create various tricks or methods in order to attract customer attentions (Haney).

There are many different ways to create a misleading graph such as scaling and axis manipulation, three dimensional effects (3D graphs) and deceptive pictographs (Misleading Graphs and Statistics, Chapter 31). Firstly, in order to mislead a graph using scaling and axis manipulation procedure, it is necessary to adjust the scale of the Y axis to be longer than the scale of the X axis. It can change the graph from a slight increase to a significant increase. Secondly, 3D graphs can impress readers at first sight. This type of graph looks more appealing, compares to a normal graph (2D graphs). Finally, deceptive pictograph is also a common type of misinforming diagrams which businessmen often use to deceive people ’eyes. Deceptive pictographs indicate a different category with various sizes depends on their actual sizes. For example, a pictogram indicates 4 kinds of domestic pets owned by people. Each symbol illustrates a type of pet which is owned by 50 people. On the left pictogram (Misleading graph), the actual size of the horse symbol is bigger than the others. Whereas, on the right pictogram (Normal graph), the horse symbol is represented in the same size as others (Misleading Graphs and Statistics, Chapter 31).

These three types of misleading graph are quite common in the internet. Especially, scaling and axis manipulation since it can easily trick the viewers and the viewers rarely focus on the scale of the graph. But, they only focus on the trend of the graph such as the declining and expanding.  Therefore, misleading graphs is regarded as one of the major causes of fallacious statistics.

(900 words)

Bibliography

Duda, M. &. (2010). Responsive Management, The Fallacy of Online Survey. Retrieved 2013

Available from  http://www.responsivemanagement.com/news_from/2010-05-04.htm

Field Epidemiology Manual, Non-response Bias. (n.d.). Retrieved 2013

Available from https://wiki.ecdc.europa.eu/fem/w/wiki/non-response-bias.aspx

Haney, D. (n.d.). How To Lie With statistics, Chapter 5, Increasing The Wow Factor. Retrieved November 2013

Available from http://faculty.nps.edu/rdfricke/docs/5123-Fielding-Ch11.pdf

Misleading Graphs and Statistics, Chapter 31. (n.d.). Retrieved November 2013

Available from  http://faculty.atu.edu/mfinan/2043/section31.pdf

Ronald D.Fricker, J. (2008). Sampling Methods for Web and E-mail Surveys. Retrieved 2013

Available from http://www.calvin.edu/academic/economics/faculty/bios/HaneyDocs/

 

Incomparable Samples

         Statistics are ways that people use numerical evidence to prove their studies. However, statistics can be misleading if data is gathered wrongly. The major aspect that leads people to misinterpret the statistics is incomparable samples. An incomparable sample refers to a comparison between different sample sizes, genders, ages, locations, living status and level of education.

       First of all, sample size is considered as one among other problems that mislead people with the statistics. The size of sample could affect the margin of error on the result. For example, a telephone survey with a sample of 100 participants produces less than 10 percent error, a sample of 500 participants reduces the error margin to less than 4.5 percent, and a sample of more than 4000 participants almost reduce the error margin to just 1.5 percent (Scheuren, 2004). Therefore, the smaller the sample is the more error we will get. So in order to obtain credible statistics, a larger sample is recommended.

In addition, a comparison between unequal sample sizes can mislead people as well. The size of the sample must be gathering equally when comparing the statistics. Because when one sample has a smaller or a larger size compared to the others, it result in misunderstanding for the readers. For instance, a survey about the airline’s complaints that published by the US News and World Report reported that US airline has more complaints than the Alaska airline. However, due to the difference in number of passengers, it makes the statistic unbalanced since the survey was conducted with 252 passengers from the US airline while it was carried out with only 13 passengers from Alaska airline (Alden,2005).

Secondly, genders and ages also cause people to misinterpret the statistics. The gender plays a very important role in misleading statistics. Since men and women that live in different areas have different point of views, surveyors should distinguish between male and female groups before doing surveys. Because some survey are only suitable for certain group of people to participate. As a hypothetical example, imagine that if marketers wanted to conduct surveys related with cosmetic products, it would not logical to conduct it on men since they have no interest in cosmetic products compares to women. In order to acquire a survey that reflect the general opinion of people, surveyors have to make sure that the percentage of male and female that participate in the survey represents the percentage of the whole population (Survey Design, 2005, Internet). If the statistic is obtained wrongly; meaning that the survey is conducted by unrelated group of people, the figures can result in misleading. Moreover, age is also one of the most essential factors in obtaining precise data. Both men and women in different age groups tend to have dissimilar interests, behaviors and perspectives. For that reason, every survey should not be done voluntarily, but should be done by various groups of people to achieve precise data.

Thirdly, social status and level of education are very crucial for gathering accurate information from the survey. Normally, rich people can afford a higher education, and live in a luxurious lifestyle while poor people have a limited education, rely on farming and lead a very simple life. So, between the two of them, one can say that rich and poor people are completely living in a different world and they tend to have different perspective. Consequently, when obtaining the statistical evidence from the survey, it is really important to select the right group of people because the result might turn out completely different if the sample is chosen recklessly.

Furthermore, balancing the right sample of society status is really essential in providing people the true and the right understanding of the statistics. For example, one statistical result showed that fluoride consumption by human beings can increases the cancer rate. So comparing to people who did not take in fluoride, the people with the consumption of fluoride have a higher chance of increasing the cancer rate (Alden, 2005). This statistic is totally misleading because it did not provide any clear information. Likewise, only wealthy people can afford to consume fluoride due to its expensive price. As a result, it made the sample biased since it did not carry out randomly and there are more factors that also contribute to the increasing of cancer rate. Generally, wealthy people have fancy and modern lifestyles, and they usually eat unhealthily. So when those people are getting old, they are likely to have more diseases especially cancer. As can be seen, by using inaccurate samples, the statistics can easily be ruined and misinterpreted. Moreover, some people might use this as a tool to benefit their own business by exaggerating the information.

Beside knowledge and living status that were just mentioned; similarly, location also stands as a main role in the statistical experiments. Nonetheless, the researchers must be aware of the result as could be accurate or mistaken. Based on the statistical evidences, different locations such as rural area or urban area can provide different beneficial information. Nevertheless, the numerical facts can be misleading when the sample is incomparable in some ways. For example, there was a survey which was conducted by the American people, questioned “Do you think the Obama administration has already cut the taxes last year?” (Haney, 2011). The truth is that he really had cut the taxes, but surprisingly there were more than 80 percent of people did not think so. The reason behind this issue is that the people who took part in the poll did not represent the whole population in America. The result was only from a small group of people in an urban area. Since people who live in rural area cannot access to the internet and the geographic barriers also make them lose connection from the city. As can be seen, there incomparable sample related to location can lead to misleading statistics as well.

Reference:

Scheuren, F. (2004, June). What is a survey. Retrieved from

https://www.whatisasurvey.info/chapters/chapter1.htm

https://www.whatisasurvey.info/chapters/chapter10.htm

Alden, L. (2005, July). Statistics can be misleading. Retrieved from http://www.econoclass.com/misleadingstats.html

Author unknown, (2005). Survey design [online] Available from:

http://www.surveysoftware.net/sdesign.htm[ accessed 27 october 2013]

Haney,B. (2011, May 13). Chapter1: our treacherous tendency. Retrieved from http://www.calvin.edu/academic/economics/faculty/bios/HaneyDocs/page-58952330.html

Essay Assignment: Asking Biased Questions

There are many factors concerning understanding misleading evidences and statistics. One in particular would be asking biased questions in order to get a biased answer. Many enterprises and businesses in order to get a data or survey they intend, favorably to their likings. Hence, it is essential that we learn to identify biased questionnaires, and keep questioning the methods. There are six walkthroughs and fundamental rules; we need to consider when it comes to analyzing data and statistics. First of which is Understanding potential use of data. What we will need to learn about this skill is to recognize the language of biased questions, explain the size of sample effects. Secondly it is then identifying the biased collection of data. It is often how to predict and identify how the sample might be affected by the way it is chosen, the intention of the study of the results, and determines when it can use to make general statements. The rest of the skills involve figures that misrepresent its data, usages, and its improper use of averages, and introducing opposing view of data. It is vital to think and read critically when doing research, reading articles concerning evaluation of data, graphs, or percentages. When it comes to graphs, readers need to identify how the graph has been manipulated to give a certain impression and to describe what the intention of the person who drew the graph may have been.

       The uses of statistics are indispensable in a multiplicity of specialties. It helps making decisions, predicting the results of the future or making estimation with a high level of confidence. However, once a statistic is misleading, misunderstanding might occurs. For instance, one misleading statistical interpretation occurred when tin helmet was initially introduced in the First World War. During that period, tin helmets were introduced in a bid to reduce the number of head injuries which were very high. By contrast, there was a dramatic increase in the number of head injuries. The issue remained indescribable until it was demonstrated that earlier records were accountable only for injuries not fatalities. The fact was that the number of fatalities fell dramatically, but injury numbers went up because the tin helmet saved their lives, while some soldiers were still injured (Misleading Statistics, Internet).  As a result, that statistics should have been presented in more detailed, as the occurrence of misunderstanding directly caused by the deficiency of detailed information.

A poor or an unfair sample can lead to a misleading statistic. In other words, if the collection and analysis of data is not correctly arranged, it can mislead both the presenters and the readers. Internet polls are obvious examples. Those type of polls cannot be trusted or used in any official purpose, simply because the attendees or voters that are interested in the topic asked in that poll only would vote their ideas. Furthermore, the background information of those attendees areunknown. A poll or a survey takes effect when it shows clearly who are the participants including their ages, socio-economic statuses and other essential background, because that would assist the user in making a clear decisions without any reluctance but with a high degree of confidence. What is more, sometimes people just vote it for fun, so they do it without any contemplative consideration. Therefore, it is crucially important as a reader to find out these information ahead of putting faith in those polls.

Biased can leads from facts to false. Not that it doesn’t seem important but biased of statistics or research can result in undermine of the aim to change based on the result of research. The misuse or misunderstanding the statistic can give us a very wrong or distorted view of reality and can change one innocent or something to guilt and vice-versa. As the gun rules in America shows that it’s clear that gun should not be bought or should be held in a hand of anyone, especially student. But how reporters want us to view depends on if they’re being biased. Some reporters can persuade us that guns can be the protection in an attack and more chance survival the physical fights, but others can argue it is very dangerous and violent to everyone because anyone can shoots at any other person as long as they want, simply because they have gun. In contrast, the reports about 5 astronauts were killed. It was obvious that NASA was blamed because of its reliability. Those reports illustrated that the blame for not being reliable isn’t the first time for NASA. So that we all could trust and at least reporters didn’t sound biased at all.

 

Bibliography
(n.d.). (Telkom Foundation) Retrieved November 1, 2013, fromhttp://www.mindset.co.za/resources/0000042664/0000068826/0000076861/TG%20Manip%20Data_no%20rubric%20FINAL.pdf.

(n.d.). Retrieved 11 01, 2013, fromhttp://www.calvin.edu/academic/economics/faculty/bios/HaneyDocs/.

Misleading Statistics. (n.d.). Retrieved 11 01, 2013, fromhttp://www.suffolkmaths.co.uk/pages/Maths_in_the_World/Misleading%20Statistics/Some%20Examples%20of%20Misleading%20Statistics.doc.

News Biased. (n.d.). Retrieved November 1, 2013, from http://www.umich.edu/ ~newsbias/omissions.html.

Statistics should be Interpreted with Caution as They can be Misleading

Numbers are one of the most important tools to provide information for people. Furthermore, numbers play a very crucial role in statistics. They are evidence that can effectively strengthen any argument and persuade the audience to change their opinions.Statistics can be used in many different fields such as economics, politics and business. However, statisticsare not simple to decipher, we cannot understand statistics by just looking at graphs, numbers and the data shown. It requires a certain knowledge and skill to analyze statistics. During the process of analysis, there are many possibilities that statistics can be misleading, especially due to the mistake of presenter in interpreting it and the presenter’s motive.

Manipulating statistics is one of the common waysto mislead people by data. Manipulate means to give the wrong idea for personal benefit. Authors, advertisers, businessmen and politicians rely on surveys, polls and other statistics to make their points of view appear more credible and trustworthy (LearningExpress Editors, 2011). Peopletend to believe in statistics without making deepconsideration, sothis gives a chance for the presenter to successfully deceive their audience.

First of all, one way that misleading statistics can be seen is through the process of running a business. The company tries to manipulate its product advertisement in order to gain more customers that may lead to the boost of its product’s sale. Misleading statistics in advertisements are seen as false advertising or deceptive advertising because the publisher of statistics uses a false or misleading statement in advertising to convince consumers into commercial transactions that may benefit them. For instance, a case of misleading statistics was depicted in Dannon, which is a well-known yogurt producing company. This company claimed that their popular yogurt, Activia, which was introduced in 2007, has a special bacterium proven to help strengthen the consumers’immune system and regulate digestion in one’s body. Therefore, the brand witnessed a dramatic increase of 30% premium in its annual profit in selling price over other brands (WEINMANN and BHASIN, 2011). In 2008, a lawsuit was filed by one of Dannon’s customer charging the company claims were false and deceived the public into buying a yogurt that was expensive whilst its quality wasa total lie. After settling in court, Dannon paid its consumers up to 45 million dollars. Dannon also had to change its health claims for Activia by removing the word “immunity” and “clinical studies show” from their advertising phrase (MCMULLEN, 2010).

On the other hand, money is not always the reason for pursuing misleading statistics. Sometimes, it can be used in a more official purpose without any relation to money. Some political parties manipulate their statistics to gain power, trust and supporters during the election campaigns. In addition, in order to maintain their images and positions in political parties, politicians use GDP definition revision to hide their falling policies by rewrites the economic statistics to make the public view their policies as successful. For instance, one of the most obvious examples is the calculation of the GDP which was made by Obama administration in which they exaggerated the GDP rates by 3%, while the original GDP report illustrated the slow economic growth in less than 1 percentage. Some professional forecasting services expected the numbers to be as low as 0.5 percentages and year by year the United States’ economic growth seemed to barely grow byone percentage compared to a 2011-2012 which was already tepid at 1.7 percentages. This led to the appearance of the recovery of United States’ economy. In fact, in 2009 all other fiscal-monetary policies in fact have failed to produce a sustainable recovery for the future of the nation (RASMUS, 2013).

Last but not least, some medical companies, in order to fulfill their targets, without any considerations of innocent people life; they falsify the medication advertisement, even though there is an obvious side effect which is a risk to patients’ health. Medicine can prolong life and prevent people from suffering disease but their marketing can be unsafe and sometimes deadly. For example, Glaxo Smith Kline (GSK), which is a giant drug industry, has hidden information regarding the effectiveness and bad side effect of their diabetic drugs, Avandia to the public. As a result, this secrethave not gone unobserved, in recent times, Santa Clara County in Northern California filed a lawsuit against GSK for cover up evidence that Avandia optimizes the risk of heart attack. Nevertheless, recent report of the Senate Committee indicated that the drug is responsible for causing thousands of heart attacks, still all the accusations have been denied by GSK and they continue to claim the FDA-approved drug is safe. The Supreme Court announced that individual has the right to sue Drug Company for great suffering which was caused by incompetent risk labeling on drugs (Ethan A. Huff, staff writer, 2010).

In conclusion, we can see that misleading statistics can be used in a variety of fields in order to deceive diverse kind of audience. Misleading statistics can be effectively used in both the economic fields and political fields because many people still lack the abilities to critically think and assess the information they received. Although some people are good at critically analyze information, no one can always be alerted of the misleading statistics since we see them everywhere, every day. Moreover,statistics for personal benefit have become a controversy for many years and we believe that many people have been aware of this kind of trick. However, clever advertisers still find ways to deceive consumers in ways that are legal or technically illegal but unenforceable.So I recommend everyone to be cautious of these kind of misleading statistics, even though some facts seem to be true at first glance, we need to reconsider about them multiple times to really see through the publisher’s trick.

Bibliography:

-          TROY MCMULLEN, (Feb 26, 2010). Dannon to Pay $45M to Settle Yogurt Lawsuit

[Online]. ABC News. Available from:

http://abcnews.go.com/Business/dannon-settles-lawsuit/story?id=9950269

[Accessed 29 October, 2013]

-          JACK RASMUS, (July 31, 2013). Economic Recovery by Statistical Manipulation [Online]. CounterPunch, Tells the Facts and Names the Names. Available from:

http://www.counterpunch.org/2013/07/31/economic-recovery-by-statistical-manipulation/

[Accessed 29 October, 2013]

-          KARLEE WEINMANN and KIM BHASIN, (SEP 16, 2011, 5:33 pm). 14 False Advertising Scandals That Cost Brands Millions [Online]. Business Insider. Available from:

http://www.businessinsider.com/false-advertising-scandals-2011-9?op=1

[Accessed 29 October, 2013]

-          LearningExpress Editors, (Sep 19, 2011). Manipulating Statistics Study Guide, Manipulating Surveys [Online]. Education. Available from:

http://www.education.com/study-help/article/numbers-game/

[Accessed 30 October, 2013]

-          Ethan A. Huff, staff writer, (Thursday, June 03, 2010). California County sues Glaxo for false advertising of Avandia drug [Online]. NaturalNews. Available from:

http://www.naturalnews.com/028918_false_advertising_big_pharma.html

[Accessed 30 October, 2013]

            In conclusion, statistics can be misleading in many different ways. Without any consideration or ability to analyze the data, people can be fooled by the statistics. Therefore, it is necessary to evaluate  the sources properly before making decisions to use them. It can provide many false interpretations of data and lead to misunderstanding. Providing clear facts and reliable resources can help reduce the risk of being tricked and therefore increase the awareness of foul mistakes. It is compulsory to understand, analyze, and think critically about the data that are shown especially false advertising. Undoubtedly it can be assumed that data and statistics are not always reliable. They  need to trust their reasoning, logic and understanding, like the  old saying " Don't judge a book by its cover".