Nowadays,
all over the world, numerous information has been put into statistics
most of which have the potential to influence people successfully. Statistics
are collections or comparisons of data which represent not only facts but also
measurements and in some cases, lies. These group writings are written in order
to alert people not to make generalizations without further analysis.
Statistics should be approached with caution: some provide relevant information
whereas others are unreliable. First and foremost, this assignment will discuss
about samples and polls then on how graphs, political statistics and
advertisements can be misleading. Lastly, it contains some examples of false
information.
Group 5:
(Word Count: 1093)
Level: EAP5
Class
day/time: Mon/Wed/Fri 11:30 – 13:00
Samples
Nowadays, statistics is crucial for
business, politics, education and science. It is also present in journals,
reports, advertisements, and so on. However, not all statistics are reliable.
Some are misused in order to convince citizens or customers. Figures catch
audiences’ attention, but it does not mean that figures are always true and
accurate. It is not very difficult to manipulate statistics. This essay
emphasizes the importance of samples in statistics and polls. The sample size
influences the accuracy of the results but size is only one point of the topic.
There are two points more that we are going to study. One is sample type and
another is categories.
To begin, it is important to know the types of
samples which are used to make polls or statistics. Although, many types of samples
are used but some of them are misused. There are two main types of samples,
Probability Sampling and Non-Probability Sampling. Probability Sampling involves
population sample selection, which means that everyone in the public has a chance
to be selected, randomly, as a representative of the population (Crossmen, date
unknown). For example, we go to interview the students in Sisowat High School
to know what subjects they like to study, so we randomly select one or
two students from each class. Most students, that we have selected, said they want to
study math, so we simply assume that most students studying
in Sisowat High School like to study math. Whereas, for non-probability sampling,
people have no chance of being selected randomly and the selection based on
people’s interest (Crossman, date unknown). For instance, a sport supervisor want
to interview people who like winter sport about the kind of winter sport they like
to play, so he go to ask a group of people who like different kind of sports. In
this case, he only want to interview people who interested in winter sport, so the
other people in the group who does not interested in winter sport have no chance
to be selected.
In addition, statistics is not reliable when the
generalization is made from a smal lsample size. It means that a small sample
size does not accurately represent the whole population. The reliability of
generalizations made from small samples are weak (Rowntree, 1982). For instance,
imagine if the Pizza Company wants to study the number of Cambodians who like to
eat pizza and it also wants to represent in percentage to persuade that new
generations really like to eat their pizza so it has to select a sample. If 100
students are chosen to be interviewed and if the result shows that 80 percent of
Cambodia's people like to eat pizza. It will not be accurate because it does not
show the number of the whole population. Furthermore, there is also a
self-selection sample in some polls which is made the
statistics undependable because there are some people who would like to vote and
other people who do not like to participate in the vote ( Renka, 2010). For
example, there was an election in 2000, Newsweek published the
following poll results. It was publicized that Nader was the only candidate
worth voting for, because he got the 9 percent of the vote so people expected him
to have at least 9 percent of the vote. But at the end of the real vote,
he had only 3 percent. In this case, it was because of the self-selected sample :
which gave some people who are underage can vote and other people did not
participate in this vote, maybe because of their work or
because they thought that they would participate only in the real vote. Moreover,
people who participated in this vote maybe they are Nader's supporters and they
are interested in the questions.
Accurate statistics have to use
samples that are representative of the population. Statisticians divide the
sample in categories: age, sex, level of education, social class, and so on. An
issue is different in a country where the majority of population is young (for
example in Cambodia) or in a country where the number of elderly people is
important (Japan or European countries). Recently, an article in The Guardian drew attention on the
question of childcare in UK (Parents struggling with cost of childcare, 2014).
The journalist provided three important numbers:
- A third of parents with children
under five spent 30% of salary on childcare.
- 50 % spent at least 20%.
- 25% say they did not ask their family for help to do childminding.
The survey was concerned with 1625 people, an accurate number for a
poll. However, the article reports that it comes from the website
GoodCareGuide.co.uk. This website is a kind of TripAdvisor for childcare
places. Parents can post admirations about a nursery, nanny or childminder. We
can assume that people who answer the questions are particularly involved in
the topic of childcare, which can make statistics misleading. Moreover the
reader has no information on the categories of family: number of children,
salary, social class, geographical origin and residence. All these data are
important because statistics have to be a fair reflection of the real
population. For instance, a family with 50 000 dollars income can spend
30% for childcare more easily than another family with 10 000 dollars.
Likewise, if your parents or your sister live 400 kilometres away from you, you
can not leave your children in their place for one day. When it comes to the
immigrants, some of them have no parents or relatives in UK, so they cannot ask
them for help. Another thing is the single mothers problem. Many mothers
educate their children alone. For them, the childcare is very important, because
they absolutely need to work. Unfortunately, the website GoodCareGuide.co.uk
does not provide information about the details of the survey and the categories
precisely involved with it. But a Guardian reader, after a quick reading, keeps
just the figures in their mind.
To sum up, after looking further,
we can see that sample can mislead people by using different techniques including
types, sizes and categorizes. This can show that not only statistics such as
advertisements or graphs are unreliable, but sometimes sample can also be unreliable
and should be looked at with caution. In order to avoid being mislead by sample in polls
or statistics, people should look through the information first and interpret
the data before jumping to the conclusion.
Bibliography :
·
Author
unknown (2014). Parents struggling with cost of childcare, researchers find. The Guardian [online]. Available from:
http://www.theguardian.com/money/2014/feb/08/parents-cost-childcare-nursery [Accessed 9 February 2014].
·
Good Care Guide (Date unknown). Available from:
http://www.goodcareguide.co.uk
[Accessed 9 February 2014]
·
Rowntree, D. (1982).
Statistics without tears: a primer for non-mathematicians. Harmondsworth:
Penguin.
https://archive.org/stream/StatisticsWithoutTears/Rowntree-StatisticsWithoutTears#page/n21/mode/1up
[Accessed 10February 2014]
·
Russell D. Renka (2010).
The Good, the Bad, and the Ugly of Public Opinion Polls.
http://cstl-cla.semo.edu/renka/Renka_papers/polls.htm.
[Accessed 10 February 2014]
·
Crossman, A. (date unknown). "Types Of
Sampling Designs."About.comSociology. Available from:
<http://sociology.about.com/od/Research/a/sampling-designs.htm>.
[Accessed: 17 February 2014]
EAP 5
Days: Mon/Wed/Fri Time: 11:30-13:00
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Fourth Draft
MISLEADING GRAPHS
There are many ways to misrepresent
data in statistics, but one of the most egregious ways is using graphs. Graphs
depict data in which numbers are often believed to have an accurate proportion.
However, there are some cases when graphs can be misleading. A misleading graph
is a graph which shows inaccurate data unintentionally or intentionally by the
designers, and the readers may make incorrect assumptions from the graphs(Witte
et al, 2009, Internet). Various types of graphs can be used such as bar graphs,
pie graphs, line graphs, pictographs, and other types of graphs. This essay
will demonstrate why misleading graphs are created, how line graphs and
pictographs can be misleading and how to avoid misinterpretation of data in
those graphs.
Graphs
constituted as misleading can be used for variety of reasons. The designers
purposefully design the graphs to hide or exaggerate the proper interpretation
of the graphs. Without careful analysis, readers will misinterpret the data and
fall into their traps. However, in some cases, misleading graphs may be created
accidentally by users who lack knowledge of numerical data or the graphing
software, by the readers own misinterpretation of the data, or because the data
is difficult to convey accurately. Misleading graphs are often found in false
advertisements which are used by some corrupted companies to convince customers
to buy their products. They are also useful in financial data and corporate
reports (Witte et al, 2009, Internet).
The following graphs are selective examples to
illustrate how graphs are misleading.
Figure
1:As
you can see in the picture above, this statistic is talking about the
productivity of fertilizer. Why is the first graphdifferent from the second
one? (Haney, Internet)
 | ||
| A |
 |
| B |
(Source:
http://www.calvin.edu/academic/economics/faculty/bios/HaneyDocs/page-58978255.html)
If we take a look at the figure 1 at the
first sight, graph B will gain the most attraction. The graph increases sharply,
which means that the company got high productivity. However, the difference
between these two graphs is vertical axis. The company used big interval numbers
to make it look more attractive. To create these kinds of graphs, the first
thing is to make sure that all the information is true. Secondly, change the
proportion of the horizontal axis or vertical axis to make it more attractive
or jaw dropping. This kind of graph is called the Gee-Wiz graph. This method
has already been used for about 70 years. (Haney, Internet)
Figure
2:In
this second picture, the graph shows someone’s GPA (Grade Point Average). Turning to the point, as you look at the
human and brain picture and the graph, arethere any differences? (Haney,
Internet)
 |
| C |
 |
| D |
(Source:
http://www.calvin.edu/academic/economics/faculty/bios/HaneyDocs/page-58978264.html)
There is a small difference between 3.0
and 3.5 by bar graph. However, in the second graph, the writer converted the
simple bar graph to pictograph by using different scales into two pictures.
Picture C will get the most eye-catching because it is bigger than picture D.
The strategy is to raise the head length and expand the width of the picture.
The length and width can change the area of the picture. The formula is Area= Length
X Width (Haney, Internet). People will get confused easily with the pictograph
at the first sight because all of the pictures are creative, reflective and
deceptive.(Haney, Internet)
Figure
3:This
graph looks different from the others because it is 3D. Based on the graph,
does it look misleading? How can this graph be reliable? (BBC, 2014, Internet)
(Source:
http://www.bbc.co.uk/schools/gcsebitesize/maths/statistics/representingdata2rev5.shtml)
The figure 3 shows the number of singles
sold from 1995 to 1998. The bar graph is different from the other graphs because
it is used as a 3D bar chart to draw attention. There are some reasons which
cause this bar graph to be misleading. First, there is no accurate scale for
the vertical axis. Furthermore, the perspective can make a huge difference of
the number of sales in 1995 comparing to other years. It would be better if the
bar graph was made in 2D picture.(BBC, 2014, Internet)
Misleading graphs are commonly found
when there is statistic presentation. To avoid misinterpretation, here are some
key strategies to help avoid the misleading graphs. First of all, find out
thetitle of the graph and then make sure what it is about. If it is a line or
bar chart, label both axes. Notice that the scale of a line or bar chart must
have the same intervals and start with zero. Figure 1 is a good example to
clearly demonstrate how the misleading graph works in different scales. In
picture A, the interval of the vertical axis is 10,starting from 0 while
picture B has only one interval different and it does not start with 0.
Consequently, it looks like picture B has a sharp rise. Actually, the two
graphs come from the same statistics about productivity of fertilizers. It is
easy to make the two graphs more accurate by equally numbering the scales of
vertical axis.
The source of the data is another thing
to consider. Also,make sure that the sourceis reliable. For pictographs, the
size of a symbol must be uniforms. In figure 2, picture C does not show the
uniform size with the picture D. The width of picture C is longer than picture
D. To make the pictures accurate, both pictures should be of the same size. One
more common type of misleading graphs is 3D bar charts which are used to easily
cheat people. Figure 3 can be an excellent example which shows the sales for
1995 were far better than the other years. In fact, it is identical to sales in
1997. To deal with the 3D bar chart, scales for vertical axis must be numbered
properly. (Faculty.atu.edu, Internet)
Graphs can be easily used to mislead
people. By using some methods, people undoubtedly believe the misrepresentation
of data in the graphs without much analysis. Nonetheless, it can be really
difficult to differentiate misleading graphs sometimes. Still, people have to be
very careful with every graph they encounter because they do notall provide
reliable information.
ôôôôôôôô¦ôôôôôôôô
BIBLIOGRAPHY
Author unknown,(2012).Misleading graph
[online].BBC. Available from:
http://www.bbc.co.uk/schools/gcsebitesize/maths/statistics/representingdata2rev5.shtm
[Accessed 10 February 2014].
Author unknown.Misleading Graphs and
Statistics [online]. Available from:
http://faculty.atu.edu/mfinan/2043/section31.pdf
[Accessed 7 February 2014].
Haney, Becky. How to lie with statistics
[online]. Calvin College. Available from:
http://www.calvin.edu/academic/economics/faculty/bios/
Haney Docs /page-58978264.html
[Accessed 10 February 2014].
Haney, Becky. How to lie with statistics
[online]. Calvin College. Available from:
http://www.calvin.edu/academic/economics/faculty/bios/
Haney Docs /page-58978255.html
[Accessed 10 February 2014].
Witte, R. S.,
& Witte, J. S. (2009). Statistics 9th edition [online]. (9th
ed.). New Jersey: John Wiley & Sons, Inc. Available from:
https://www.boundless.com/statistics/frequency-distributions/frequency-distributions-for-qualitative-data/misleading-graphs/
[Accessed
10 February 2014].
MISLEADING POLITICAL STATISTICS
Statistics are the science of collecting
numbers which represent a fact or measurement. Statistics have been used in
advertisements, news, politics, science, and also economics, in the forms of
tables, charts, bars, graphs, polls, and so on. Statistics can be used to
indicate examinations of facts; however, in some cases, people create fake statistics
which make people misunderstand it. In this essay, we will describe about a
type of misleading statistics which is about politics and we will also talk
about the causes and effects with some solutions along with it too.
First of all, the causes of misleading
political statistic would be desires of politicians to catch people’s interest
and also journalists’ goals of catching people’s attention toward their
articles or projects. Some politicians may use misleading statistics to reach
their goals in some ways such as to promote themselves before the election or
to convince citizens about the development of the country and the achievements during
their time of becoming president. For example, the misleading political
statistic which happened in the last two years in the United States that was provided
by Obama about the unemployed veterans’ rate. It was announced that the
percentage of the unemployment was lower after Obama entered the office
comparing to the period before he was elected. In fact, the number of
unemployment was already low at the time when he came into the office (Michael
Tennart, unknown year). The statistic which was used by Obama can also be
misleading because in this type of issue, political statistics can earn the interest
of the citizens for the politicians as it shows the ability to solve problems
and how successful the current president’s works are. Other than misleading
statistics that were made by politicians, some other misleading statistics can
be made by journalists or reporters as well. For instance, from what we have
studied, there was an online poll about the people that would get the most
votes in the election. Comparing this online poll result to the real election
result, we found that there were huge differences. It was misleading because
not all the citizens participated in the polls and only groups of people who
were really interested or those who live in modern lifestyles would join it,
which made this statistic unreliable.
Secondly, as misleading political
statistics mostly happen intentionally, it may widely affect citizens’ lives
after they believed in political lies. Political statistics may be able to make
people believe and make assumption quickly without careful analysis, however,
for people who see further, they will think critically about the source of
statistics which can help them avoid making wrong decisions, while those who may
simply be persuaded by the statistics, would make wrong choices. For example,
before every election, politicians from all parties will spread policies to
attract supporters. Some politicians may stretch the truth by using statistics
if they think it will increase the rate of voters. So some people may jump to
conclusions quickly which makes them choose the wrong leader or party to lead
their country. Other than this, misleading political statistics will also make
people unsatisfied. Citizens need the leader who is competent and able to
manage all the problems. As soon as the citizens are able to reveal the fake
information or misleading data they will lose hope or belief and feel less
confident about the leader’s policies (Richard R.Lau, Lee Singleman, Ivy Brown Rovner,
2007). Another example, politicians could promise that if they
win the election, the government will pay for the citizens’ medical services.
Thus, some people who are knowledgeable about economic status of the country
will not believe in that kind of policies which is almost impossible to be
provided. They would think that it is just a fake promise to persuade people to
believe and vote for them. In addition to this, when the leader cannot complete
what they promised, people will protest against the government by holding
demonstrations or strikes. These can affect the social security and have an
impact on the investment processes which may affect investors’ decisions as
they might be worrying about conducting business in an insecure political
country, which leads to another economic crisis in the country.
Finally, the main solution to this problem
is to clarify the statistics. The first suggested solution is to learn more
about the methods of the survey. Generally, misleading political statistics are
made by using graphs or asking biased questions to get the result that can
benefit them (Harwell, 2010) or using
amounts or number to exaggerate the result instead of using percentage. The
second advice is to clarify the meaning of words included in the statistic. It
occurs frequently that people misunderstand the definition of the word being
used which is the statistics’ goal of making it misleading. Beside these
advices above, it is suggested that readers should understand clearly about the
mode, median, and mean average because different types of average are being
used to provide different results. The last thing that is advised is to make
sure that the statistic included reliable sources. Normally, the reliable
sources would be provided below the statistic by using an asterisk as the sign
for the sources in small letters.
In conclusion, misleading political
statistics can be found everywhere. People try to produce misleading statistics
for different kinds of benefits so people should try to avoid being convinced
by any kind of misleading statistics. For some reason, people should not always
believe what they see in statistics; instead they should compare it with real
life or situations. It would be more helpful to identify the true and the fake
information using reality. This is also the key to avoid misleading statistic.
Bibliography
Michael
Tennart. Obama’s Misleading Statistic on Veterans’ Unemployment.
Retrieved from http://www.thenewamerican.com/usnews/politics/item/13389-obama%E2%80%99s-misleading-statistic-on-veterans%E2%80%99-unemployment
Harwell. (2010, 03). How to create Misleading
statistics in 6 easy steps. http://blog.makingitclear.com/2010/03/25/statistics/
Richard R. Lau, Lee Singlman, Ivy
Brown Rovner (2007). The Effect of Negative Political Campaigns: A
Meta-Analytic Reassessment. Retrieve from
www.web.posc.jmu/polbehavior/readings/Topic10_Median/lau+singleman+rovner%.com.
Best,
Misleading Advertisements
In addition to the issues, which were
mentioned earlier, let us take a look at how advertisements could be misleading
with and without statistics.
The
most common ways that have been used by marketers are the use of misleading
statistics to link up with the terms of “more”, ”new”, ”discount”, and fear
factors which are used to threaten people in their advertisements (False
advertising, 2012, Internet). In this technique, the marketers might use
inappropriate samples to misinform the statistics, which leads to misleading
advertisements. One good example of this technique would be from the Colgate
advertisement in 2007 when the company claimed that 80 percent of dentists
recommended the brand. At that time, customers might conclude that Colgate was
the best choice because only 20 percent of dentists recommended different brands.
However, according to the Advertising Standards Authority, Colgate’s survey was
only based on telephone surveys of dentists and hygienist which were made by an
independent market research company. Therefore, it turns out that the marketers
just used a small sample size to make misleading statistics and included it in
the advertisement (Derbyshire, 2007, Internet). Moreover, fear factors are used
in advertisements to entice customers as well. Normally, they insert threatening
words in their commercials to convince customers to assume that they need to
purchase those goods. A good example would be the advertisement of ACME life
insurance. It indicated that accidental and premature events could occur to the
head ofAmerica’s families who live to age 75 on average, and leave no support
to the family members. In this case, among the list of fearful things, the fear
of death ranks at the top (Critical Reading of Advertising Material, 1996,
Internet).
In
addition, in some commercials, the producers not only like to conceal the real
benefits of the products, but also paying the actors to mention the terms and
conditions in inappropriate accents. To conceal the qualities means the
creators try to persuade consumers that their products’ quality and appearance
are the best while the actual products are usually in average conditions and
forms. For instance, Activia yogurt and DanActive dairy drink advertised that
it had been scientifically and clinically proven to regulate digestion and
boost immunity system 10 percent better than the others. Nevertheless, the
company was sued to pay $45 million and changed its health claim because their
products have not been medically proven as the company claimed it would be
(Troy, 2010, Internet). Furthermore, in some TV commercials, the actors are
paid to mention about products’ terms and conditions in uncertain accents or
accelerate their speech so that most customers could not understand. For
example, in 1981, Moschitta, who was best known for rapid speech delivery, was
paid to advertise in FedEx’s commercial. In this advertisement, it wrote “When
it absolutely, positively has to be there overnight” in very big capital while
Moschitta mentioned “Areas served, delivery times, and liability subject to
limitations in our Service Guide” for just 5 seconds after it (John Moschitta,
Jr, 2009, Internet).
Instead
of inserting false statistics, there are two other popular ways which are used
in advertisements to manipulate consumers. Firstly, and commonly, the producers
hire celebrities to advertise their products and then follow by the use of
fantasy words in the advertisements.Tobegin, using celebrities to advertise is
a very effective marketing trap. It provides lots of advantages to manufacturers
of the products because celebrities often generate attention from people. In
this case, people might fall for the trap and purchase the products
unconsciously. People may think those products must have high qualities since
they are recommended by celebrities. Moreover, people would also think that by
using those goods, it will make them beautiful like celebrities because there
are some people out there who think “If the product is good enough for her,
it’s good enough for me.” Additionally, it is obvious that obsessed fans would
purchase products that are advertised by their idols. For instance,
Wonderstruck perfume has rapidly become very popular after Taylor Swift
advertised it. Thus, there is a high chance that people would be influenced to
the products without examining it effectively, especially with celebrities’
presences (Suttle, 2014, Internet). Another persuasive marketing technique that
is used by marketers is advertising dreams. They often use the glitz and
glamour words to hide the impossible and unachievable result of their products.
For example, nanoblur claimed that by using this cream, it could make you look
younger in 40 seconds. It is obvious that they are just selling an impossible
dream because even though the particles are at 700 nanometers, it is still too
big to slip into the skin. Hence, they could only reflect the light from the
skin’s surface (Food for thought, 2009, Internet).
Bibliography
Simon, R., (2007). Critical
Reading of Advertising Material [online]. 6 University Way, Bellevue
Heights, SA, 5050. Available from:
hptt://www.rocketreader.com/newsletter/newsletter14.html
[Accessed 15 February
2014]
Troy, M., (2010). Dannon
to Pay $45M to Settle Yogurt Lawsuit [online]. Available from:
hptt://abcnews.go.com/Business.dannon-settles-lawsuit/story?id=9950269
[Accessed 15 February
2014]
Author unknown, (2011).
False advertising [online]. Available from:
hptt://en.wikipedia.org/wiki/False_advertising
[Accessed 15 February
2014]
Suttle, R., (2014). What are five advantages of using celebrities in
advertising? [online]. Available from: hptt://
smallbusiness.chron.com/five-advantages-using-celebrities-advertising-34394.html.
[Accessed 15 February 2014]
Derbyshire, D., (2007). Colgate gets the brush off for “misleading”ads
[online]. Available from:
hptt://www.telegraph.co.uk/news/uknews/1539715/Colgate-gets-the-brush-off-for-misleading-ads.html
[Accessed 02 March 2014]
Author unknown, (2009). John Moschitta, Jr. [online]. Available
from:
hptt:// en.wikipedia.org/wiki/John_Moschitto,_Jr.
[Accessed 02 March 2014]
Author unknown, (2009), Food for thought [online]. Available from:
hptt://flawlessgl.wordpress.com/tag/misleading-advertising/
[Accessed 02 March 2014]
Word Count: 852
False
information impacts on statistics
For today’s world, technology
has improved and found ways to describe figures or interests such as
communication, descriptions, commercials and statistics. Statistics is a method
used to organize data (Rowntree, 1982). Statistics can illustrate both lie and truth to the users so that people
should be careful with what they are reading or creating. This essay will focus
on false information and discuss about benefits and drawbacks of statistics as
well as some samples.
Statistics are ubiquitous, especially in newspapers and commercials, and they are
the main source of countless numbers of articles (Bain, 2011). For instance, there
are advertisements about business, politics, games and
television commercials. For example, a company tried to convince customers to buy
their products by stating that many scientists recommended their products. Some
individuals instantly believed it without any further analysis. Experts might
value the product, but it did not specify the exact number of scientists or whether those scientists were qualified
to endorse that product or not. Vishal, resident of Gurgaon in India,
tried to copy a commercial “Red bull gives you wing’’. Vishal who drank thirty
cans of red bull jumped off a building due to that commercial. The commercial
indicated that after having the energetic drink, anyone would be able to grow
wings and lift off their feet from the ground (Virginia, 2010).
In another commercial “All natural, All cola” from Red bull, the narrator said that Red bull drinks contained only natural ingredients, but later there were studies of consumers suffering from dehydration, tremors, heat strokes and heart attacks (Moefu, 2010). Why was this information not included in the commercial? This was done in order to make the commercial become beneficial for the company, then people could understand how good Red bull was, so the writer chose what was suitable to present. Similarly, some companies benefited by creating the experiments with a small group of people, which proved that their products have good quality (Korn, 2009).
Nonetheless, although statistics can show parts of the truth, they also cause misinterpretations to the users (Korn, 2009). An Internet advertisement shows that “wrinkles
free in only minutes”. What is wrong with this phrase? The “only” and “minutes”
are obviously created to motivate readers to use their products. The attraction
of “no wrinkles” in any “minutes” was used in this case, but we do not know the
real amount of minutes (Ryan 2008). For this reason, the company might be able
to boost their popularity and attraction when users read the products’ tags.
The majority of statistics are used for describing numbers, figures,
amounts and percentages. Specifically, data can help the users to classify
things and identify the problems (Rowntree, 1982). Coloration
also plays a salient role in some misleading statistics because it tends to
confuse readers about what it really tries to show (Robbins, 2012). The
coloring parts in different charts, which are on the same topic, do not even
connect well with each other. Then the statistics could be hardly true. All the
mistakes would only fool people and convince readers to agree with their
confused theory (Robbins, 2012). The following picture is one of the graph
charts that exist with the mistake above.
The colors in the map and
the accompanying pie chart are different. For this reason, on the map (right),
we see that upper-black color was used to represent Kentucky, and then the
readers might make an assumption that the black color on the pie chart (left) would
also refer to Kentucky without reading the labels carefully. Actually, the
black color on the pie chart (left) indicates Piedmont. So, consistency of color
is very important in graphs showing the same data of one statistic (Robbins,
2012). People tend to get a better
understanding in comparing two or more tables or graphs on the topic by reading
through those statistics (Pinkmonkey, Study Guide, 2011). However, in some cases
like picture above, the charts are not even accurate so readers have to read
carefully in order to avoid the wrong statistics.
Moreover, there are
many ways that graph can be misleading such as using casual images, reversing
skills, and hiding small samples (Post,
2011).
Firstly, attractive images could bewilder people about the graphs. For example,
this particular company was trying to decide which products had given them more
profits than the others. This graph (below) was made with little pictures of dogs,
cats and food cans. That was an example of bad sampling that readers cannot
understand just by reading the graph (Post,
2011). Whenever the statistics are fabricated or intentionally invented without
proof, many people will be misled with the data that has been shown (Korn,
2009).
To sum up, statistics are widely used. There is clear evidence that
shows statistics can coat the truth too. Statistics are essential in daily
life, but they are also notorious for the purpose of making false and
misleading arguments (Korn, 2009). As a result, readers in particular areas
should search more even if they have the statistics since they can also be
deceiving when the truth is being manipulated or hidden for specific purposes
(Can, 2011).
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