While Statistics can also be misused in many ways such as using not representative samples, small sample size, ambiguous averages and dispersions, detached facts, implied connections, wrong and misleading graphs, wrong use of statistical techniques, serious violation of assumption behind the statistical techniques and faculty surveys, we should also realize that Statistical literacy is not a skill that is widely accepted as necessary in education. Therefore a lot of misuse of statistics is not intentional, just uninformed. But that does not mitigate its danger when misused because Statistical techniques are many times misused, to sell products that don’t work; to prove something that is not really true, to get the attention of public by evoking fear and shock. Statistics has numerous uses. It is difficult to find a field in which statistics is not used. Statistics plays integral part in many disciplines, and do not take reported relationships at their face value, especially if you cannot see a direct, causal link between them. There may be a common-sense reason why they are linked through a third, unreported variable or other intended or unintended connections. Going through exercises 1 through 10 on page 810, I decided to do exercise number 4. The question reads “In many ads for weigh loss products, under the product claim and in small print, the following statement is made: “These results are not typical.” What does this say about the product being advertised?” It is intriguing but rather serious when media plays with our emotion just to get our attention in whatever ways they can. Both print and electronic media have created a means of satisfying our emotional instabilities by coming up with advertisements that will capture our attentions. Weigh loss products and program are few of the many that have been bombarding the airwaves. Many at times I pondered when watching television or listening to radio commercial, whether these...

...Running head: MisusesStatistics 1
MisusesStatistics
Regena Kelley
MAT126: Survey of Mathematical Methods
Instructor: Zhimin Huang
January 21, 2013
MisusesStatistics 2
MisusesStatisticsStatistics and survey are misused and not accurate because of many factors. The types of these statistics are found suspect samples, asking Biased questions and misleading graphs. There are businesses that use these statistics with questions to convice people to accept the statistics. People need to understand what is and not being persented in the statistics. The two examples that I will talk about will be either implied connections, or ambrguous average. These types of misleading and misused examples is used as a scheme for you to buy into it.
The first example is number 3 on page 810. It states: “In an ad for women the following statement was made for everyhundred women, 91 have taken the road less traveled”.
This statement uses some implied connections that are confusing in an effort to convince people that an ad said for every hundred women that 91 have taken the road less traveled. It doesn’t say that a survey was conducted and has been proven that out of every hundreds of women only 91 say they have taken the road...

...analytical ability and articulation skill based on sound knowledge of statistics, which I developed during my academic career both as a student and teacher of Statistics at BHU, greatly contributed to my progress and success in banking career. I am grateful and thankful to all my teachers and colleagues in the department for what I am today.
4. Today, I have chosen to speak on a theme which is directly relevant to all of you and that is “Uses andMisuses of Statistics”. Let me begin with a quote:
The safety of science depends on the existence of men who care more for the justice of their methods than for the value of any results obtained by using them.2
5. Statistics is a method of learning from experience and decision making under uncertainty. That is why it is often called the study of the laws of chance. Chance is inherent in all natural phenomena, and the only way of understanding nature and making predictions is to study the laws of chance and formulate appropriate rules of action. Chance may appear as an obstructor and an irritant in our daily life but chance can also create. Through statistics, we have now learnt to put chance to work for the benefit of mankind. C. R. Rao, in the preface of his famous book ‘Statistics and Truth’ thus said ‘all knowledge is, in the final analysis, history. All sciences are, in the abstract, mathematics and all methods of...

...Misuse of Statistics
Johnny Test
MAT 126
Professor Plum
June 32, 2011
Dermatologist Recommended
In an ad for moisturizing lotion, the claim “it’s the #1 dermatologist recommended brand” was made. This is clearly misrepresentation because no supporting facts are provided. When I read that something is ranked number one, the first thing I think of how this was originally decided. What exactly makes this lotion the top recommended brand and what other brands were tested by dermatologists? Exactly how many products were included in the deciding factor and what was the basis for comparison? It could be anything from greasiness to longevity. Every consumer is different and may have different reasons for choosing a certain brand. For this particular claim, we don’t even know if the dermatologists were licensed to practice. It is a vague and bold statement designed to address the basic needs of the consumer and it uses a bit of deception to sell a product.
For this particular example there is a bold and direct statement saying that the results of some unknown research has revealed the top brand. The problem with this ad is that no one knows what brands were selected, how they were selected, or the size of the sample. This is a claim that uses detached statistics.
Give Up Your Coffee
In an article in USA Weekend, this statement was made: “More serious seems to be...

...techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of data analysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to infer the...

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t like this...

...of 1000 flights and proportions of three routes in the sample. He divides them into different sub-groups such as satisfaction, refreshments and departure time and then selects proportionally to highlight specific subgroup within the population. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost.
TABLE 1: Data Summaries of Three Routes
Route 1
Route 2
Route 3
Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean
107.15
Std Dev
5.1536687
Std Err Mean
0.3644194
Upper 95% Mean
107.86862
Lower 95% Mean
106.43138
N
200
Sum
21430
From the table above, the total number of passengers for route 1 is 44,266, route 2 is 29,131 and route 3 is 21,430 and the total numbers of passengers for 3 routes are 94,827.
Although route 1 has the highest number of passengers and flights but it has the lowest means of passengers among the 3 routes. From...

...compliments the regular mathematics and therefore both are tested in primary schools. Mathematics is the written application of operation. It teaches students to think clearly, reason well and strategize effectively. Mental Mathematics is the ability to utilise mathematical skills to solve problems mentally. The marks scored by pupils generate statistics which are used by teachers to analyse a student’s performance and development of theories to explain the differences in performance.
The Standard 3 class is where the transition from junior to senior level occurs where teachers expect the transference of concrete to abstract thinking would have occurred.
A common theory by many primary school teachers is ‘Students perform better in Mathematics than Mental math. Mental math is something that has to be developed and involves critical thinking. Mental math requires quick thinking and the student must solve the problem in their minds whereas in regular mathematics, the problem can be solved visually. Therefore, teachers should take these factors into consideration while testing and marking students in these areas.’
In this study, the statistics of 30 students of a standard 3 class of San Fernando Boys’ Government School will be analysed to determine the truth of this theory.
DATA COLLECTION METHODS
Mathematics and mental mathematics marks of term 1 of the class of 2013 were obtained from a Standard 3 teacher of San Fernando Boys’...

...
MBA 501A – [STATISTICS]
ASSIGNMENT 4
INSTRUCTIONS: You are to work independently on this assignment. The total number of points possible is 50. Please note that point allocation varies per question. Use the Help feature in MINITAB 16 to read descriptions for the data sets so that you can make meaningful comments.
[10 pts] 1. Use the data set OPENHOUSE.MTW in the Student14 folder. Perform the Chi
Square test for independence to determine whether style of home and location are are related. Use α = 0.05. Explain your results.
Pearson Chi-Square = 37.159, DF = 3, P-Value = 0.000
Likelihood Ratio Chi-Square = 40.039, DF = 3, P-Value = 0.000
The P value associated with out chi square is 0.00 and the Alpha level is 0.05 so we reject the null hypothesis. The P- value is less than the alpha level. So, we conclude that style of homes and locations are not related.
[10 pts] 2. Use the data set TEMCO.MTW in the Student14 folder. Perform the Chi
Square test for independence to determine whether department and gender are related. Use α = 0.05. Explain your results.
Pearson Chi-Square = 1.005, DF = 3, P-Value = 0.800
Likelihood Ratio Chi-Square = 1.012, DF = 3, P-Value = 0.798
The P-value associated with out chi square is 0.800 and the Alpha level is 0.05 we can see that we are unable to reject the null hypothesis. The P- value is greater than the alpha level. So, we conclude that departments and gender are related..
[30 pts] 3. Use the data set...

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