Misuses Statistics
Regena Kelley
MAT126: Survey of Mathematical Methods
Instructor: Zhimin Huang
January 21, 2013

Misuses Statistics2

Misuses Statistics
Statistics 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 less traveled. There is on the other hand a clear implication that 91 out of a hundred women have traveled the road less traveled in some point of their lives.This example says that in an ad for women for every hundred women 91 of them has traveled the road less traveled. . The implied connection states that from a magizine of a women ad that for every hundred women 91 of them has travedled the road less traveled. It doesn’t discuss who surveyed the ad but implies that an ad was in a women magizine saying this. There is no evidence that proves that the ad was from a

MISUSES STATISTICS3

survey of hundred women and out if the hundred women on 91...

...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 ofmisuse 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...

...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...

...Statistics 1
Business Statistics
LaSaundra H. – Lancaster
BUS 308 Statistics for Managers
Instructor Nicole Rodieck
3/2/2014
Statistics 2
When we hear about business statistics, when think about the decisions that a manager makes to help make his/her business successful. But do we really know what it takes to run a business on a statistical level? While some may think that businessstatistics is too much work because it entails a detailed decision making process that includes calculations, I feel that without educating yourself on the processes first you wouldn’t know how to imply statistics. This is a tool managers will need in order to run a successful business. In this paper I will review types of statistical elements like: Descriptive, Inferential, hypothesis development and testing and the evaluation of the results. Also I will discuss what I have learned from business statistics.
My description of Descriptive statistics is that they are the numerical elements that make up a data that can refer to an amount of a categorized description of an item such as the percentage that asks the question, “How many or how much does it take to “ and the outcome numerical amount. According to “Dr. Ashram’s Statistics site” “The quantities most commonly used to measure the dispersion of the values about...

...
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...

...Lecture Notes on Introductory Statistics, I
(P.P. Leung)
Lecture notes are based on the following textbook:
N.A. Weiss (2012), Introductory Statistics, 9th edition, Pearson.
Chapter 1 The Nature of Statistics 統計本質
§1.1 Two kinds of Statistics
§1.4 Other Sampling Designs (其他抽樣方法)
Chapter 1 The Nature of Statistics 統計本質
What is Statistics? 何謂統計?
From Wikipedia, the free encyclopaedia:
Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities. Statistics is also used for making informed decisions in government and business.
Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics comprise applied statistics. There is also a discipline called mathematical statistics, which is concerned with the theoretical basis of the subject....

...INTRODUCTION
A. Importance of Statistics
Statistical methods have been applied to problems ranging from business to medicine to agriculture. A review of the professional literature in almost any field will substantiate the extent of statistical analysis.
Accounting: Public accounting firms use statistical sampling procedures when conducting audits for their clients.
Economics: Economists use statistical information in making forecasts about the future of the economy or some aspect of it.
Marketing: Electronic point-of-sale scanners at retail checkout counters are used to collect data for a variety of marketing research applications.
Finance: Financial managers have routine contact with information in numerical form. Financial forecasts, break-even analyses, and investment decisions under uncertainty are but part of their activities.
Production: A variety of statistical quality control charts are used to monitor the output of a production process.
Statistics
the collection, organization, presentation, analysis, or interpretation of numerical data, especially as a branch of mathematics in which deductions are made on the assumption that the relationship between a sufficient sample of numerical data are characteristic of those between all such data.
it is a science which deals with the collection, organization, presentation, analysis, and interpretation of data.
B. Fields of Statistics
Descriptive...

...1. Introduction
This report is about the case study of PAR, INC. From the following book: Statistics for Business an Economics, 8th edition by D.R. Anderson, D.J. Sweeney and Th.A. Williams, publisher: Dave Shaut. The case is described at page 416, chapter 10.
2. Problem statement
Par, Inc. has produced a new type of golf ball. The company wants to know if this new type of golf ball is comparable to the old ones. Therefore they did a test, which consists out of 40 trials with the current and 40 trials with the new golf balls. The testing was performed with a mechanical fitting machine so that any difference between the mean distances for the two models could be attributed to a difference in the design. The outcomes are given in the table of appendix 1.
3. Hypothesis testing
The first thing to do is to formulate and present the rationale for a hypothesis test that Par, Inc. could use to compare the driving distance of the current and new golf balls. By formulation of these hypothesis there is assumed that the new and current golf balls show no significant difference to each other. The hypothesis and alternative hypothesis are formulated as follow:
Question 1
H0 : µ1 - µ2 = 0 (they are the same)
Ha : µ1 - µ2 ≠ 0 (the are not the same)
4. P-value
Secondly; analyze the data to provide the hypothesis testing conclusion. The p-value for the test is:
Question 2
Note: the statistical data is provide in § 5.
-one machine
-two...

...typically have? You take a random sample of 51 reduced-fat cookies and test them in a lab, finding a mean fat content of 4.2 grams. You calculate a 95% confidence interval and find that the margin of error is ±0.8 grams. A) You are 95% confident that the mean fat in reduced fat cookies is between 3.4 and 5 grams of fat. B) We are 95% confident that the mean fat in all cookies is between 3.4 and 5 grams. C) We are 95% sure that the average amount of fat in the cookies in this study was between 3.4 and 5 grams. D) 95% of reduced fat cookies have between 3.4 and 5 grams of fat. E) 95% of the cookies in the sample had between 3.4 and 5 grams of fat. Determine the margin of error in estimating the population parameter. 12) How tall is your average statistics classmate? To determine this, you measure the height of a random sample of 15 of your 100 fellow students, finding a 95% confidence interval for the mean height of 67.25 to 69.75 inches. A) 1.5 inches B) 0.25 inches C) 1.06 inches D) 1.25 inches E) Not enough information is given. 12) 11) 10)
3
Construct the indicated confidence interval for the difference between the two population means. Assume that the assumptions and conditions for inference have been met. 13) The table below gives information concerning the gasoline mileage for random samples of trucks of two different types. Find a 95% confidence interval for the difference in the means m X - m Y. Brand X Brand Y 50 50 20.1 24.3 2.3 1.8 13)...