Statistics involves the development of methods and tests that are used to quantitatively define the variability inherent in data, the probability of certain outcomes, and the error and uncertainty associated with those outcomes. Some statistics are biased, some are based on opinions, and some are fabricated. A common misconception is that statistics provide a measure of proof that something is true. Instead, statistics provide a measure of the probability of observing a certain result. It is easy to misuse the statistics in data analysis even to the point of misconception because statistics do not introduce systematic error which can be introduced into the data intentionally or accidentally. There are many associated variables in statistical numbers that the person analyzing the data does not see, and without further explanation or supportive data, one can easily come to the wrong conclusion and the scientist data could be presented as facts rather than probability. If the source from which the data was gathered was not factual, then this will reflect a statistic that is misleading, biased, and based on false information, but those persons who might later interpret the data had no idea that the source was not factual, and as a result wrong information is publicized. Because statistics deal with numbers they often seem to be more convincing and less suspicious of false claim than descriptive arguments, but numbers can be easily manipulated in favor of someone’s opinion. In the last presidential election in the United States, there have been many misconstrued statistical data in the polls leading up to election day that give a false reflection of American public. From the statistical data, one would assume that only poor minority groups voted for President Obama and only white middle class and rich people voted for Mitt Romney. In many instances, people who were polled willingly set out to give false information of their intention, some people refused to reveal...

...Howcouldgraphics and/or statistics be used to misrepresentdata? Where have you seen this done? Statistics, graphics, and database are used in medical field to approve, prove, or disapprove theories, analysis, and interpretation of ailments, medication and it’s impact, and treatment and it’s effectiveness. However, these data can be easily misinterpreted when and where there is a vested interest. Individual opinions are generalized without considering whole aspects of the issue, thus forming a biased opinion.
Data can be misguiding if the sampling is not done properly. A random selection without background knowledge or without specified criteria leads to misinterpretation of the data. Another cause of misinterpretation is difference in causation and association. Variables after another but one variable does not cause another. One of the manipulated areas in medical world is pharmacy. Pharmaceutical companies use misguided data in competitive markets. Generic medicines for same purposes are branded out and to advertise it misguiding database is used. The most important thing to be considered while interpreting or predicting an outcome of a statistical analysis is a well balanced and well selected population. Sample is to be selected considering different aspects...

...testing of two samples means were because it compared the two sets of data that are directly related to each other. The reason why I believed that rural homes have a lower average of beds due to the fact that rural areas are the countryside rather than the big known towns or towns of the state.
The population that my data set represents was the number of beds that the in-patients had in each of the homes between non-rural home and rural home facilities. The reason why the data was collected was because the Department of Health and Social Services of the State of New Mexico and cover 60 licensed nursing facilities in New Mexico in 1988. The methods that were used to collect the data was by the number of beds that were used in the home, annual medical in patient days (hundreds), annual total patient days (hundreds), annual total patient care revenue ($hundreds), annual nursing salaries ($hundreds), annual facilities expenditures ($hundred), and where the home was located between non-rural and rural areas. The source of the data set of the nursing home information toward New Mexico in 1988 was part of the data analyzed by Howard L. Smith, Niell F. Piland, and Nancy Fisher. This was published in the Journal of Rural Health in winter 1992. This data set can be calculated in four different types of forms. It can be calculated in a health, consumer,...

...Statistics can be very helpful in providing interpretation of reality but also can be used to distort our understanding. Discuss some of the ways in which statistics can be used or misused in different Areas of Knowledge to assist and mislead us, and how we can determine whether to accept the statistical evidence that is present to us.
When you turn on the news, what do you hear? 1 in 10 people in South Africa have AIDS , Unemployment Reaches New High of 9.3 Percent , etc. Statistics is supposed to convey information in an objective and comprehendible way to the general population. However, this is usually not the case. Most of the present statistics use objectivity as a veil to hide the personal agendas behind the numbers.
Statistics are comprised of numbers and language, both these could be manipulated in a way to "bend" the truth.
In the mathematical sense, statistics are made from information gathered from a specific sample population that was asked a specific question, and then given an error margin. In order for the statistics to be valid, the sample population and error margins should be stated in the conclusion. Neglecting to mention any of these will cause the statistics to be misleading, for example, according to the U.S Bureau of Censes, the official unemployment rate in the U.S is 6% as of...

...
Simply use statistics as a tool. You will be given a data. (Next year you will not be given data, you will gather data yoruself).
1. Data: one of the variables is dependent and other dependent. Can be multiple. Then do regression analysis. ANOVA for overall significance and Regression equation. And write based on ANOVA there is a significance or not.
2. Some comments on correlation: volume vs. horse power etc.
3. Hypothesis test of one population. I assume that the mean is etc etc. Small paragraph analysis below the results of the test. ANOVA for small, large and medium size businesses for example.
Simply use statistics as a tool. You will be given a data. (Next year you will not be given data, you will gather data yoruself).
1. Data: one of the variables is dependent and other dependent. Can be multiple. Then do regression analysis. ANOVA for overall significance and Regression equation. And write based on ANOVA there is a significance or not.
2. Some comments on correlation: volume vs. horse power etc.
3. Hypothesis test of one population. I assume that the mean is etc etc. Small paragraph analysis below the results of the test. ANOVA for small, large and medium size businesses for example.
Simply use statistics as a tool. You will be given a data. (Next year you will not be...

...Definition:
Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments.
A statistician is someone who is particularly well-versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained experience through working in any of a wide number of fields.
Some consider statistics to be a mathematical body of science pertaining to the collection, analysis, interpretation or explanation, and presentation of data, while others consider it a branch of mathematics concerned with collecting and interpreting data. Because of its empirical roots and its focus on applications, statistics is usually considered to be a distinct mathematical science rather than a branch of mathematics. Much of statistics is non-mathematical: ensuring that data collection is undertaken in a way that allows valid conclusions to be drawn; coding and archiving of data so that information is retained
Statisticians improve the quality of data by coming up with a specific design of experiments and survey sampling. Statistics itself also provides tools for prediction and forecasting the use of...

...How to Lie with Statistics Summary
There are some people that rely heavily on the statistical information provided by the media, government, and other research groups in order to form opinions or come to a conclusion on a particular idea or product. However they fail to realize that a lot of the time the data is manipulated in such a way that leads them to believe something that is not actually the case. Statistics can lie in many ways the first way is by using a sample that has a bias. For instance, the data collected would only be of one particular group of people, but they would claim it was the population. Another way data is manipulated is through averages. The data will be presented as the average, but the type of average that is taken is not given. For example is it the arithmetical average, median, or mode that is being used to present the data. This can completely skew the data one way or another. Furthermore, when data is presented the presenter can lie by leaving out certain things that will usually go unnoticed by the reader. In addition, many people make a big deal about something that doesn’t matter when using statistics, which leads the reader to believe that whatever the made a big deal about actually is significant. There could be a difference that is so tiny that it...

...in decision making. These developments were so successful that after World War II many companies used similar techniques in
managerial decision making and planning.
The decision making task of modern management is more demanding and more important
than ever. Many organisations employ operations research or management science personnel or
consultants to apply the principles of scientiﬁc management to problems and decision making.
In this module we focus on a number of useful models and techniques that can be used in the
decision making process. Two important themes run through the study guide: data analysis and
decision making 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...

...References 15
Question 1
The sampling method that Mr. Kwok is using is Stratified Random Sampling Method. In this case study, Mr Kwok collected a random sample 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...

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