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Statistics is the name of the subject. It is the general definition which deals with the collection, presentation and interpretation of data. On the other hand, statistic is a… test used to test a hypothesis. It is commonly applied to sample cases. A statistic is a description of some measure, such as your height, weight, or age. Such measures may be collected in large numbers to be analyzed statistically to determine some characteristic of a population. For example, the collection of a population's ages make up a data base that may be analyzed by statistical methods to determine the proportion of the population that will retire and start drawing pension funds during the next decade. (MORE)

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In Scientists

They use it to organize and collect data. When testings a hypothesis, statistics can be used to calculate the chances or probability of getting a result

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A statistic is a distinct, descriptive value that has been acquired by some method (measured, counted, etc.). Statistics is the subjective and objective manipulation of the va…lues acquired. A statistic is simply the count of something. Statistics (plural) is the count of something added to or compared to the count of something else. (MORE)

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In Statistics

I believe you asked for the relationship between "statistical significance" and hypothesis testing. In hypothesis testing, we state the null and alternative hypothesis, t…hen in the traditional method, we use a test statistic and a significance level, alpha, to decide whether to accept or reject the null hypothesis in favor of the alternative. If our test statistic falls in the reject area (critical region) of the sampling distribution, then we reject the null hypothesis. If not, we accept it. There is the second method, the p-value method, which is similar in that an alpha value has to be selected. Now, the term "statistical significant result", as used in statistics, means a result (mean value, proportion or variance) from a random sample was not likely to be produced by chance. When we reject the null hypothesis in favor of the alternative, we indicate our data supports an alternative hypothesis, so our result is "statistically significant." Let me use an example. Generally workers arrive at work a few minutes more or less than required. Our null hypothesis will be an average lateness of 5 minutes, and our alternative hypothesis will be greater than 5 minutes. Our data shows an average lateness of 12 minutes, and our test statistic, taking into account the variance and sample size, and our chosen alpha level, concludes that we reject the null hypothesis, so the 12 minute average is a significantly significant result because it supported rejection of the hypothesis. The problem is that significant, in common usage, means important or meaningful, not trivial or spurious. The sample used to calculate late time may have been not randomly chosen, more people come to work late in bad weather. The sample is to make inferences on the a general population, but there is no static population in this case, as a company hires and fires employees. So, since our data is flawed, so can our conclusions. Used as a technical term in statistics, statistical significance has a much more rigorous and restricted meaning, which can lead to confusion. See: http://en.wikipedia.org/wiki/Statistical_significance (MORE)

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secondary data source on which you rely on what other people have already published about the topic at hand.

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MaryLou Ross

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In Technology

Both the iPhone 5 and the 5c have 4 inch screens. The frame of the 5c is slightly larger than the the iPhone 5.

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In Education

Statistics can help you in your everyday life.

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In Science

For decades, biostatistics has played an integral role in modern medicine in everything from analyzing data to determining if a treatment will work to developing clinical tria…ls. The School of Global Public Health defines biostatistics as "the science of obtaining, analyzing and interpreting data in order to understand and improve human health." Virtually any medical research study uses biostatistics from beginning to end. "Statisticians help medical researchers design studies, decide what data to collect, analyze data from medical experiments, help interpret the results of the analyses, and collaborate in writing articles to describe the results of medical research." To make it even plainer: biostatistics helps researchers make sense of all the data collected to decide whether a treatment is working or to find factors that contribute to diseases. As such, it is important that statistics are used in medicine in order to justify the development and subsequent use of a particular drug or treatment; as well as identifying in the first place whether it is having the desired effect at all. At the heart of the use of statistics in medicine is the seemingly insurmountable problem that everybody is different. Not only in a psychological sense, but a physiological sense too. While human beings may share similar organs, tissues and chemical compounds; how they are bonded, how we are composed and the effects different drugs have on the individual can be radically different from one person to the next. Therefore, to measure the effectiveness of any form of medication, it is important to run trials where a wide variety of subjects are administered the drug. Firstly, this helps gage the effectiveness of the medicine when compared to, for example, a placebo. Subsequent statistical analysis can also give medical professionals and pharmaceutical companies the information they need to judge whether the medicine is an effective treatment for the majority of patients; and whether it is a cost-effective solution to a particular ailment. (MORE)

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In Uncategorized

The division of statistics are generally divided into two groups: inferential and descriptive. Inferential statistics require that a conclusion is drawn from data, based a…lmost solely on human inference. Descriptive statistics are numbers that describe a set of data. (MORE)

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In Definitions

when you have a hypothesis, you have to guess what will happen during your expierement before you start testing it. for example if you are doing a project on heredity then you… will guess, for example, kids/children inherit genes from their parents. (MORE)