Common Errors in Statistics by Phillip I.Good, James W.Hardin

Common Errors in Statistics by Phillip I.Good, James W.Hardin

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Get Common Errors in Statistics by Phillip I.Good, James W.Hardin at Salaedu.com

Forex Trading – Foreign Exchange Course

You want to learn about Forex?

Foreign exchange, or forex, is the conversion of one country’s currency into another.
In a free economy, a country’s currency is valued according to the laws of supply and demand.
In other words, a currency’s value can be pegged to another country’s currency, such as the U.S. dollar, or even to a basket of currencies.
A country’s currency value may also be set by the country’s government.
However, most countries float their currencies freely against those of other countries, which keeps them in constant fluctuation.

A guide to choosing and using the right techniques High-speed computers and prepackaged statistical routines would seem to take much of the guesswork out of statistical analysis and lend its applications readily accessible to all. Yet, as Phillip Good and James Hardin persuasively argue, statistical software no more makes one a statistician than a scalpel makes one a surgeon. Choosing the proper technique and understanding the analytical context is of paramount importance to the proper application of statistics. The highly readable Common Errors in Statistics (and How to Avoid Them) provides both newly minted academics and professionals who use statistics in their work with a handy field guide to statistical problems and solutions. Good and Hardin begin their handbook by establishing a mathematically rigorous but readily accessible foundation for statistical procedures. They focus on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. A handy checklist is provided to summarize the necessary steps. Topics covered include: Creating a research plan Formulating a hypothesis Specifying sample size Checking assumptions Interpreting p-values and confidence intervals Building a model Data mining Bayes’ Theorem, the bootstrap, and many others Common Errors in Statistics (and How to Avoid Them) also contains reprints of classic articles from statistical literature to re-examine such bedrock subjects as linear regression, the analysis of variance, maximum likelihood, meta-analysis, and the bootstrap. With a final emphasis on finding solutions and on the great value of statistics when applied in the proper context, this book will prove eminently useful to students and professionals in the fields of research, industry, medicine, and government.

Get Common Errors in Statistics by Phillip I.Good, James W.Hardin at Salaedu.com