Statistics are important and powerful tools for conducting sound scientific research. Statistical methods can affect the validation of such research at almost every stage beginning with the design of the study through to the interpretation of the results and statements of the conclusions. To be valid, a study must have a testable hypothesis, a properly chosen statistical method to test that hypothesis with a suitable type I error rate, and a sufficient number of study subjects in order to achieve the degree of statistical power necessary for detecting a meaningful difference or effect. Descriptive statistics can help to summarize the data, check assumptions, and guide further analysis. While many statistical software packages are powerful tools for data analysis, applied researchers should understand the statistical basis of the procedures they use and avoid careless operation of such software.
Many topics are not included in this chapter, and aging researchers are collecting data with increasing levels of complexity, such as microarray and other highdimension biological data. We strongly suggest that the applied researchers seek assistance from statisticians when necessary. The basic concepts and considerations discussed in this chapter will be helpful for communication between applied researchers and statisticians.
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