Kolmogorov-Smirnov test or Shapiro-Wilk goodness of fit test may be applied rather than making assumptions. Some of the other prerequisites of parametric tests are that samples have the same variance i. A one-tailed test calculates the possibility of deviation from the null hypothesis in a specific direction, whereas a two-tailed test calculates the possibility of deviation from the null hypothesis in either direction. When Intervention A is compared with Intervention B in a clinical trail, the null hypothesis assumes there is no difference between the two interventions.
Deviation from this hypothesis can occur in favor of either intervention in a two-tailed test but in a one-tailed test it is presumed that only one intervention can show superiority over the other. Although for a given data set, a one-tailed test will return a smaller p value than a two-tailed test, the latter is usually preferred unless there is a watertight case for one-tailed testing.
It is obvious that we cannot refer to all statistical tests in one editorial. However, the schemes outlined will cover the hypothesis testing demands of the majority of observational as well as interventional studies. Finally one must remember that, there is no substitute to actually working hands-on with dummy or real data sets, and to seek the advice of a statistician, in order to learn the nuances of statistical hypothesis testing.
SPSS for Applied Sciences - Basic Statistical Testing
National Center for Biotechnology Information , U. Journal List Indian J Ophthalmol v. Indian J Ophthalmol. Barun K Nayak and Avijit Hazra 1. Barun K Nayak P.
- SPSS for Applied Sciences: Basic Statistical Testing.. Clouston and Hall Booksellers.
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Author information Copyright and License information Disclaimer. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article has been cited by other articles in PMC. Open in a separate window. Figure 1. Figure 2.
Figure 3. Tests to address the question: Is there an association between variables?
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Figure 4. References 1. Research methodology simplified: Every clinician a researcher. New Delhi: Jaypee Brothers; Hypothesis testing and choice of statistical tests; pp. Petrie A, Sabin C, editors. This book offers a quick and basic guide to using SPSS and provides a general approach to solving problems using statistical tests.
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It is both comprehensive in terms of the tests covered and the applied settings it refers to, and yet is short and easy to understand. Whether you are a beginner or an intermediate level test user, this book will help you to analyse different types of data in applied settings.
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It will also give you the confidence to use other statistical software and to extend your expertise to more specific scientific settings as required. Instead, he provides a very practical, easy and speedy introduction to data analysis, offering examples from a range of scenarios from applied science, handling both continuous and rough-hewn data sets. Examples are given from agriculture, arboriculture, biology, computer science, ecology, engineering, farming and farm management, hydrology, medicine, ophthalmology, pharmacology, physiotherapy, spectroscopy, sports science, audiology and epidemiology.
SPSS software can read and write data from other statistical packages, databases, and spreadsheets. These headings enable the user to characterize the data. In the field of psychology, techniques such as crosstabulation, t-test , chi square test , etc. In this case, the split file option will help them get the result of three regions separately so that they can interpret and compare the literacy rate of the three regions.
SPSS software has a technique called missing value analysis , and this technique helps in making better decisions about the data.