Null hypotheses and chi-squared tests may seem like relics of your college days, but you can’t afford to bury them if accurate organizational measurement is your objective. For corporate research to be of value, statistical rigor is vital, says marketing professor Geoff Lancaster in his new book Research Methods in Management (Elsevier, 2005). Lancaster provides a thorough grounding in data collection, classification, and analysis, taking the time to discuss in detail often-overlooked basics such as the differences between scientific and non-scientific research, data and information, primary and secondary sources, and observational and experimental methodologies. In particular, Lancaster has written a fine chapter on analysis, pointing out the dangers of misinterpreting research results and warning us that “ineffective data analysis can lead to a number of potentially disastrous outcomes with regard to tackling organizational and management problems.” He cites one study in which the researchers missed the effects of group processes on productivity. As a result, the company took the wrong steps to enhance productivity, concentrating on the physical environment rather than on workgroup design and management.
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