Chapter 10 Quantitative Data Analysis Approaches
DOI: 10.23912/978-1-910158-51-7-2786 | ISBN: PBK |
Published: September 2015 | Component type: chapter |
Published in: Research Methods for Business and Management 2nd edn | Parent DOI: 10.23912/978-1-910158-51-7-2735 |
Abstract
In order to understand data and present findings in an accurate way, researchers and managers need to develop an awareness of statistical analysis techniques. This chapter focuses on two sets of the most widely used statistical tools – exploring relationships and comparing groups. It also briefly explains the nature of Big Data. This chapter explores the data preparation approach, how to conduct preliminary (descriptive) analysis as well as introducing some of the main statistical techniques used in quantitative research in business management. The key issues that should be related back to your study question are a) how to prepare your data; b) how to conduct preliminary data analysis; c) what analyses are appropriate for comparing groups; d) what techniques are most appropriate for exploring relationships.
Sample content
Contributors
- Babek Taheri, Heriot-Watt University (Author)
- Catherine Porter, Heriot-Watt University (Author)
- Christian Konig, Heriot-Watt University (Author)
- Nikolaos Valantasis-Kanellos, Heriot-Watt University (Author)
For the source title:
- Kevin D O'Gorman, Heriot-Watt University (Editor) http://orcid.org/0000-0001-6239-6619
- Robert MacIntosh, Heriot-Watt University (Editor) http://orcid.org/0000-0001-7333-0201
Cite as
Taheri, Porter, Konig & Valantasis-Kanellos, 2015
Taheri, B., Porter, C., Konig, C. & Valantasis-Kanellos, N. (2015) "Chapter 10 Quantitative Data Analysis Approaches" In: O'Gorman, K.D. & MacIntosh, R. (ed) . Oxford: Goodfellow Publishers http://dx.doi.org/10.23912/978-1-910158-51-7-2786
References
Alexander, M., MacLaren, A., O'Gorman, K., & Taheri, B. (2012). "He just didn't seem to understand the banter": Bullying or simply establishing social cohesion? Tourism Management, 33(5), 1245-1255. https://doi.org/10.1016/j.tourman.2011.11.001
Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, Big Data, and Smart Assets: Ten tech-enabled business tends to watch: McKinsey.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences: Taylor & Francis.
Field, A. (2009). Discovering Statistics using SPSS (Vol. 3). London: SAGE Publications Ltd.
Hair, J. F. J., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). USA: Pearson.
Hair, J. F. J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). UK: Sage.
Han, J., Kamber, M., & Pei, J. (2011). Data Mining: Concepts and Techniques. USA: Morgan kaufmann.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277-319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Laney, D. (2012). The Importance of 'Big Data': A Definition. Gartner.
Lohr, S. (2012). The Age of Big Data. The New York Times. http://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html
Nair, R., & Narayanan, A. (2012). Getting results from big data: a capabilities-driven approach to the strategic use of unstructured information. http://www.strategyand.pwc.com/
Stevens, J. P. (2012). Applied Multivariate Statistics for the Social Sciences, Fifth Edition: Taylor & Francis.
Tabachnick, B. G., & Fidell, L. S. (2012). Using Multivariate Statistics. Boston: Pearson Education.
Taheri, B., Jafari, A., & O'Gorman, K. (2014). Keeping your audience: Presenting a visitor engagement scale. Tourism Management, 42, 321-329. https://doi.org/10.1016/j.tourman.2013.12.011
Zikopoulos, P., deRoos, D., Parasuraman, K., Deutsch, T., Giles, J., & Corrigan, D. (2012). Harness the Power of Big Data The IBM Big Data Platform: Mcgraw-hill.
Wisniewski, M. (2010). Quantitative Methods for Decision Makers, Essex: Pearson Education, Limited.