BOX-COX TRANSFORMATION APPROACH FOR DATA NORMALIZATION: A STUDY OF NEW PRODUCT DEVELOPMENT IN MANUFACTURING SECTOR OF PAKISTAN
Fozia Malik (),
Ph.D AjmalWaheed Khan () and
Muhammad Tahir Ali Shah ()
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Fozia Malik: Ph.D Scholar, Quaid-i-Azam School of Management Sciences Quaid-i-Azam University Islamabad
Ph.D AjmalWaheed Khan: Professor, Quaid-i-Azam School of Management Sciences Quaid-i-Azam University Islamabad
Muhammad Tahir Ali Shah: AllamaIqbal Open University Islamabad
IBT Journal of Business Studies (JBS), 2018, vol. 14, issue 1, 110-119
Abstract:
The aim of this paper is the application of BoxCox transformation approach for data normalization.It is mostly noticed that in social science research discipline the data is not normally distributed which can cause various problems for researchers.These problems are related to decisions which statistical tools should apply in case of nonnormality of data.A data set using two independent variables i internal resources, ii external resources, one mediating variable which is new product development process and one dependent variable namely new product success from manufacturing sector of Pakistan is utilized to analyze normality of data through the ShapiroWilk statistics.When it was analyzed that data is not normal than boxcox transformation approach was employed.It was noticed that applyingafter boxcox transformation data was normal which can be utilized for further statisticalanalysis.Therefore, this paper contributes in suggesting statistical technique, for example, BoxCox Transformation approach Box & Cox, 1964 can be used for normalizing data.Theresearch scholars can gain insight from this research regarding the procedure of BoxCoxTransformation approach.
Keywords: Box-Cox Transformation approach; Data Normalization; Shapiro-Wilk Test; New Product Development; Manufacturing Sector (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:aib:ibtjbs:v:14:y:2018:i:1:p:110-119
DOI: 10.46745/ilma.ibtjbs.2018.141.9
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