DYNAMISM(E) - Biannual Student Magazine June-2017 | Page 9

#ISMEianWrites Quantitative Data Analysis for Beginners in Business Research Dr. SHAMPA NANDI, Professor–Marketing, ISME “The essence of Mathematics is not to make simple things complicated but to make complicated things simple”—S. Gudder At the initial stage of research, researchers in business or management area often face a dilemma; which is first—theories/research concepts, statistics or software like SPSS, Excel. To be a systematic and good researcher, a person should have basic research concepts, understand statistical techniques and its assumptions and finally make wise use of software. Most of the time all these go hand in hand and error or lack of understanding in one area often blocks the progress in the other part. This article is an attempt to discuss the basics of research emphasising quantitative analysis part of any business research. Topics like sample size, sampling method, data collection procedure and qualitative data analysis are not discussed here. Research in Business or Management area deals with the intangible latent concepts, attitudes and behavioural aspect, therefore most of these concepts are difficult to quantify. Suppose a re- searcher wants to measure the Servqual dimen- sions and its impact on customers (patients) sat- isfaction and customer loyalty. Except “Tangible” all the other dimensions of Servqual (Reliability, responsiveness, assurance and empathy) are in- tangible in nature. Therefore, a structured ques- tionnaire has to be prepared by the researcher to obtain the attitude of the customers on these Servqual dimension in a quantifiable manner. 9 Question arises about the reliability and validi- ty of the research instrument or questionnaire. Reliability is nothing but the consistency of the measurement instrument whereas validity meas- ures whether the instrument is measuring what the researcher intends to measure. It is advised to do a pilot testing to check the reliability of the questionnaire. Most commonly “Cronbach Alpha” test is used to measure the re- liability. If “Cronbach Alpha” value is more than 0.7 then it shows questionnaire is reliable. For va- lidity of the research instrument, different types of validity are measured. Mostly in business re- search content validity, concurrent validity, pre- dictive validity, convergent validity, nomological validity, and discriminant validity are considered. Unfortunately very common direct techniques are not available to measure validity. Subject experts can be consulted for questionnaire preparation to enhance content validity, Cronbach alpha also helps to measure the validity of the question- naire to a certain extent. Structural equation modelling technique is the most commonly used for measuring the validity of any model. As a be- ginner it is better to start with a proven set of measurement scale used by an earlier research- er in similar area (available in reputed journals) and then modify according to a current context. The next part is how to prepare any question in different types of scales- nominal, ordinal, inter- val or ratio scale. Most of the research method books cover the definitions of all the above men- tioned scale. The question often arises in the mind of the researcher—what is the significance of framing a question in each type of scale. Ques- tion can be framed in any types of scale depend- ing on the researcher’s objective as well as the techniques going to be used to analyse the data. Let’s take an example—Question about an em- DYNAMISM(E)