6-1 Discussion: Data Analysis and Planning
Hello,
The research question I am working on is: Will a new hatch model with new features such as more space and fuel-efficient into its hatch model help MSIL keep its leadership position in the Indian automobile market and recover its lost market share?
Our ability to collect and analyze quantitative and qualitative data will determine the answer qualities in this research. Quantitative research will permit us to define the relationship between fuel efficiency or car space and the number of automobiles sold at MSIL. To test the causality between the two events, we will maintain a level of control of the different variables that may influence the link between events and recruit respondents randomly. A survey will allow us to collect the quantitative data that will give us numerical data that can be used statistically and yield a result that can be generalized to the whole Indian population.
Qualitative research will help us to explain how a change in the car space affects MSIL sales. We will use individual interviews and focus group discussions to collect the data necessary to answer that question. After collecting the data, we will reduce them to their proper size. We can use the framework approach analysis to examine our findings with a pre-defined framework that reflects our objectives. This approach allows us to focus on particular answers and abandon the rest (Pope et al 2000). The thematic network analysis approach will help us code all our data, allowing new impressions to shape our interpretation in different and unexpected directions (Attride-Stirling, 2001).
Determining sample size is crucial for any research. The confidence interval or margin of error and the confidence level are the main statistics that we will use to calculate the sample size.
The confidence interval refers to the tolerable range that our estimate can lie. The confidence level determines how sure we want to be that the actual percentage falls within our selected confidence interval. Since we are using a sample and not asking every customer individually, we are making an estimate of the real value, and we can never be 100% confident. In common, a level of confidence of 95% is used, which means that there is a 5% chance that the actual percentage will not lie between the confidence interval selected (Sekaran & Bougie, 2016)
We will then stratify the sample because the individuals in the Indian population lives in the urban and rural area. Stratifying the sample helps us calculate the number of participants from each group proportionally to the total population. For instance, a population of 100 people lives in two cities, with 40% in city A and 60% in city B. If we have a required sample size of 70, in order to stratify our sample, we need to calculate 40% of 70. Number of people from city A in sample = 70 * 0.4 = 28 people. Number of people from city B in sample = 70 * 0.6 =