IAD PROJECT: GUIDELINES

(Courtesy: Prof. K Ramakrishnan) 

Timeline for selecting database:    31 Oct 2009, 5pm

Timeline for submission of report:  30 Nov 2009, 5pm

No report will be accepted after 5pm on 30 Nov 2009

Date for presentation:                   To be decided 

The project carries 20 percentage points with the following breakup:

Meeting the timeline for selection of database:   1 point

Meeting the timeline for submission of report :    1 point

Evaluation of Report                                    :   8 points

Presentation of report (individually assessed) : 10 points

 

1.      Objectives:

This project work is intended to enable you to get some practice in gathering, organizing and analyzing data. In doing so, you are expected to illustrate your grasp of the concepts learnt in the IAD course. Additionally, you will also strengthen your communication skills by presenting your work as meaningful report.  The project work will be carried out by groups of four.  While every group has to show, through the report, their understanding of a minimum of FOUR concepts, the more concepts you illustrate, the more credit you get. You need not collect data through any field work but can depend on secondary data. 

Groups:  

a. Aravind, Sujith, Johncy, Jayan

b. Hasil, Thomas, Ashok, Nimisha

c. Srihari, Natasha, Vinita, Annada

d. Neethu, Kanimozhi, Karthika, Ansu

e. Kiran, Shruthi, Aneesh, Rahul

2.      An Example.

For example, let us take the case of analysis of the information of a sample of SMEs in India. You can have 30 cases or observations - each firm is a case or observation.  Your database would consist of the values for the following ‘variables’ or ‘attributes’ of each firm.

       a. Sales               b. Number of products in their product line.

       c. Net Profits        d. Debt/Equity Ratio      e. Number of employees    

       f. Employee remuneration as percent of sales.    

       g. In which state or UT of India, the mill is located?  (Example of a qualitative attribute)

 Obviously, information on items (a) to (f) would have to be for the same specific year for all firms.

There can be many more such ‘variables’ (or attributes) the ‘values’ for which, for each company can be readily obtained or computed.  (What are the possible sources for data?). It is not necessary to confine yourself to data pertaining to business entities alone. One creative student did the project with 30 different cross word puzzles. Think of the “attributes” of each cross word puzzle which can be collected and statistical analysis can be done. (e.g. number of words in the puzzle; number of anagrams;  Can you think of any qualitative  attribute?)

3.      Example continued: Analysis/Organization:

Once you collect the data, your first task will be to tabulate the information appropriately (choosing class intervals judiciously).  For example: the distribution of the 50 companies by the  variable Debt/Equity ratio may be (in skeleton form) as below.

Debt/Equity Ratio                                 Firms with that ratio   

                                                                  No.            Percent

      Less than 1.0                                               -----               -----

      GE 1.0 but LT 2.0                                         -----               -----            

      GE 2.0 but LT 3.0                                         -----               ----- 

      GE 3.0                                                         -----               -----

You can have two-way tables; say a) by D/E Ratio and NP/ sales or b) by sales and   employee remuneration as % of sales. The above information can also be presented through charts.  Computation of summary measures such as mean, s.d. and median etc., will lead to some inferences.

4. Example continued

You can also illustrate concepts of probability (joint, conditional etc.) using the same information (e.g.: What is the probability that a company will have a D/E ratio between 1 and 2? What is the probability that the company’s NP/Sales will be a certain value given that its D/E ratio is some value?).  Assuming 30 cases as a large population you can calculate binomial probabilities of say, coming up with 2 companies having NP/Sales ratio of  a specific value – say, 0.08 or 8% - if 5 companies are chosen at random.  Thus a variety of concepts which are covered in the IAD course can be illustrated with just one set of data you have collected.

5.   Research questions 

Ideally the data collection effort should depend on some purposive questions to be formulated first. However, this exercise is intended to familiarize you with methods of organizing data and applying statistical concepts to be used and hence the emphasis is not so much on the research questions. But, the data collected and organized can also be used to gain some insights on the concepts to be learnt in the next term course on Integrated Cases and Projects. 

6. Guidelines for collecting data:

a.       You must collect data for at least 4 ‘variables’ or attributes.  For each variable you must have at least 30 observations or cases.  Of the four ‘attributes’ at least one must be qualitative and at least two must be quantifiable.

b.       The database you use must be enclosed in original, if possible.  If not a list of the sources must be enclosed.

c.       While you may use the concepts illustrated in this note, for your project, they alone will not give you full credit. Think of other concepts that you can illustrate.

d.       Attempt some meaningful inferences which are free from statistical jargon but can be understood by ordinary citizens.

7.      Potential Data Sources: (you can use other similar sources too)

1.      Advertisements for jobs in business magazines and newspapers.

2.      Advertisements for products in a business periodical.

3.      Questions to the counsellor in a women’s magazine. (Each question is a case)

4.      Television commercials.

5.      Collection of books in a home library.

6.      Consumption of soft drinks by 30 ASB students during the past week.

Many other such data sets can be identified by you.  Think carefully about what “attributes” or “variables” and their “values” you can use to create the data set.