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MB0050—Research Methodology


Master of Business Administration- MBA Semester 1

MB0050—Research Methodology-4 Credits

(Book ID: B1700)

Assignment (60 Marks)

Note: Answer all questions (with 300 to 400 words each) must be written within 6-8 pages. Each Question carries 10 marks 6 X 10=60

Q1. Explain the process of problem identification with an example.

Answer. Problem identification’ is actually ‘seeing’ the problem before trying to solve it. In other words, it is the first strategy in solving a problem.
First, you have to realize and accept there IS a problem. Once you ‘identify’ the problem you can then observe and reflect what’s going on, gather information that relates and begin working on solutions.


Q2. Interview method involves a dialogue between the Interviewee and the Interviewer. Explain the interview method of data collection. What are the uses of this technique? What are the different types of interviews?

Answer. Interview Method of Data Collection  Interview is verbal questioning. In research, Lindzey Gardner has defined interview as “a two-person conversation, initiated by the interviewer for the specific purpose of obtaining research-relevant information and focused by him on the content specified by the research objectives of description and explanation”.

Characteristics of interview: Black and Champion have pointed out the following characteristics of an interview:
– Personal communication.
– Equal status: The status of the interviewer and the interviewee is equal.
– Instant response.

Q3. A study of different sampling methods is necessary because precision, accuracy, and efficiency of the sample results depend on the method employed for selecting the sample. Explain the different types of Probability and Non-Probability sampling designs.

Answer.  Probability Sampling

A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.


Q4. a. Differentiate between descriptive and inferential analysis of data.

b. Explain with examples various measures of Central Tendency.

Answer. A. Statistical procedures can be divided into two major categories: descriptive statistics and inferential statistics.

Descriptive Statistics

Descriptive statistics includes statistical procedures that we use to describe the population we are studying. The data could be collected from either a sample or a population, but the results help us organize and describe data. Descriptive statistics can only be used to describe the group that is being studying. That is, the results cannot be generalized to any larger group.

Descriptive statistics are useful and serviceable if you do not need to extend your results to any larger group.

3. Mode

The mode is the most frequent score in our data set. On a histogram it represents the highest bar in a bar chart or histogram. You can, therefore, sometimes consider the mode as being the most popular option.

Type Description Example Result
Mean Sum of values divided by no. of values (1+2+2+3+4+7+9)/7 4
Median Middle value separating the greater and lesser halves of a data set 1,2,2,3,4,7,9 3
Mode Most frequent value in a data set 1,2,2,3,4,7,9 2



Q5. The chi-square test is widely used in research. Discuss the various applications of chi-square test. Under what conditions is this test applicable?

Answer. Chi-square is a statistical test commonly used to compare observed data with data we would expect to obtain according to a specific hypothesis. For example, if, according to Mendel’s laws, you expected 10 of 20 offspring from a cross to be male and the actual observed number was 8 males, then you might want to know about the “goodness to fit” between the observed and expected. Were the deviations (differences between observed and expected) the result of chance, or were they due to other factors. How much deviation can occur before you,


Q6.What is analysis of variance? What are the assumptions of the technique? Give a few examples where this technique could be used.

Answer. Analysis of Variance (ANOVA) is a statistical method used to test differences between two or more means. It may seem odd that the technique is called “Analysis of Variance” rather than “Analysis of Means.” As you will see, the name is appropriate because inferences about means are made by analyzing variance.

ANOVA is used to test general rather than specific differences among means. This can be seen



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