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ASSIGNMENT
| DRIVE | SUMMER 2014 |
| PROGRAM | MBADS / MBAN2 / MBAHCSN3 / MBAFLEX – (SEM 3)
PGDENMN /PGDFMN/ PGDHRMN / PGDHSMN / PGDIB / PGDISMN / PGDMMN / PGDOMN / PGDPMN /PGDROMN / PGDSCMN / PGDTQMN – (SEM 1) |
| SUBJECT CODE & NAME | MB0050 – RESEARCH METHODOLOGY |
| BK ID | B1700 |
| CREDITS | 4 |
| MARKS | 60 |
Note: Answer all questions. Kindly note that answers for 10 marks questions should be approximately of 400 words. Each question is followed by evaluation scheme.
1 How would you distinguish between a management decision problem and a management research problem? Do all decision problems require research? Explain and illustrate with examples.
Answer : Decision Problem and Research Problem
Drivers for problem formulation:
- Unaticipated change, basically in the environment of the
focal firm (suppliers,competitors, customers)
- Planned change (estimation, effects, outcome)
- Serendipity (random ideas or information)
Differetn Problem Levels:
1) Individual orientation, PSYCHOLOGY
2 How are research designs classified? What are the distinguishing features of each? Differentiate by giving appropriate examples.
Answer : The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data.
Action Research Design
3 Discuss with the help of examples the four key levels of measurement. What mathematical operations/statistical techniques are and are not permissible on data from each type of scale?
Answer : 4 Levels of Measurement
Nominal Scale
The nominal scale (also called dummy coding) simply places people, events, perceptions, etc. into categories based on some common trait. Some data are naturally suited to the nominal scale such as males vs. females, redheads vs. blondes vs. brunettes, and African American vs. Asian. The nominal scale forms the basis for such analyses as Analysis
4 Processing of data involves editing, coding, classifying and tabulating. Explain each of these steps by taking an appropriate example.
Answer : After collecting data, the method of converting raw data into meaningful statement; includes data processing, data analysis, and data interpretation and presentation.
Data reduction or processing mainly involves various manipulations necessary for preparing the data for analysis. The process (of manipulation) could be manual or electronic. It involves editing, categorizing the open-ended questions, coding, computerization and preparation of tables and diagrams.
5 Distinguish between the following:
- Null hypothesis and Alternative hypothesis
Answer : The Null Hypothesis
The null hypothesis reflects that there will be no observed effect for our experiment. In a mathematical formulation of the null hypothesis there will typically be an equal sign. This hypothesis is denoted by H0.
- One tailed and two tailed tests
Answer : A one- or two-tailed t-test is determined by whether the total area of a is placed in one tail or divided equally between the two tails. The one-tailed t-test is performed if the results are interesting only if they turn out in a particular direction. The two-tailed t-test is performed if the results would be interesting in either direction. The choice of a one- or two-tailed t-test effects the hypothesis testing procedure in a number of different ways.
- Type I and Type II error
Answer : Type I error
A type I error occurs when one rejects the null hypothesis when it is true. The probability of a type I error is the level of significance of the test of hypothesis, and is denoted by *alpha*. Usually a one-tailed test of hypothesis is is used when one talks
- One way and two way analysis of variance
Answer : The two-way analysis of variance is an extension to the one-way analysis of variance. There are two independent variables (hence the name two-way).
Assumptions
- The populations from which the samples were obtained must be normally or approximately normally distributed.
- The samples must be independent.
- The variances of the populations must be equal.
- Descriptive and inferential analysis of data
Answer : 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.
6 a. What is Chi-square test of goodness of fit? What precautions are necessary while applying this test? Point out its role in business decision making.
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
- Two research workers classified some people in income groups on the basis of sampling studies. Their results are as follow:
| Investigators | Income groups
|
Total
|
||
| Poor
|
Middle
|
Rich
|
||
| A | 160 | 30 | 10 | 200 |
| B | 140 | 120 | 40 | 300 |
| C | 300 | 150 | 50 | 500 |
Show that the sampling technique of atleast one research worker is defective.
Answer : Let us take the hypothesis that the sampling techniques adopted by research workers are similar(i.e. there is no difference between the techniques adopted by research workers).This being so, the expectations of A investigator classifying the people in
(I)Poor Income Group : =200 x 300 /500 =120
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