Soft Copy: Yes
Downloadable File: Yes
Course: Master of Business Administration
Q&A of MS-95 Solved Assignment 2017 - Research Methodology for Management Decisions
Q. A social scientist sampled 140 people and classified them according to income level and whether or not they played a state lottery in the last month. The sample information is reported below. Is it reasonable to conclude that playing the lottery is related to income level? Use the .05 significance level.
Low Middle High Total
Played 46 28 21 95
Did not play 14 12 19 45
Total 60 40 40 140
(a) What is this table called?
(b) State the null hypothesis and the alternate hypothesis.
(c) What is the decision rule?
(d) Determine the value of chi-square.
(e) Make a decision on the null hypothesis. Interpret the result.
Q. What is of more value to the corporate world –basic, fundamental, or applied research? Justify your reasoning!
Q. Distinguish between secondary and primary methods of data collection. Is it possible to use secondary data methods as substitutes of primary methods? Justify your answer with suitable illustrations.
Q. What is a systematic sample? How is it selected? What are the advantages and disadvantages of a systematic sample?
Q. Discuss the applications of rating scales in various functional areas of management.
Product Details: Mba MS-95 Solved Assignment 2017
Course: IGNOU MBA (Master of Business Administration)
Session: Jan - June 2017
Subject: Research Methodology for Management Decisions
Ignou Mba MS-95 Assignments - Old Sample Answers
Q. What is a. Regression Analysis?
Answer. Time series analysis is the term used to describe a set of statistical tools that are useful for identifying patterns of demand that repeat periodically—in other words, patterns that are driven by time. The other most widely used tool for demand forecasting is regression analysis. This statistical tool is useful when the analyst has reason to believe that some measurable factor other than time is affecting demand. Regression analysis begins with the identification of two categories of variables: dependent variables and independent variables....... Regression models are built using a data set of historical values. They are used to evaluate the relationship between independent and dependent variables in an existing data set and produce a mathematical framework that can be extrapolated to values of the independent variables not present in the data set..................... A diverse range of regression models exists, and the appropriate model to employ for a given task depends on the nature of the dependent variable being predicted. In some cases, an explicit value must be predicted—say, the total amount of revenue a new user will spend over the user’s lifetime.............. In other cases, the value predicted by the regression model is not numeric but categorical; following from the example above, if, instead of the total revenue a new user will spend over the user’s lifetime, a model was constructed to predict whether or not the user would ever contribute revenue, the model would be predicting for a categorical (in this case, binary) variable: revenue or no revenue............. Imagine you are a consultant working in a purchasing department whose input into business decision-making process is welcomed within the firm. The Purchasing Manager believes that by working more closely with suppliers, subsequent delivery performance will improve. His idea of working more closely means visiting suppliers on a regular basis to discuss business issues.........