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MS-95 Solved Assignment

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  • Version: 2019 Jan - June

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Soft Copy: Yes
Downloadable File: Yes
University: IGNOU
Course: Master of Business Administration
File: PDF/ZIP

Q&A of MS-95 Solved Assignment 2019 - Research Methodology for Management Decisions

Q. Describe the terms "Unit of analysis", "Characteristics of Interest" and "Decision Making Unit". Why is there confusion between the first two?

Answer......

Q. What is stratified sampling? How allocation of sample to different strata is done? Discuss the benefits of such an approach.

Answer......

Q. What is the objective of doing factor analysis? Explain the terms involved in Factor Analysis? How many factors one need to take.

Answer......

Q. A physical instructor claims that a particular exercise when done continuously for 7 days reduces body weight by 3.5 kg. Five overweight girls did the exercise for 7 days and their body weight were found as under:

Girls 1 2 3 4 5
Weight before exercise 70 72 75 71 78
Weight after exercise 66 70 72 66 72

Making use of the sign test, verify the claim at =0.05 that the exercise reduces weight by at least 3.5 kg.

Answer......

Q. Discuss the major elements of communication dimensions that are relevant to a presentation

Answer......

Product Details: Mba MS-95 Solved Assignment 2019

Course: IGNOU MBA (Master of Business Administration)
Session: Jan - June 2019
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 users 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.........


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