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MS-95 Solved Assignment

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  • Version: 2017 July - Dec


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

Q&A of MS-95 Solved Assignment 2017 - Research Methodology for Management Decisions

Q. Discuss the points that should be kept in mind while defining a research problem. Briefly mention advantages of considering these points.

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Q. The secondary data are to be scrutinized before they are compiled from the source. How does one examine the reliability, suitability, accuracy and adequacy of secondary data?

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Q. Describe, in brief, the importance of editing, coding, classification, tabulation and presentation of data in the context of research study.

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Q.The production manager in a large undertaking randomly paid 10 visits to a work site in a month. The number of workers who reported late for duty were found to be 2,4,5,1,6,3,2,1,7, and 8 respectively. Using the Wilcoxon signed rank test, verify the claim of the production superintendent at 0.05 level of significance that on an average not more than 3 workers report late for duty

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Q. Discuss the various components of presentation skills. Your answer should include communication dimensions, presentation package, and use of audio-visual aids. Answer......

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Product Details: Mba MS-95 Solved Assignment 2017

Course: IGNOU MBA (Master of Business Administration)
Session: July - Dec 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.........


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