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problem1) Discuss the various primary measurement scales. What type of statistical technique could be applied to each of the different measurement scales?

problem2) Differentiate Comparative and Non comparative scales. Discuss the use of each of these type of scaling techniques.

problem3)a) Why is sampling necessary?

b) Differentiate simple random sampling and stratified sampling.

problem4) prepare short note on the following:

a) Type I and Type II error

b) Classify the different observation techniques

c) Aspects to be kept in mind while preparing research report.

d) use of hypothesis testing for data analysis.


Case Study

The number of students completing MBA has increased exponentially from under 5000 in the 60’s to over 1,00,000 by the year 2000. One of the aspects which is agitating the minds of these students is on deciding on the area of specialization which they should adopt. To study the same four variables were considered: Previous work experience affects the choice (X1), Placement of a senior affects the choice (X2), Experience with the courses and the professors in the first year affects the choice (X3) and future job prospects affects the choice (X4). Data was collected on the above four variables from randomly chosen 69 participants and the analysis of the results are given below.Data for each variable was collected using a five point scale.

An analysis of variance technique was used to analyse the data which is given below:

                             Sum of Squares         df          Mean Square       F          Sig.
Between Groups      70.214                    3            23.405           21.591    .000
Within Groups          294.841                 272      1.084          
Total                       365.054                 275               
Test of Homogeneity of Variances
Levene Statistic    df1    df2    Sig.
7.004                    3    272    .000

Multiple Comparisons

Dependent Variable: rating
Tukey HSD

1644_Multiple comparison.jpg

* The mean difference is significant at the .05 level.

987_Rating factor.jpg

Case problems:

problem1) prepare null and alternative hypothesis for the above problem.

problem2) Interpret the Anova output and its post hoc analysis.

problem3) Do you think ANOVA was the suitable test to understand the above problem? If not why and what could have been done.

Operation Research, Management Studies

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