Attempt all the problems.
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.
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
Dependent Variable: rating
* The mean difference is significant at the .05 level.
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.