LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034
B.Sc. DEGREE EXAMINATION – STATISTICS
SIXTH SEMESTER – APRIL 2011
ST 6603/ST 6600 – DESIGN & ANALYSIS OF EXPERIMENTS
Date : 05-04-2011 Dept. No. Max. : 100 Marks
Time : 9:00 – 12:00
SECTION – A
Answer ALL the questions (10 X 2 = 20 Marks)
- State the assumptions used in a linear model.
- Distinguish between pair-wise and non-pair-wise contrasts.
- What do you mean by randomization in experimental designs?
- State the assumptions for ANOVA.
- What are the demerits of a completely randomized design?
- Give the layout of a 4 x 4 Latin Square Design.
- What is meant by a factorial experiment?
- What are the advantages of confounding?
- What is meant by incomplete block designs?
- When do we go for a BIBD?
SECTION – B
Answer any FIVE questions (5 x 8 = 40 Marks)
- In what way are contrasts helpful in the analysis of experimental data?
- Give the statistical analysis of a two-way classification.
- Derive the expression to measure the efficiency of RBD over CRD
- What is Latin Square Design? Carry out the analysis of LSD.
- Explain the least square method of estimating one missing observation in a LSD.
- Explain in detail the analysis of 22 factorial experiment.
- Give the analysis of 32 factorial experiment.
- Develop the intra-black analysis of a BIBD.
SECTION – C
Answer any TWO questions (2 x 20 = 40 Marks)
- a) Discuss clearly between one-way and two-way classifications of analysis of
variance.
- b) Describe in detail analysis of variance in one-way classification with suitable
examples.
- a) What is missing plot technique? Derive the formula for missing value when one
observation is missing in the case of LSD.
- b) Discuss briefly the advantages and disadvantages of a Latin Square Design.
- a) Distinguish between Complete and Partial Confounding.
- b) Give the Yates method of computing the factorial effects in a 23 factorial experiment.
- a) Explain a BIBD with suitable illustration.
- b) Develop the inter – block analysis of a BIBD stating the model, Hypothesis, ANOVA
and inference.
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