Design and Analysis of Experiments (ISS Statistics Paper IV): Questions 1 - 8 of 36

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Question number: 1

» Design and Analysis of Experiments » Basic Principle of Experimental Design

Appeared in Year: 2013

Essay Question▾

Describe in Detail

For a PBIB design with parameters ʋ , b, r, k, λi , ni show that i=1mniλi=r(k1)

Explanation

A PBIB design with m associate classes based on the association scheme is an arrangement of ʋ treatments into b blocks such that

(i) Each block contains k distinct treatments (k < ʋ)

(ii) Each treatment occurs in r blocks

(iii) Any two treatments, which are ith associates occur… (130 more words) …

Question number: 2

» Design and Analysis of Experiments » Analysis and Layout of Completely Randomized Design

Appeared in Year: 2012

Essay Question▾

Describe in Detail

Discus symmetrical BIBD. For an SBIBD, under usual notations, show that

N = r(rλ)υ12

Explanation

Symmetrical BIBD:

A BIBD is said to be symmetric if b = υ and r = k.

υ, r, b, k and λ are called the parameters of the BIBD

υ= number of varities or treatments

b = number of blocks

r = number of replicates for each treatment… (384 more words) …

Question number: 3

» Design and Analysis of Experiments » Randomized Block and Latin Square Design

Appeared in Year: 2015

Essay Question▾

Describe in Detail

Discuss how you would proceed with the analysis if data on one plot is missing in a Latin Square design.

Explanation

To analysis the data of a Latin square design having missing values, we first estimate the missing value by minimizing the error mean square and the rest missing values by guess estimate which is generally the mean of all available values. The estimated value of x is obtain by to… (251 more words) …

Question number: 4

» Design and Analysis of Experiments » Analysis and Layout of Completely Randomized Design

Appeared in Year: 2011

Short Answer Question▾

Write in Short

Explain Randomized block design.

Question number: 5

» Design and Analysis of Experiments » Basic Principle of Experimental Design

Appeared in Year: 2015

Essay Question▾

Describe in Detail

Explain briefly the main principles of design of experiment and analogy in sample surveys with the corresponding concepts.

Explanation

The main principle of design of experiment is to study the sampling error. If these principles hold, the chance of getting a data set or a design which could be analyzed, with less doubt about structural nuisances, is higher as if the data was collected arbitrarily.

Principle 1: Fisher’s Principle… (379 more words) …

Question number: 6

» Design and Analysis of Experiments » Analysis of Variance for 1 Way and 2 Way Classifications

Appeared in Year: 2012

Essay Question▾

Describe in Detail

What is a 23 factorial experiment? Discuss a method to estimate all main effects and interaction effects considering replication size r. Also, write its ANOVA table.

Explanation

23Factorial experiment:

The 23factorial experiment is a two level factorial experiment design with three factors. Let us consider A, B, C as the three factors under study. Then This design tests three main effects (A, B and C) and three, two factorial effects (AB, BC, AC)… (1357 more words) …

Question number: 7

» Design and Analysis of Experiments » Need for Design of Experiments

Appeared in Year: 2010

Essay Question▾

Describe in Detail

Discuss the layout for 23 factorial experiment with suitable illustration, how would you carry out the analysis of such a design?

Explanation

Here we will have 3 factors each at two levels. Let A, B, C be three factors under study and let small letters a, b, and c represent the two levels of each of the corresponding factors. say,

( a0,a1), (b0,b… (912 more words) …

Question number: 8

» Design and Analysis of Experiments » Analysis of Covariance

Appeared in Year: 2009

Essay Question▾

Describe in Detail

What is the use of analysis of covariance? Give the general procedure of analysis of covariance for a RBD, stating the necessary assumptions.

Explanation

Analysis of Covariance (ANCOVA) : Extension of ANOVA gives way of statistically controlling the (linear) effect of variables one does not want to examine and the extraneous variables are called covariates, or control Variables. It allows removing covariates from the list of possible explanations of variance in the dependent variable.… (406 more words) …

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