Important MCQs Design of Experiments

This test contains MCQs Design of Experiments (DOE). Click the links from the MCQS Design of Experiments list to start with the quiz. All the MCQs Designs of Experiments are from topics of Basic principles of Design of Experiments, concept of Randomization, Replication, types of Designs, Experimental Unit and Error, CRD, CRBD, LSD, Greco LSD, Factorial design and experiments, Response surface design, and balanced incomplete block designs. etc.

Online MCQs Design of Experiments

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An experiment deliberately imposes a treatment on a group of objects or subjects to observe the response. The experimental unit is the basic entity or unit on which the experiment is performed. It is an object to which the treatment is applied and the variable under investigation is measured and analyzed.

Single-Factor Design: In a single-factor experiment only a single factor varies while all others are kept constant. The CRD, RCBD, and LSD are examples of single-factor designs.

Multi-Factor Design: Multi-factor designs are also known as factorial experiments. When several factors are investigated simultaneously in a single experiment, such experiments are known as factorial experiments.

Systematic Designs: In systematic designs treatments are applied to the experimental units by some systematic pattern, i.e., by the choice of the experimenter. For example, the experimenter wishes to test three treatments and he decides to have four repetitions of each treatment.

Online MCQs Design of Experiments

Randomized Designs: In randomized designs, as the treatments are applied randomly, therefore the conclusions drawn are supported by statistical tests. In this way, inferences are applicable in a wider range and the random process minimizes the systematic error. The analysis of variance techniques is also suitable for randomized designs only.

The purpose of the Design of Experiments is:

  • Get maximum information for minimum expenditure in the minimum possible time.
  • Helps to reduce the experimental error.
  • To ignore spurious effects, if any.
  • To evaluate and examine the outcomes critically and logically.
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Important Design of Experiments Quiz 2

The post contains MCQs on the Design of Experiments Quiz (DOE). Most of the MCQs on the Design of Experiments Quiz are from factorial Experiments. Let us start with Online MCQs on the Design of Experiments Quiz.

Multiple Choice Questions about the Design of Experiments for preparation of examinations related to PPSC, FPSC, NTS, and Statistics job- and education-related examinations

1. In a randomized complete block design, the block should be constructed so that

 
 
 
 

2. The parameter $\lambda$ for a balanced incomplete block design with $a=4, b=4, k=3, r=3$ as usual notation is

 
 
 
 

3. When all pairs of treatments are compared with approximately the same precision, even though the differences among blocks may be large, called

 
 
 
 

4. If ABC is confounded in replicate I,
AB is confounded in replicated II,
BC is confounded in replicate III,
then the design technique is called

 
 
 
 

5. When a factorial experiment is performed in fractional replication, the two factorial effects that are represented by the same comparisons are called

 
 
 
 

6. In $3^k$ factorial design with $n$ replicates in the experiment, the $df$ of error are

 
 
 
 

7. When a number of confounded arrangements for factorial designs are made in Latin Squares, the designs are called

 
 
 
 

8. The designs in which the number of treatments must be an exact square, the size of a block is the square root of this form separate replications are called

 
 
 
 

9. For a Latin Square design

 
 
 
 

10. An experiment was designed to investigate the effect of the amount of water and seed variety on the subsequent growth of plants. Each plant was potted in a clay plot, and a measured amount of water was given weekly. The height of the plant at the end of the experiment was measured. Which of the following is not correct?

 
 
 
 

11. Which of the following is NOT CORRECT about a randomized complete block experiment?

 
 
 
 

12. The number of aliases of two-factor interactions in a $2^6$-factorial experiment (1/4 replicate) would be

 
 
 
 

13. A design with $v$ treatment labels, each occurring $r$ times, and with $bk$ experimental units grouped into $b=v$ blocks of size $k<v$ in such a way that the units within a block are alike and units in different blocks are substantially different is

 
 
 
 

14. For a two-factor factorial design, if there are ‘$a$’ levels of Factor-A and ‘$b$’ levels of Factor-B, then $df$ of interaction are:

 
 
 
 

15. An experiment was conducted where you analyzed the results of the plant growth experiment after you manipulated the amount of water and seed variety. Which of the following is correct?

 
 
 
 

16. In a factorial experiment, if $r$ is the number of replicates then each factorial effect has the same variance, that is

 
 
 
 

17. In a $2^3$ factorial experiment with partial confounding in three replications of 6 blocks, the error degrees of freedom would be

 
 
 
 

18. An important relationship between the coefficient of determination $R^2$ and the F-ratio used in ANOVA is

 
 
 
 

19. The models in which the levels of treatment factors are specifically chosen are known as

 
 
 
 

20. Let ADE and BCE be two effects confounded in blocks. Then generalized interaction is

 
 
 
 


Design of experiments (DOE) is a systematic method used to plan, conduct, analyze, and interpret controlled tests to study the relationship between factors and outcomes. Design of Experiment is a powerful tool used in various fields, including science, engineering, and business, to gain insights and optimize processes.

Design of Experiments Quiz

Design of Experiments Quiz

  • The parameter $\lambda$ for a balanced incomplete block design with $a=4, b=4, k=3, r=3$ as usual notation is
  • For a two-factor factorial design, if there are ‘$a$’ levels of Factor-A and ‘$b$’ levels of Factor-B, then $df$ of interaction are:
  • In $3^k$ factorial design with $n$ replicates in the experiment, the $df$ of error are
  • Let ADE and BCE be two effects confounded in blocks. Then generalized interaction is
  • If ABC is confounded in replicate I, AB is confounded in replicated II, BC is confounded in replicate III, then the design technique is called
  • An important relationship between the coefficient of determination $R^2$ and the F-ratio used in ANOVA is
  • In a randomized complete block design, the block should be constructed so that
  • For a Latin Square design
  • In a factorial experiment, if $r$ is the number of replicates then each factorial effect has the same variance, that is
  • When all pairs of treatments are compared with approximately the same precision, even though the differences among blocks may be large, called
  • In a $2^3$ factorial experiment with partial confounding in three replications of 6 blocks, the error degrees of freedom would be
  • When a factorial experiment is performed in fractional replication, the two factorial effects that are represented by the same comparisons are called
  • When a number of confounded arrangements for factorial designs are made in Latin Squares, the designs are called
  • The number of aliases of two-factor interactions in a $2^6$-factorial experiment (1/4 replicate) would be
  • The designs in which the number of treatments must be an exact square, the size of a block is the square root of this form, and separate replications are called
  • A design with $v$ treatment labels, each occurring $r$ times, and with $bk$ experimental units grouped into $b=v$ blocks of size $k<v$ in such a way that the units within a block are alike and units in different blocks are substantially different is
  • An experiment was designed to investigate the effect of the amount of water and seed variety on the subsequent growth of plants. Each plant was potted in a clay plot, and a measured amount of water was given weekly. The height of the plant at the end of the experiment was measured. Which of the following is not correct?
  • The models in which the levels of treatment factors are specifically chosen are known as
  • Which of the following is NOT CORRECT about a randomized complete block experiment?
  • An experiment was conducted where you analyzed the results of the plant growth experiment after you manipulated the amount of water and seed variety. Which of the following is correct?
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Best MCQs Random Variables Quizzes

The following are online quizzes containing MCQs Random variables. Start any of the online quizzes/exams/tests by clicking the links below.

MCQs Random Variables Quizzes

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A Random Variable (random quantity or stochastic variable) is a set of possible values from a random experiment. The domain of a random variable is called sample space. For example, in the case of a coin toss experiment, there are only two possible outcomes, namely heads or tails. A random variable can be either discrete or continuous. The discrete random variable takes only certain values such as 1, 2, 3, etc., and a continuous random variable can take any value within a range such as the height of persons.

MCQs Random Variables

By using random variables, one can use the tools of probability and statistics to analyze the outcomes of the experiment. One can calculate such as the probability of getting a certain result, the average outcome, or how spread out the results are.

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Wilcoxon Signed Rank Test Made Easy

The Wilcoxon Signed Rank test assumes that the population of interest is both continuous and symmetric (not necessarily normal). Since the mean and median are the same (for symmetrical distribution), the hypothesis tests on the median are the same as the hypothesis test on the mean.

The Wilcoxon test is performed by ranking the non-zero deviations in order of increasing magnitude (that is, the smallest non-zero deviation has a rank of 1 and the largest deviation has a rank of $n$). The ranks of the deviations with positive and negative values are summed.

These sums are used to determine whether or not the deviations are significantly different from zero. Wilcoxon Signed Rank Test is an alternative to the Paired Sample t-test.

One-Tailed Test

$H_0: \mu = \mu_0\quad $ vs $\quad H_1: \mu < \mu_0$

Test Statistics: $T^-$: an absolute value of the sum of the negative ranks

Two-tailed Test

$H_0: \mu = \mu_0 \quad$ vs $\quad H_1:\mu \ne \mu_0$

Test Statistics: $min(T^+, T^-)$

Wilcoxon Signed Ranked Test

Because the underlying population is assumed to be continuous, ties are theoretically impossible, however, in practice ties can exist, especially if the data has only a couple of significant digits.

Two or more deviations having the same magnitude are all given the same average rank. The deviations of zero are theoretically impossible but practically possible. Any deviations of exactly zero are simply thrown out and the value of $n$ is reduced accordingly.

Single Sample Wilcoxon Signed Rank Test

Wilcoxon Signed Rank Test

The Wilcoxon Signed Rank Test is important for researchers as it fills a critical gap in statistical analysis.

  • Non-normal data: Most of the statistical tests, like the dependent samples t-test, assume that the data follows a normal distribution (bell curve). The Wilcoxon Signed Rank Test supersede the assumption of normality, making it ideal for analyzing data that is skewed, ranked, or ordinal (like survey responses on a Likert scale Questions).
  • Robust against outliers: Outliers (very large or small observations in the data) can significantly skew the results of some statistical tests. The Wilcoxon Signed Rank Test focuses on the ranks of the differences, making it less sensitive to extreme values (outliers) in the data compared to tests that rely on raw numbers.
  • Focuses on changes within subjects: The Wilcoxon Signed Rank Test is designed for paired data (dependent samples), to look at the same subjects before and after situation (like a treatment) or under two different conditions.

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