Important MCQs Multivariate Statistics 4

by

The post is about MCQs Multivariate Statistics with Answers. It covers topics of Eigen values, Eigen Vectors, Moderation, and Mediation, etc.

Multiple Choice Questions about Multivariate Analysis with Answers.

1. The combined effect of two variables on one another is known conceptually as ————–, and in statistical terms as ————-.

 
 
 
 

2. A moderator effect is where the size of the relationship one variable and another variable is:

 
 
 
 

3. If a researcher wants to determine the amount of variance in the original variables that is associated with a factor, they would use?

 
 
 
 

4. If the Eigenvalues is negative the direction is – – – – – – – -.

 
 
 
 

5. The percentage of variance criteria specifies that the number of factors to be extracted is determined by the cumulative percentage of variance extracted reaching a satisfactory level. This level should be at least – – – – – – – -.

 
 
 
 

6. If one of the Eigenvalues of $[A]_{n\times n}$ is zero, it implies – – – – – – -.

 
 
 
 

7. Which of the following is an orthogonal rotation in factor analysis – – – – – – – – -.

 
 
 
 

8. A – – – – – – – – mediates the relationship between the independent and dependent variables explaining the reason for such a relationship to exist:

 
 
 
 

9. The word Eigen means – – – – – – – -‘

 
 
 
 

10. Why is it a good idea to center your variable when conducting a moderation analysis?

 
 
 
 

11. The word “Eigen” originates from  – – – – – – -.

 
 
 
 

12. ———– analysis tests a hypothetical causal chain where one variable $X$ affects a second variable $M$ and, in turn, the variable affects a third variable $Y$:

 
 
 
 

13. Eigenvectors are by definition – – – – – – – – -.

 
 
 
 

14. Eigenvectors with distinct Eigenvalues are – – – – – – – – -.

 
 
 
 

15. Singular Matrices have Eigenvalues

 
 
 
 

16. Imagine we wanted to at the relationship between the number of hours spent practicing the guitar per week and skill level. If we had reason to believe that the strength or direction of the relationship between these variables would be affected by the level of enjoyment, what type of analysis should be conducted on these data?

 
 
 
 

17. ———— is a way to check whether that third variable influences the strength or direction of the relationship between an independent and dependent variable:

 
 
 
 

18. Moderation effect is also known as – – – – – – – -.

 
 
 
 

19. Which of the following are violations of as assumption underlying regression analysis – – –  – – – – – .

 
 
 
 

20. Eigenvalues may be equal to – – – – – – – – -.

 
 
 
 


Online MCQs Multivariate Statistics

  • The word “Eigen” originates from  ——-.
  • Eigenvectors are by definition ———.
  • Eigenvalues may be equal to ———.
  • Eigenvectors with distinct Eigenvalues are ———.
  • Singular Matrices have Eigenvalues
  • If the Eigenvalues are negative the direction is ——–.
  • If one of the Eigenvalues of $[A]_{n\times n}$ is zero, it implies ——-.
  • The word Eigen means ——–‘
  • Which of the following is an orthogonal rotation in factor analysis ———.
  • If a researcher wants to determine the amount of variance in the original variables that is associated with a factor, they would use?
  • Which of the following are violations of as assumption underlying regression analysis ——–.
  • The percentage of variance criteria specifies that the number of factors to be extracted is determined by the cumulative percentage of variance extracted reaching a satisfactory level. This level should be at least ———.
  • A moderator effect is where the size of the relationship between one variable and another variable is:
  • Moderation effect is also known as ——–.
  • The combined effect of two variables on one another is known conceptually as ———–, and in statistical terms as ———–.
  • Imagine we wanted to at the relationship between the number of hours spent practicing the guitar per week and skill level. If we had reason to believe that the strength or direction of the relationship between these variables would be affected by the level of enjoyment, what type of analysis should be conducted on these data?
  • ———– analysis tests a hypothetical causal chain where one variable $X$ affects a second variable $M$ and, in turn, the variable affects a third variable $Y$:
  • A ——– mediates the relationship between the independent and dependent variables explaining the reason for such a relationship to exist:
  • ———— is a way to check whether that third variable influences the strength or direction of the relationship between an independent and dependent variable:
  • Why is it a good idea to center your variable when conducting a moderation analysis?
MCQs Multivariate Statistics

Learn R Programming

Important Multivariate Quiz 3

by

Multivariate Analysis term includes all statistics for more than two variables analyzed simultaneously. The post is about Multivariate Quiz. Let us start with the Online Multivariate Quiz with Answers.

Please go to Important Multivariate Quiz 3 to view the test

An application of different statistical methods applied to the economic data used to find empirical relationships between economic data is called Econometrics. In other words, Econometrics is “the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference”.

Multivariate Quiz Questions

  • An empirically based hypothetical variable consisting of items that are strongly associated with each other and upon which individuals differ is known as what?
  • Identify the correct statement from the following
  • Look at the steps below. Is there anything else a researcher could do? The correlation matrix is produced → factors are then retained based on eigenvalues over 1 and theoretical considerations → then the rotated factor loadings (whatever their loading) are used to name factors.
  • Rotation usually involves __________ high correlations and _________ low ones.
  • The most common method of rotation is called
  • Variables are not always measured in the same units so using the correlation matrix in factor analysis is equivalent to standardizing the data so that they are comparable.
  • You cannot retain factors that have an eigenvalue value of less than 1 as only factors with an eigenvalue over 1 should be kept.
  • ——— was known for his seminal work on testing and measuring “Human Intelligence” by using “Factor Analysis” during World War I.
  • Factor analysis is a:
  • Assumptions to be fulfilled for running factor analysis:
  • Principle component analysis is one of the methods of:
  • Determination of a number of factors:
  • In factor analysis ———— is the amount of variance explained by a factor.
  • In factor analysis, there are two common rotation techniques:
  • It can be defined as the correlation coefficient between the variable and the factor.
  • Some steps for Conducting factor analysis are:
  • A technique for the study of interrelationships among variables, usually for data reduction and the discovery of underlying constructors or latent dimensions is known as:
  • To determine which variables relate to which factors, a researcher would use:
  • If a researcher wanted to determine which variables were associated with which factors they would look at:
  • If a researcher uses factor rotation in a factor analysis, what will be the likely outcome:
MCQs Multivariate Quiz itfeature.com
  • Partial Least Squares (PLS) Regression is an example of multivariate analysis (MVA).
  • Multivariate Multiple Regression is a method of modeling multiple dependent variables, with a single set of predictor variables.
  • Testing text and visual elements on a webpage together.
  • An example of multivariate data is Vital signs recorded for a newborn baby: This includes multiple variables such as heart rate, respiratory rate, blood pressure, and temperature.

Learn R Programing Language

Online MCQs Test Website for various Subjects

Design of Experiments Objective Questions 3

by

MCQs about the Design of Experiments Objective Questions for the preparation of PPSC, FPSC Lecturer Statistics job, and BS, M.Phil, Ph.D. Statistics Degree Programs. Let us start with the Design of Experiments Objective Questions quiz.

Please go to Design of Experiments Objective Questions 3 to view the test

Planning an experiment to obtain appropriate data and drawing inferences from the data concerning any problem under investigation is known as the design and analysis of the experiments.

Design of Experiments Objective Questions

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 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.

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.

Design of Experiments Objective Questions

  • Which one provides the estimate of experimental error in the design of the experiment
  • There are – – – – – – – – basic principles of sound statistical design.
  • If the experimental material is not homogenous and there is one source of variation in the experiment then we use
  • An experiment is performed in CRD with 3 replications to compare four treatments. Then, the total experimental units will be
  • An experiment is performed in CRD with 3 replications to compare four treatments, then what will be the degrees of freedom for error?
  • An experiment is performed in CRE with 3 replications to compare four treatments. The treatment sum of squares = 8. If the error sum of square = 12 then what will be the total sum of square?
  • An experiment is performed in CRD with 3 replications to compare four treatments. The treatment sum of squares = 9. If the error sum of squares = 12 then what will be the mean sum of squares for treatment?
  • What will be the F ratio if an experiment is performed in CRD with 3 replications to compare four treatments? The treatment mean sum of squares = 96, error mean sum of squares = 12.
  • Analysis of variance is a statistical method of comparing the – – – – – – – – of several populations.
  • To test the hypothesis about one population variance, the test statistic will be – – – – – – -.
  • Under one-way variability in environmental conditions, the appropriate design for experimenting will be – – – – – – – -.
  • The scientific method for the construction of a statistical layout plan for an experiment is – – – – – -?
  • Manova stands for
  • For a $7 \times 7$ Latin Square Design, there will be ___________ observations.
  • The experiment is performed on
  • The random process of assigning treatments to the experimental units can be done by
  • In systematic designs, the treatments are applied to the experimental units by some
  • Planning an experiment to obtain appropriate data and drawing inferences out of the data for any problem under investigation is known as ___________
  • One of the purposes of experimental design is to
  • What will be a degree of freedom (df) for column-wise blocking in $5 \times 5$ Latin Square Design?
https://itfeature.com

Online Design of Experiments Objective Questions

Learn R Language Frequently Asked Questions

Classification of Randomized Designs (2023)

by

Randomized designs are a type of experimental design where randomization process is used to assign the units (like people or objects) to different treatment groups. The randomization process helps to control for bias and ensures that any observed differences between the groups are likely due to the treatment itself, rather than some other factors.

Randomized Designs

In randomized designs, the treatments are applied randomly, therefore the conclusions drawn are supported by statistical tests. The classification of randomized designs for single-factor are:

Example: A market gardener wants to test three types of peas, $A$, $B$, and $C$, on his land. He divides a square plot into nine equal squares, three to be planted with each type of pea. The problem he then faces is which square to plant with which type.

Classification of Randomized Designs

One method is a Completely Randomized Design (CRD) which might,

123
CAC
BAA
BBC
Allocation of Different Types of Peas Randomly to plots

This would be all right if all the plots were equally desirable. If however, there were prevailing north wind so that the northernmost plots were exposed, he might decide to use, a Randomize Complete Block Design (RCBD).

Randomized Complete Block Design, where each of the types $A$, $B$, and $C$ is planted once in each west-east block.

123
ABC
ACB
CBA
Allocation of Different Types of Pease in each West-East Block

If the gardener also felt that the soil to the east was rather better than that to the west, he would use, a Latin Square Design (LSD).

A Latin Square design, where each type of pea is planted once in each row (west-east), and once in each column (north-south).

Block 1Block 2Block 3
ABC
BCA
CAB
Allocation of Different Types of Pease planted once in each row (West-East), and once in each column (North-South)

For Randomized Designs, Note that

  • Completely Randomized Design (CRD) is a statistical experimental design where the treatments are assigned completely at random so that each treatment unit has the same chance (equal chance) of receiving any one treatment.
  • In CRD any difference among experimental units receiving the same treatment is considered as an experimental error.
  • CRD is applicable only when the experimental material is homogeneous (eg., homogeneous soil conditions in the field).
  • Since soil is heterogeneous in the field, the CRD is not a preferable method in field experiments. Therefore, CRD generally applies to the lab experimental conditions, as in labs, the environmental conditions can be easily controlled.
  • The concept of “local control” is not used in CRD.
  • CRD is best suited for experiments with a small number of treatments.
Design of Experients

The best design for a study will depend on the specific research question and the factors that one needs to control for. By incorporating randomization, you can control for extraneous variables that might influence the outcome and improve the validity of the findings.

However, the choice of the randomized design depends on the specific research question(s) being asked. It is important to consider the strengths and weaknesses of each design before making a decision.

Learn Statistics

Learn about Poisson Regression in R Language