Multivariate Statistics

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.

The quiz contains Multivariate related multiple choice questions with answers.

1. In factor analysis, there are two common rotation techniques:

 Obligue rotation, varimax rotation

 Orthogonal rotation

 Varimax rotation

 Orthogonal rotation, obligue rotation

2. 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:

 Discriminant analysis

 Canonical correlation analysis

 Multiple regression

 Factor analysis

3. Identify the correct statement from the following

 In extracting factors we want to account for as little variance as possible while keeping the number of factors extracted as small as possible

 In extracting factors we want to account for as much variance as possible while keeping the number of factors extracted as large as possible

 In extracting factors we want to account for as much variance as possible while keeping the number of factors extracted as small as possible

 In extracting factors we want to account for as little variance as possible while keeping the number of factors extracted as large as possible.

4. To determine which variables relate to which factors, a researcher would use:

 Beta coefficients

 Eigenvalues

 Factor loadings

 Communalilities

5. ——— was known for his seminal work on testing and measuring “Human Intelligence” by using “Factor Analysis” during World War I.

 Charles Darwin

 Charles Edward Spearman

 William Whewell

 Lord Kelvin

6. Look at the steps below. Is there anything else a researcher could d0?

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.

 Exploration of the scree plot when retaining factors

 Try to account for approximately 75% of the variance when retaining factors

 Look at items with loadings greater that 0.40 when naming factors

 All of the above

7. If a researcher wanted to determine which variables were associated with which factors they would look at:

 Factors loading

 Factor scores

 Factors

 Factor associations

8. In factor analysis ———— is the amount of variance explained by a factor.

 Reduction of variables

 Screeplot

 Eigenvalue

 Grouping of factors

9. It can be defined as the correlation coefficient between the variable and the factor.

 Factor analysis

 Communality

 Multivariate

 Factor loading

10. Principle component analysis is one of the methods of:

 Linear Combination

 Matrix

 Multivariate Analysis

 Factor Analysis

11. An empirically based hypothetical variable consisting of items that are strongly associated with each other and upon which individuals differ is known as what?

 A factor

 Factor analysis

 Rotation

 A factor loading

12. Some steps for Conducting factor analysis are:

 All of the Options

 Testing the assumptions, Construction of correlation matrix

 Method of factor analysis, determination of number of factor analysis

 Rotation of factors, interpretation of factors

13. Assumptions to be fulfilled for running factor analysis:

 Normality of the data set

 No outliers in the data set

 All of the Options

 Adequate sample size

14. Determination of a number of factors:

 Kaiser guttmann criterion, Screeplot

 Eigenvalues, Kaiser guttmann criterion, and Screeplot

 Screeplot, Eigenvalues

 Eigenvalues

15. Rotation usually involves _____ high correlations and _____ low ones.

 Maximizing, Minimizing

 Omitting, Plotting

 Minimizing, Maximizing

 Plotting, Omitting

16. The most common method of rotation is called

 Data reduction

 Direct oblimin

 Varimax

 Vector

17. 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.

 True

 False

18. If a researcher uses factor rotation in a factor analysis, what will be the likely outcome:

 The pattern of loading stays the same

 The pattern of loading stays changes

 The pattern of loadings changes and the total variance explained by the factors remains the same

 The pattern of loading stays the same and the total variance explained

19. You cannot retain factors that have an eigenvalue value of less than 1 as only factors with an eigenvalue over 1 should be kept.

 False

 True

20. Factor analysis is a:

 Variable reduction technique

 Correlation of variables

 Grouping of many variables

 Grouping of some variables

 Loading …

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:

• 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.

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Online MCQs Test Website for various Subjects

The post is about the MCQs Multivariate Analysis test. It includes a Variance-Covariance matrix, Principal Component Analysis, Factor Analysis, Factor Loading, etc. Let us start with the Online MCQs Multivariate Quiz.

Please go to Important Online MCQs Multivariate 2 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”.

Online MCQs Multivariate

• In multivariate analysis Var-Cov matrix is
• In the relation $\Sigma = V^{1/2} \rho ^{1/2} V^{1/2}$, the $V^{1/2} is called
• If $X \sim N (\mu, \Sigma)$ then $(X-\mu)’ \Sigma^{-1} (X-\mu)$ is distributed as
• In multivariate analysis, $n(\overline{x} – \mu)’ S^{-1} (\overline{x} – \mu)$ is called
• In multivariate analysis the distribution of $\overline{X}$ is
• In multivariate analysis the distribution of the sample covariance matrix is
• In factor analysis the reliable variance
• In principal component analysis (PCA) the first component contains
• In principal component analysis, the components are
• In PCA, when the variables are measured in different units then PCs extracted on the basis of
• The goal of multiple regression is to
• A multivariate statistic that allows you to investigate the relationship between two sets of variables is
• Correlational multivariate analysis includes
• An advantage of using an experimental multivariate design over separate univariate designs is that using the multivariate analysis – – – – – – -.
• A multivariate statistic that allows you to analyze several dependent variables from an experimental design simultaneously is
• ——- is used for causal analysis
• Factor loading is
• A factor loading of 0.80 means, generally speaking, that
• A factor is a combination of variables
• Factor analysis pinpoints the clusters of correlations between variables and for each cluster

• 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.

Online MCQs Multivariate

Online MCQs about various Subjects