# Important Online MCQs Multivariate 2

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.

Online Multivariate Quiz

1. An advantage of using an experimental multivariate design over separate univariate designs is that using the multivariate analysis – – – – – – -.

2. ——- is used for causal analysis

3. In multivariate analysis the distribution of $\overline{X}$ is

4. In multivariate analysis Var-Cov matrix is

5. In principal component analysis (PCA) the first component contains

6. In multivariate analysis, $n(\overline{x} – \mu)’ S^{-1} (\overline{x} – \mu)$ is called

8. A multivariate statistic that allows you to analyze several dependent variables from an experimental design simultaneously is

9. Factor analysis pinpoints the clusters of correlations between variables and for each cluster

10. If $X \sim N (\mu, \Sigma)$ then $(X-\mu)’ \Sigma^{-1} (X-\mu)$ is distributed as

11. In the relation $\Sigma = V^{1/2} \rho ^{1/2} V^{1/2}$, the $V^{1/2} is called 12. In factor analysis the reliable variance 13. A factor loading of 0.80 means, generally speaking, that 14. The goal of multiple regression is to 15. A factor is a combination of variables 16. A multivariate statistic that allows you to investigate the relationship between two sets of variables is 17. In PCA, when the variables are measured in different units then PC extracted on the basis of 18. In principal component analysis, the components are 19. Correlational multivariate analysis includes 20. In multivariate analysis the distribution of the sample covariance matrix is An application of different statistical methods applied to the economic data used to find empirical relationships between economic data is called Econometrics. In other words, Econometrics is “the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference”. ### Online MCQs Multivariate • In multivariate analysis Var-Cov matrix is • In the relation$\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
• 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.