**Q.1** Independent variables refer to those variables _________.

**A.** Which acts as an input in the experiment

**B.** Whose values are not related to the experiment

**C.** Whose values are known during the experiment

**Ans : **Which acts as an input in the experiment

**Q.2** What is multivariate statistics?

**A.** Simultaneous observations on several variables

**B.** Simultaneous analysis on several variables

**C.** Finding relation between several variables

**D.** All the options

**Ans : **All the options

**Q.3** Use of only one variable to describe data is known as _____________.

**A.** Multivariate data analysis

**B.** Univariate data analysis

**C.** Infinite data analysis

**D.** Bivariate data analysis

**Ans : **Univariate data analysis

**Q.4** Multivariate data analysis is an application of ________.

**A.** Dimension reduction

**B.** Multivariate Statistics

**C.** Categorizing Variables

**D.** All the options

**Ans : **Multivariate Statistics

**Q.5** What are the features of a multivariate random variable?

**A.** It is a set of unknown variables

**B.** The variables have not occurred yet

**C.** Both the options

**Ans : **Both the options

**Q.6** Dependent variables refer to those variables __________.

**A.** Whose variation is never analyzed

**B.** Whose variation is analyzed

**C.** Both the options

**Ans : **Whose variation is analyzed

**Q.7** If the area under the PDF curve is zero, then __________.

**A.** Probability = 1

**B.** Probability = 0

**C.** Probability = not defined

**D.** Data insufficient

**Ans : **Probability = 0

**Q.8** What is done when a new data in the sub Interval is added?

**A.** Bin is inserted from the bottom

**B.** One bin is added on the top

**C.** Height of the previous bin is doubled

**D.** Height of the bin is increased

**Ans : **One bin is added on the top

**Q.9** A pattern such as a group or a trend in the data table cannot be studied using Multivariate data analysis.

**A.** True

**B.** False

**Ans : **False

**Q.10** The least number of coordinates required to showcase a point is _________.

**A.** Multivariate analysis

**B.** Co-ordinates

**C.** Dimension

**D.** Bivariate analysis

**Ans : **Dimension

**Q.11** Stochastic variables are also known as ___________.

**A.** Random variables

**B.** Variables

**C.** Both the options

**D.** None of the options

**Ans : **Random variables

**Q.12** What is the drawback of using Kernel density estimation’s Histogram method?

**A.** It is independent of the bin width

**B.** Plot is discontinuous

**C.** Plot is not smooth

**D.** Plot is over smooth

**Ans : **Plot is not smooth

**Q.13** What are the features of multivariate random variable?

**A.** It is a set of unknown variables

**B.** The variables have not occurred yet

**C.** Both the options

**Ans : **Both the options

**Q.14** What is posterior probability?

**A.** The conditional probability of the event after the evidence is taken into consideration!

**B.** The probability distribution that is done as a lack of evidence

**C.** Both the options

**D.** None of the options

**Ans : **Both the options

**Q.15** Least number of coordinates required to showcase a point is ______________.

**A.** Dimension

**B.** Co-ordinates

**C.** Multivariate analysis

**D.** Bivariate analysis

**Ans : **Dimension

**Q.16** Lurking variable remains _________________.

**A.** Not defined

**B.** Present during the analysis

**C.** Omnipresent in the analysis

**D.** Hidden during the analysis

**Ans : **Hidden during the analysis

**Q.17** Which estimation can be represented by a single value?

**A.** It is difficult to represent estimations as single value

**B.** Interval estimation

**C.** Point estimation

**D.** All the options mentioned

**Ans : **All the options mentioned

**Q.18** What is prior probability?

**A.** Probability distribution done with a lack of evidence

**B.** Probability distribution done with sufficient evidence

**Ans : **Probability distribution done with a lack of evidence

**Q.19** What is density estimation?

**A.** It estimates only probability

**B.** It estimates probability density function

**C.** It is a type of point estimation

**D.** None of these

**Ans : **It is a type of point estimation

**Q.20** What are the characteristics of Markov process?

**A.** It is a Random process

**B.** The past event does not affect the future event

**C.** Both the options

**Ans : **Both the options

**Q.21** In box kernel density estimation, __________.

**A.** The histogram is centered over the data points

**B.** The histogram is decentralized

**C.** The histogram is decentralized over several data points

**D.** None of the options

**Ans : **The histogram is centered over the data points

**Q.22** Probability mass function is also known as ________.

**A.** Mass function

**B.** Probability density function

**C.** Simple mass function

**D.** Statistical mass function

**Ans : **Probability density function

**Q.23** Principal component analysis reduces ____________.

**A.** Large number of uncorelated variables

**B.** Large number of corelated variables

**C.** Both the options

**Ans : **Large number of corelated variables

**Q.24** What is Kernel density estimation?

**A.** It is the implementation of parametric density estimation

**B.** It is the implementation of non – parametric density estimation

**Ans : **It is the implementation of non – parametric density estimation

**Q.25** _____________ is an example of Multivariate analysis in which relationship exists between a dependent variable and independent variable/variables.

**A.** Partial Least Squares Regression

**B.** Cluster analysis

**C.** None of the options

**Ans : **Partial Least Squares Regression

**Q.26** What is data analysis?

**A.** Organizing the data

**B.** Analyzing the data

**C.** Interpretation of the data

**D.** All the options

**Ans : **All the options

**Q.27** We use _______ in histogram for sub intervals.

**A.** “blocks”

**B.** “points”

**C.** “segments”

**D.** “bins”

**Ans : **“bins”

**Q.28** What is Random walk?

**A.** We can sometime predict the outcome in advance

**B.** We can always predict the outcome in advance

**C.** We cannot predict the outcome in advance

**D.** None of the options

**Ans : **We can sometime predict the outcome in advance

**Q.29** What is box kernel density estimate?

**A.** Block in the histogram is averaged somewhere

**B.** Blocks of the histogram are integrated

**C.** Block in the histogram is centered over the data points

**D.** Blocks of the histogram are combined to form the overall block

**Ans : **Block in the histogram is centered over the data points

**Q.30** If time space or state space is discrete, ___________.

**A.** Markov process can be termed as continuous-time Markov chains

**B.** Markov process can be termed as discrete-time Markov chains

**C.** None of the options

**Ans : **Markov process can be termed as discrete-time Markov chains

**Q.31** p(x|?) is also known as the _________.

**A.** Estimation

**B.** Likelihood

**C.** Probability

**D.** Variance

**Ans : **Likelihood

**Q.32** What is parameter?

**A.** It tells something useful about the population!

**B.** Parameter is a measurable quantity

**C.** Both of these

**D.** None of these

**Ans : **Parameter is a measurable quantity