# Correlation and dependence: Quiz

Question 1: The correlation coefficient completely defines the dependence structure only in very particular cases, for example when the distribution is a ________.
Multivariate normal distributionProbability distributionGeneralized normal distributionStudent's t-distribution

Question 2: The Pearson correlation is 1 in the case of an increasing linear relationship, −1 in the case of a decreasing linear relationship, and some value between -1 and 1 in all other cases, indicating the degree of ________ between the variables.
Linear algebraEigenvalue, eigenvector and eigenspaceVector spaceLinear independence

Question 3: where x and y are the sample means of X and Y, sx and sy are the sample ________ of X and Y.
VarianceNormal distributionMedianStandard deviation

Question 4: Measures of dependence based on ________ are always defined.
PercentileQ-Q plotQuantileMedian

Question 5: If the measures of correlation used are product-moment coefficients, the correlation matrix is the same as the ________ of the standardized random variables Xi /SD(Xi) for i = 1, ..., n.
Matrix (mathematics)Multivariate normal distributionPrincipal component analysisCovariance matrix

Question 6: Karl Pearson developed the coefficient from a similar but slightly different idea by ________.
Ronald FisherCharles DarwinErasmus DarwinFrancis Galton

Question 7: Note that the examples are sometimes said to demonstrate that the Pearson correlation assumes that the data follow a ________, but this is not correct.
Generalized normal distributionNormal distributionProbability distributionStudent's t-distribution

Question 8: It is a corollary of the Cauchy–Schwarz inequality that the correlation cannot exceed 1 in ________.
Absolute valueEuclidean spaceVector spaceComplex number

Question 9: In statistics, correlation and dependence are any of a broad class of statistical relationships between two or more random variables or observed ________ values.
DataGeometric meanStatistical graphicsExperiment

Question 10: The most familiar measure of dependence between two quantities is the ________, or "Pearson's correlation." It is obtained by dividing the covariance of the two variables by the product of their standard deviations.
Correlation and dependenceStudent's t-distributionPearson product-moment correlation coefficientNormal distribution