Match List I with List Il

List I (Techniques/Analysis) LIST II (Application)

A. Time Series Analysis I. Most commonly recommended test for uniformity model.

B. Chi Square Test II. Making predictions with reasonable confidence.

C. Cluster Analysis III. Comparing distributions on 2-dimensional surfaces.

D. Lorenz Curve IV. It may be either agglomerative or divisive.

Choose the correct answer from the options given below:

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Match List I with List Il

List I (Techniques/Analysis) LIST II (Application)

A. Time Series Analysis I. Most commonly recommended test for uniformity model.

B. Chi Square Test II. Making predictions with reasonable confidence.

C. Cluster Analysis III. Comparing distributions on 2-dimensional surfaces.

D. Lorenz Curve IV. It may be either agglomerative or divisive.

Choose the correct answer from the options given below:

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UGC NET (Geography) Official Paper-II (Held On: 03 Mar, 2023 Shift 1)

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A - II, B - I, C - IV, D - III
A - I, B - III, C - II, D - IV
A - III, B - II, C - IV, D - I
A - IV, B - III, C - I, D - II

Answer 1

The correct answer is A - II, B - I, C - IV, D - III
Important Points

List I (Techniques/Analysis)	List II (Application)	Characteristics
A. Time Series Analysis	II. Making predictions with reasonable confidence	Time Series Analysis is a statistical technique that deals with time series data, or trend analysis. This method is widely used for forecasting or making predictions based on known historical patterns or trends. It can help predict a future event with a reasonable degree of confidence.
B. Chi Square Test	I. Most commonly recommended test for uniformity model	The Chi-Square test is a statistical method used to determine if a null hypothesis of independence or homogeneity is likely to be true. It's often used in hypothesis testing, and it's indeed a common choice when you're trying to understand whether different groups follow the same distribution, i.e., if they are "uniform" with respect to some property.
C. Cluster Analysis	IV. It may be either agglomerative or divisive	Cluster Analysis is a set of techniques used to classify or group similar data objects into clusters. The process can be either agglomerative, where each data point starts in its own cluster and pairs of clusters are merged. As one moves up the hierarchy, or divisive, where all observations start in one cluster and splits are performed recursively as one moves down the hierarchy.
D. Lorenz Curve	III. Comparing distributions on 2-dimensional surfaces	A Lorenz Curve is a graphical representation used in economics to represent income or wealth distribution. It is a two-dimensional diagram which is used to express inequality in a distribution.

Therefore, the correct matching is: A - II, B - I, C - IV, D - III

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	List I (Techniques/Analysis)		LIST II (Application)
A.	Time Series Analysis	I.	Most commonly recommended test for uniformity model.
B.	Chi Square Test	II.	Making predictions with reasonable confidence.
C.	Cluster Analysis	III.	Comparing distributions on 2-dimensional surfaces.
D.	Lorenz Curve	IV.	It may be either agglomerative or divisive.