Which of the following is not a component of decision support mathematical processes?

1. The objective of B. is

A. To support decision-making and complex problem solving. B. To support information gathering. C. To support data collection. D. To support data analysis.

1. Decision making process is of phases. A. Three B. Five C. Two D. Six E.
2. DSS stands for:

A. Decision Support System. B. Definition support System. C. Data sub system D. D. Data storage system.

1. measurements express the level of conformity of a given system to the objectives for which it was designed. A. Effectiveness B. Efficiency C. Evaluation D. Feedback

2. Decision support systems are used for A. Management decision making B. Providing tactical information to management C. Providing strategic information to management D. Better operation of an organization

3. Which of following is not phase of decision making process A. Design B. Analysis C. Intelligence D. Choice

4. Strategic information is needed for A. Day to day operations B. Meet government requirements C. Long range planning D. Short range planning

5. Strategic information is needed for A. Day to day operations B. Meet government requirements C. Long range planning

D. Short range planning

1. Phases are in Decision making process A. Intelligence, Design, Choice, Implementation, Control. B. Design, Develop, Apply C. Data, Process, Develop, Implement, Control D. Search, Sort, Design, Develop, Implement

2. Business intelligence allows to make and timely decisions. A. Effective B. Right C. Correct D. Beneficiary

3. What is a model?

A. a selective abstraction of real world B. a selective imagination of 1st world C. a selective proposal of real world D. a selective example of second word

1. A material representation of a real system, whose behaviour is imitated for the purpose of the analysis is called as?

A. Analogical Model B. Iconic Model C. Symbolic Model D. Static Model

1. Which is the last Phases of mathematical models for decision making

A. Problem Identification B. Implementation and Testing C. Model Formation D. Development of Algorithm

1. Which of the statement is not true about Data Mining?

A. The term data mining refer to the overall process consisting of data gathering and analysis, development of inductive learning models and adoption of practical decisions and consequent actions based on the knowledge acquired. B. Data mining analysis is to draw a fresh conclusion without investigating the past data, observations and interpretations

A. Min-max standardization B. z- score C. standardisation D. zero scaling

1. how many distinct myopic search schemes are followed? A. two B. four C. three D. one

2. Which of the following is finally produced by Hierarchical Clustering? a. final estimate of cluster centroids b. tree showing how close things are to each other c. assignment of each point to clusters d. k-Means Clustering

3. Point out the wrong statement. a. k-means clustering is a method of vector quantization. b. k-means clustering aims to partition n observations into k clusters. c. k-nearest neighbor is same as k-means. d. k-nearest neighbor has nothing to do with k-means.

4. Which of the following is characteristic of exploratory graph? a. Made slowly b. Axes are not cleaned up c. Color is used for personal information d. All of the mentioned

5. Which of the following gave rise to need of graphs in data analysis? a. Data visualization b. Communicating results c. Decision making d. data Analysis

6. Which of the following information is not given by five-number summary? a. Mean b. Median c. Mode d. average

7. Which of the following graph can be used for simple summarization of data? a) Scatterplot b) Overlaying c) Barplot d) pie chart

27 ) Classify variable which is not continuous. a. age

b. height c. gender d. revenue of medical shop

28 ) Neural Networks are methods of?

a. Regression b. Clustering c. Classification d. Customization

1. Classify variable which is not continuous. a. age b. height c. gender d. revenue of medical shop

2. Agglomerative methods are techniques.

a) Top-Down b) Left-Right c) Right-Left d) Bottom-Up

1. Which of the following is not a component of Relational Marketing A. Organisation B. BI and Data Mining C. Technology D. Fund

2. Which of the following is not an optimization model? A. Extra Capacity B. Maximum Fixed Cost C. Backlogging D. Multiple Plants

3. The expresses relationship between the Inputs utilized and Outputs Produced: A. Efficiency Function B. Effective Frontier C. Efficient Frontier D. Effective Fact

34). The Relationship Marketing is all about A. Creating database value B. Travelling programs C. Maintaining relationship with customer

d. Culture

1. Characteristics of expert systems A. High Performance B. Demonstrating C. Advising D. Diagnosing

2. Strategy followed for finding cause or reasons. A. Backward Chaining B. Forward Chaining C. Facts D. Decisions

3. Knowledge Management Activity aims at A. Total turing test B. The rational agent approach C. To build knowledge infrastructure D. Thinking humanly

4. What is the form of Knowledge representation? A. IF-THEN B. IF-THEN-ELSE C. IF-ELSE D. ELSE

5. A is nothing but an expert system without knowledge base. A. Tools B. Expert System C. shell D. knowledge

6. which one of the following is not a type of Knowledge A. Declarative Knowledge B. Procedural Knowledge C. Tactic Knowledge D. Collective Knowledge

7. Who introduced the term “Artificial Intelligence” A. Arthur Samule B. Marvin Lee Minsky C. Jhon McCarthy

D. E. F. Codd

1. is required to exhibit intelligence. A. Data B. Knowledge C. Information D. High-quality data

2. Who is the person who is responsible for making knowledge management effort in an organization . A. CIO B. CEO C. CKO D. CKE

1. Decision making process is of phases. a) Three

c) Two d) Six

1. Well defined and recurring decision-making procedure is called

b) Semi-structured c) Operational d) Unstructured

1. In approach, a decision maker considers economic, tactical legal, ethical, procedural and political factors. a) Absolute rationality approach b) Bounded rationality approach

d) None of the above.

1. a) Data mart is a subset of data warehouse. b) Data marts contain repositories of summarized data collected for analysis on a specific section or unit within an organization. a) Only a is correct b) Only b is correct

d) Both are wrong.

1. is the outcome of extraction and processing activities carried out on data. a) Data

c) Knowledge d) Wisdom

1. In ETL ‘E’ stands for. a) External

c) Extreme d) None of the above

1. DSS stands for:

b) Definition support System. c) Data sub system d) Data storage system

1. represent the real problem situations. a) Data b) Models

c) Tools d) Information

1. During the phase, additional data conversion occurs to performed to obtain the summaries that will reduce the response time. a) Loading. b) Extraction.

d) Performance Evaluation.

1. Optimization is:

b) Successful marketing approaches to achieve the optimum outcome. c) Getting the greatest return for the least expenditure of time, effort, manpower. d) All the above.

1. (a)A decision support system helps in decision making but does not necessarily give a decision itself. (b) decision support system is a computer-based application that collects organizes and analyses business data to facilitate quality business decision making for management, operations, and planning. a) only a is correct. b) only b is correct c) d) both are wrong.

2. measurements express the level of conformity of a given system to the objectives for which it was designed.

b) Efficiency c) Evaluation d) Feedback

1. is the first stage in developing in decision support system. a) Analysis b) Design

d) Planning

1. Data by itself is not useful unless a) It is massive

c) It is collected from diverse sources d) It is properly stated

1. Decision support systems are used for

b) Providing tactical information to management c) Providing strategic information to management d) Better operation of an organization

1. Close System Cycle defined as a) Which is System cycle does not need any output.

c) Able to modify their own output flows based on process. d) Able to modify their own output without any process.

1. Information is transformed into to make decisions. a) Data b) Information

d) File

1. Mathematical models are developed by

b) exploring the relationships with data. c) developing mathematical logic d) exploiting the relationships among system control variables, parameters and evaluation metrics

1. BI supports for data. a) Files b) Data Marts & Data Warehouse. c) Data Mining

2. The fourth phase of the Bicycle involves performances measurement a) Design

c) Intelligence d) Graph

1. technologies enabling factors that have facilitate development of BI with complex organizations a) Application b) System c) business information

2. Phases are in Decision making process

b) Design, Develop, Apply c) Data, Process, Develop, Implement, Control d) Search, Sort, Design, Develop, Implement

1. Decisions can be classified into their a) concept and thoughts b) Supply and Demand

d) Techniques

1. Full Form of DSS is a) Day–to-day System Support. b) Dynamic System Service.

d) Decision Solve System.

1. Knowledge Management increase in the

b) no. of difficulties considered c) no. of risks considered d) no. of models considered

1. Information is transformed into when it is used to make decisions and develop the corresponding actions. a) Data

c) Outcome d) Experience

1. Business intelligence allows to make and timely decisions.

b) Correct c) Right d) Beneficiary

1. It is necessary to recognize and accurately spell out the problem in phase in the Cycle of a business intelligence analysis

b) Insight c) Decision d) Evaluation

1. ETL process consists of Extract, and Load. a) Translate b) Track c) Transmit

2. Analysis, Design, Planning and are the Phases in the development of a business intelligence system. a) Implementation

c) Control d) Coding

1. The evaluation metrics can be categorized into two main classes - effectiveness and . a) Perfection b) Performance

c) Symbolic d) Static

1. What is allowed by Sensitivity and Scenario analyses be assessed? a) the robustness of optimal decisions from variations in the input parameters. b) the robustness of optimal decisions to variations into input parameters. c) the robustness of optimal decisions to variations in the input data. d) the robustness of optimal decisions to variations in the input parameters.

2. Which model observes the status of a system only at the beginning or at the end of discrete intervals?

b) Static-time dynamic models c) Symbolic -time dynamic models d) Iconic-time dynamic models

1. The purpose of explanatory models is to functionally identify a possible relationship between a dependent variable and? a) a set of positive attributes b) a set of negative attributes c) a set of neutral attributes d) s

2. Which is one of the primary objectives of mathematical models?

b) to identify irregular patterns in the data c) to identify negative patterns in the data d) to identify neutral patterns in the data

1. The conceptual paradigm outlined determines a wide and popular class of mathematical models for decision making, represented by models

b) stochastic models c) supervised models d) iconic models

1. What is the aim of Data Mining?

b) useful for knowledge workers in decision making c) extracting raw data d) Both A & B

1. On which learning methods the Data Mining method is based?

b) deductive learning methods c) basic learning methods d) comprehensive learning methods

1. What is the purpose of Interpretation?

b) to express the rules and criteria for easy understanding c) to identify irregular patterns in the data d) Both A & B

1. Classification Trees or Association Rules are also called as?

b) knowledge discovery in databases c) deep learning d) A & B

1. Which are the last Phases of mathematical models for decision making a) Problem Identification

c) Model Formation d) Development of Algorithm

1. Which mathematical model aims at understanding the mechanisms that regulate the development of intelligence, ability to extract knowledge from experience in order to apply it in the future. a) Risk analysis models b) Optimization models

d) Waiting line models

1. In which Mathematical model the decision maker is required to choose among a number of available alternatives

b) Optimization models c) Pattern recognition Models d) Waiting line models

1. Which of the statement is not true about Data Mining? a) The term data mining refers to the overall process consisting of data gathering and analysis, development of inductive learning models and adoption of practical decisions and consequent actions based on the knowledge acquired.

c) Data mining activities can be subdivided into two major investigation streams, interpretation and prediction. d) The data mining process is based on inductive learning methods

1. Which is not the Phase of data Mining Process a) Data Gathering b) Selection of Attributes c) Prediction and interpretation

2. ''To anticipate the value that a random variable will assume in the future or to estimate the likelihood of the future events'' is the purpose of? a) Interpretation

c) Data mining d) A & B both

1. attributes are numerical attributes that assume a finite number or a countable infinity of values. a) Ordinal b) Continuous

d) Nominal

1. is used when the target variable takes on continuous values.

b) Clustering c) Classification d) Characterization

1. The purpose of is to identify and implement corrective actions in case of incomplete and inconsistent data or data affected by noise.

b) Data Transformation c) Data Reduction d) Data Noise

1. If the distribution of values of the attribute aj is roughly normal, the z index-based transformation generates values that are almost certainly within the range.

b) (-2,2) c) (-4,4) d) (-1,1)

1. The purpose of is to obtain a decrease in the number of distinct values assumed by one or more attributes. a) Data Validation b) Data Transformation

d) Data Noise

32. PCA is

a) Projection Combination Analysis b) Principal Combination Analysis

d) Projection Combination Analysis

1. In learning analysis, a target attribute either represents the class to which each record belongs.

b) Unsupervised Learning c) Clustering d) Classification

1. learning analyses are not guided by a target attribute. a) Supervised Learning

c) Clustering d) Classification

1. Which of the following does not include in seven basic data mining tasks? a) characterization and discrimination

c) regression d) time series analysis

1. In a a set of observations is available, usually represented by the records of a dataset, whose target class is known. a) b) Data Transformation c) Data Reduction d) Clustering problem

2. is used when the target variable takes on continuous values. a) Classification

c) Data Transformation d) Data Reduction

1. are used to identify interesting and recurring associations between groups of records of a dataset. a) Supervised Learning b) Unsupervised Learning

d) time series analysis

1. The term refers to a homogeneous subgroup existing within a population. a) Continuous b) Discrete c) Nominal

2. In there are no predefined classes or reference examples indicating the target class.

Which component of a robot help them to make decisions according to their environment?

Which of the following types of bots simulate conversations with people?

What part of an expert system is divided into knowledge about the domain and knowledge about problem solving and solution procedures?

What measure is used to characterize the peak tall thin nature of distribution?