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Quantitative Methods Prelims

Total questions: 59

Worksheet time: 30mins

Name
Class
Date
1.

It is a scientific approach to managerial decision making in which raw data are processed and manipulated to produce meaningful information

a)

Quantitative Analysis

b)

Qualitative Analysis

c)

Quantitative Research

d)

Qualitative Research

2.

combination of numbers and letters

a)

Alphanumeric

b)

Text

c)

Image

d)

Audio

3.

sentences and paragraphs used in written communication

a)

Alphanumeric

b)

Text

c)

Image

d)

Audio

4.

graphics, shapes, figures etc.

a)

Alphanumeric

b)

Text

c)

Image

d)

Audio

5.

human voice and other sounds

a)

Alphanumeric

b)

Text

c)

Image

d)

Audio

6.

Best of the Worst

a)

Maximin

b)

Maximax

c)

Minimin

d)

Minimax

7.

It involves looking at the worst that could happen for each possible course of action and then choosing/selecting the action with the largest value.

a)

Maximin

b)

Maximax

c)

Minimin

d)

Minimax

8.

It involves looking at the best that could happen for each possible course of action and then choosing/selecting the action with the largest value.

a)

Maximin

b)

Maximax

c)

Minimin

d)

Minimax

9.

Best of the Best

a)

Maximin

b)

Maximax

c)

Minimin

d)

Minimax

10.

It involves calculating the average of each alternative and then choosing/selecting the alternative with the largest average.

a)

Laplace Strategy

b)

Hurwicz Strategy with α as coefficient of realism

c)

Minimax regret Strategy

d)

Minimin regret Strategy

11.

It involves multiplying the best outcome in the row by the given value of α, multiplying the worst outcome in the row by 1-α, and adding the two (2) result together.

a)

Laplace Strategy

b)

Hurwicz Strategy with α as coefficient of realism

c)

Minimax regret Strategy

d)

Minimin regret Strategy

12.

It involves computing an opportunistic loss (or regret) of each alternative by simply subtracting the entry from that of the highest column value and selecting the maximum regret value of each row. Finally, determine the decision by choosing the minimum/lowest regret.

a)

Laplace Strategy

b)

Hurwicz Strategy with α as coefficient of realism

c)

Minimax regret Strategy

d)

Minimin regret Strategy

13.

EV = P (X)


Expected Value

a)

EV

b)

P

c)

X

d)

=

14.

EV = P (X)


Probability of an Event

a)

EV

b)

P

c)

X

d)

=

15.

EV = P (X)


Amount to be received for a particular event

a)

EV

b)

P

c)

X

d)

=

16.

The Quantitative Analysis Approach


Types of Model Except

a)

Iconic Model

b)

Analog Model

c)

Mathematical Model

d)

Analytical Model

17.

The Quantitative Analysis Approach


Possible Problems in Defining the Problem (4)

a)

Conflict Viewpoints

b)

Impacts on other departments

c)

Beginning Assumptions

d)

Solution Outdated

e)

Testing the Solution

18.

The Quantitative Analysis Approach


Possible Problems in Developing a Model (2)

a)

Fitting the Textbook Model

b)

Impacts on other departments

c)

Beginning Assumptions

d)

Understanding the Model

19.

The Quantitative Analysis Approach


Possible Problems in Acquiring an Input Data (2)

a)

Fitting the Textbook Model

b)

Using Accounting Data

c)

Validity of Data

d)

Understanding the Model

20.

The Quantitative Analysis Approach


It is usually sensitive data such as cash flows and turnovers, hence, it is not open for public research.

a)

Fitting the Textbook Model

b)

Accounting Data

c)

Validity of Data

d)

Understanding the Model

21.

The Quantitative Analysis Approach


We tend to manipulate data according to our own purposes to make it look “good and clean”.

a)

Fitting the Textbook Model

b)

Accounting Data

c)

Validity of Data

d)

Understanding the Model

22.

It is about attributes and properties; information that can't actually be measured.

a)

Qualitative Data

b)

Quantitative Data

c)

Research Data

d)

Confidential Data

23.

It is the data that can be measured and expressed in numerical terms.

a)

Qualitative Data

b)

Quantitative Data

c)

Research Data

d)

Confidential Data

24.

A kind of Qualitative Data that involves naming/identifying a thing without assigning it to an implicit or natural value or rank.

a)

Nominal Data

b)

Ordinal Data

c)

Discrete Data

d)

Continuous Data

25.

A kind of Qualitative Data that involves some kind of order or scale (such as low to high or high to low) relationship among the variable’s observations.

a)

Nominal Data

b)

Ordinal Data

c)

Discrete Data

d)

Continuous Data

26.

A kind of Quantitative Data that reflects a number obtained by counting. Typically, it involves integers.

a)

Nominal Data

b)

Ordinal Data

c)

Discrete Data

d)

Continuous Data

27.

A kind of Quantitative Data that could be divided and reduced to finer and finer levels. The

number of decimal places depends on the precision of the measuring device.

a)

Nominal Data

b)

Ordinal Data

c)

Discrete Data

d)

Continuous Data

28.

Methods of Collecting Qualitative Data


It is an open discussion group of about 6- 8 participants led by a neutral moderator or facilitator.

a)

Focus Group

b)

Observation

c)

Interview

d)

Archival Materials

29.

Methods of Collecting Qualitative Data


It is the process of gathering open-ended, firsthand information by observing an object or a phenomenon in a certain way.

a)

Focus Group

b)

Observation

c)

Interview

d)

Archival Materials

30.

Methods of Collecting Qualitative Data


It is a purposeful discussion between two (2) or more people by asking questions directly from respondents, either face-to- face or by telephone.

a)

Focus Group

b)

Observation

c)

Interview

d)

Archival Materials

31.

Methods of Collecting Qualitative Data


This involves materials such as newspapers.

a)

Focus Group

b)

Observation

c)

Interview

d)

Archival Materials

32.

Classification of Quantitative Data


It is a data which not only classifies and orders the measurements, but also specifies the exact differences between the values.

a)

Interval Data

b)

Ratio Data

c)

Discrete Data

d)

Continuous Data

33.

Classification of Quantitative Data


It tell us the exact value between units and also have an absolute zero.

a)

Interval Data

b)

Ratio Data

c)

Discrete Data

d)

Continuous Data

34.

Methods of Collecting Quantitative Data


It is used to collect/gather information from a group of people by employing printed questionnaires mailed to large samples, though it can also be done through the telephone.

a)

Survey

b)

Experiments Study

c)

Observational Study

d)

Observations and Interviews

35.

Methods of Collecting Quantitative Data


It deliberately assigns subjects to various treatments for studying the reasons for changes in the output response(s).

a)

Survey

b)

Experiments Study

c)

Observational Study

d)

Observations and Interviews

36.

Methods of Collecting Quantitative Data


It collects data in a way that does not directly interfere with how the data arise, i.e. merely "observe".

a)

Survey

b)

Experiments Study

c)

Observational Study

d)

Observations and Interviews

37.

Manipulation can be done by EXCEPT:

a)

Solving equations

b)

Trial and Error

c)

Complete enumeration

d)

Using an algorithm

e)

Controlling someone

38.

It involves examining the collected information in ways that reveal the relationships, patterns, trends, etc. that can be found within it.

a)

Analyzing Data

b)

Sensitivity Analysis

c)

Ratio Data

d)

Interval Data

39.

It allows a series of “what-if” questions to be answered for it determine possible changes in the

various parameters of the original problem.

a)

Analyzing Data

b)

Sensitivity Analysis

c)

Ratio Data

d)

Interval Data

40.

There is a false notion in us that if someone thinks complicatedly or elaborately thinks well.

a)

Analyzing Data

b)

Sensitivity Analysis

c)

Hard to understand mathematics

d)

Only one answer is limiting

41.

QA models tend to give one solution to a problem. One way to offset this is to come up with alternative scenarios or sensitivities to give managers options to choose from.

a)

Analyzing Data

b)

Sensitivity Analysis

c)

Hard to understand mathematics

d)

Only one answer is limiting

42.

Planning and Conducting Surveys


I. Analyze the results by making graphs and drawing conclusions

II. Determine the goal of your survey

III. Decide what questions to ask in what order, and how to phrase them

IV. Choose which of the following methods to use to collect valuable information with the survey

V. Identify the sample population

VI. Conduct the interview and collect the information.

a)

I, III, V, VI, II, IV

b)

IV, VI, I, II, V, III

c)

II, V, IV, III, VI, I

d)

VI, I, III, II, IV, V

43.

It is the factor that causes a change in the dependent variable. It can be thought of as an intervention or a treatment.

a)

Independent Variables

b)

Dependent Variables

c)

Random Variables

d)

Interconnected Variables

44.

It is what we hope to change through the experiment. This is the “effect” in cause and effect relationship.

a)

Independent Variables

b)

Dependent Variables

c)

Random Variables

d)

Interconnected Variables

45.

(aka Classification Factors, Uncontrollable Factors)

a)

Independent Variables

b)

Dependent Variables

c)

Random Variables

d)

Interconnected Variables

46.

(aka Experimental Factors, Controllable Factors)

a)

Independent Variables

b)

Dependent Variables

c)

Random Variables

d)

Interconnected Variables

47.

Planning and Conducting Experiments


I. Experiment Idea (Recognition of the goal of the experiment)

II. Analysis and Interpretation

III. Experiment Planning

IV. Presentation and Package

V. Experiment Operation

a)

I, III, V, II, IV

b)

IV, I, II, V, III

c)

II, V, IV, III, I

d)

I, III, II, IV, V

48.

Experiment Designs


This is when each person or object upon which the treatment is applied is assigned to a treatment completely at random.

a)

Completely Randomized Design

b)

Matched-pair Design

c)

Randomized Block Design

d)

Internal Point Design

49.

Experiment Designs


This is when the person or object upon which the treatment is applied are paired up and each of the pair is assigned to a different treatment.

a)

Completely Randomized Design

b)

Matched-pair Design

c)

Randomized Block Design

d)

Internal Point Design

50.

Experiment Designs


This is used when the person or object upon which the treatment is applied are divided into homogeneous groups called blocks. Within each block, the person or object upon which the treatment is applied are randomly assigned treatments.

a)

Completely Randomized Design

b)

Matched-pair Design

c)

Randomized Block Design

d)

Internal Point Design

51.

Validity Evaluations


It occurs when causal relationship between the variables being studied can be determined.

a)

Internal Validity

b)

External Validity

c)

Construct Validity

d)

Conclusion Validity

52.

Validity Evaluations


It occurs when conclusions can be generalized to other people, times and contexts.

a)

Internal Validity

b)

External Validity

c)

Construct Validity

d)

Conclusion Validity

53.

Validity Evaluations


It demonstrates that the assessment is actually measuring the quality of an instrument or experimental design.

a)

Internal Validity

b)

External Validity

c)

Construct Validity

d)

Conclusion Validity

54.

Validity Evaluations


It occurs when a relationship of some kind between the two variables being examined can be found.

a)

Internal Validity

b)

External Validity

c)

Construct Validity

d)

Conclusion Validity

55.

Experiment Operation


It is concerned with preparing the subjects as well as the material needed (e. g., data collection forms). The participants must be informed about the intention; we must have their consent and they must be committed.

a)

Preparation

b)

Execution

c)

Data Validation

d)

Planning

56.

Experiment Operation


It is concerned with ensuring that the experiment is conducted according to the plan and design

of the experiment, which includes data collection.

a)

Preparation

b)

Execution

c)

Data Validation

d)

Planning

57.

Experiment Operation


It is concerned with ensuring that the actual collected data is correct and provide a valid picture of the experiment.

a)

Preparation

b)

Execution

c)

Data Validation

d)

Planning

58.

Analysis and Interpretations


Provides information about the properties of the produced data and allow readers to understand important things about it from a single glance.

a)

Descriptive Statistics

b)

Data set reductions

c)

Hypothesis testing

d)

Presentation and Package

59.

Analysis and Interpretations


It allows us to estimate how likely it is that our results were produced by chance rather

than a genuine experimental effect.

a)

Descriptive Statistics

b)

Data set reductions

c)

Hypothesis testing

d)

Presentation and Package