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PMP - Study Guide > Data Analysis > Flashcards

Data Analysis Flashcards

1
Q

A data analysis technique used to evaluate and select between identified options.

Used in:

Plan Scope Management (P)
Define Scope (P)
Plan Schedule Management (P)
Estimate Activity Resources (P)
Estimate Activity Durations (P)
Estimate Costs (P)
Plan Risk Responses (P)
Plan Cost Management (P)
Manage Quality (E)
Monitor and Control Project Work (M&C)
Perform Integrated Change Control (M&C)
Control Resources (M&C)
Monitor Stakeholder Engagement (M&C)
A

Alternative Analysis

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2
Q

Using other characteristics of risk (in addition to probability and impact) when prioritizing individual project risks for further analysis and action.

Used in:

Perform Qualitative Risk Analysis (P)

A

Assessment of other risk parameter

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3
Q

A data analysis technique that involves analyzing assumptions and constraints on the project for the purposes of identifying risks.

Used in:

Identify Risks (P)
Plan Stakeholder Engagement (P)
A

Assumption and constraint analysis

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4
Q

A data analysis technique to determine the costs incurred to ensure quality and to avoid the costs of failure (such as rework, warranty, or loss of reputation).

Used in:

Estimate Costs (P)
Plan Quality Management (P)
A

Cost of Quality (CoQ)

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5
Q

A data analysis technique used for financial analysis. In this technique, the benefits of a given situation or business-related action are summed, and then the costs associated with taking that action are subtracted.

Used in:

Plan Quality Management (P)
Plan Risk Responses (P)
Monitor and Control Project Work (M&C)
Perform Integrated Change Control (M&C)
Control Resources (M&C)
A

Cost-Benefit Analysis

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6
Q

A data analysis technique that uses a tree-like graph or model of decisions and their possible consequences to support selection of the best of several alternative courses of action. Alternative paths through the project are shown in the decision tree using branches representing different decisions or events, each of which can have associated costs and related individual project risks (including both threats and opportunities). The end-points of branches in the decision tree represent the outcome from following that particular path, which can be negative or positive.

Decision Tree

Decision Tree Example

Used in:

Perform Quantitative Risk Analysis (P)

A

Decision Tree Analysis

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7
Q

A data analysis technique consists of reviewing and assessing any relevant documented information.

Used in:

Identify Stakeholders (I)
Collect Requirements (P)
Identify Risks (P)
Manage Quality (E)
Close Project or Phase (C)
A

Document analysis

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8
Q

A data analysis technique for measuring the amount of work performed. The core elements of the EVT are:

Actual Cost (AC)
Planned Value (PV)
Earned Value (EV)
Using the values for the elements above you can work out:
Schedule Variance (SV)
Cost Variance (CV)
Schedule Performance Index (SPI)
Cost Performance Index (CPI)
Estimate at Completion (EAC)
Budget at Completion (BAC)
Variance at Completion (VAC)
Estimate to Complete (ETC)
To Complete Performance Index (TCPI)
Used in:
Monitor and Control Project Work (M&C)
Control Schedule (M&C)
Control Costs (M&C)
Control Procurements (M&C)
A

Earned value analysis

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9
Q

A data analysis technique using graphical aids to assist “decision making” under uncertainty.

Used in:

Perform Quantitative Risk Analysis (P)

A

Influence Diagram

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10
Q

A data analysis technique that uses a chart to track the work that remains to be completed in the iteration backlog.

Used in:

Control Schedule (M&C)

A

iteration burndown chart

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11
Q

A data analysis technique used in procurement management to determine what to buy based on capability, capacity, control, proprietary information, and budget.

Used in:

Plan Procurement Management (P)

A

Make-or-Buy Analysis

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12
Q

A technique that is used to measure, compare, and analyze actual performance of work in progress against the baseline.

Used in:

Control Schedule (M&C)
Control Quality (M&C)
Control Resources (M&C)
Control Procurements (M&C)
A

Performance Reviews

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13
Q

Identifying opportunities for process improvements.

Used in:

Manage Quality (E)

A

Process analysis

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14
Q

TA data analysis technique used in procurement processes to ensure proposals are complete and respond in full to the requirements as specified in the bid package.

Used in:

Conduct Procurements (E)

A

Proposal Evaluation Techniques

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15
Q

A data analysis technique used in the closing project processes to analyze the interrelationships between different project variables that contributed to the project outcomes to improve performance on future projects.

Used in:

Close Project or Phase (C)

A

Regression Analysis

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16
Q

A data analysis technique to establish a reserve for the project schedule and cost.

Used in:

Estimate Activity Durations (P)
Estimate Costs (P)
Determine Budget (P)
Control Costs (M&C)
Monitor Risks (M&C)
A

Reserve Analysis

17
Q

A data analysis technique used to assess the reliability of the data that has led to the qualitative risk assessment.

Used in:

Perform Qualitative Risk Analysis (P)

A

Risk Data Quality Assessment

18
Q

A data analysis technique used to assess each identified risk for the probability that it will occur and the impact that it will have if it does occur.

Used in:

Perform Qualitative Risk Analysis (P)

A

Risk probability and impact assessment

19
Q

A data analysis technique to determine the basic underlying reason that causes a variance, defect, or risk.

Used in:

Identify Risks (P)
Plan Stakeholder Engagement (P)
Manage Quality (E)
Monitor and Control Project Work (M&C)
Control Quality (M&C)
Monitor Stakeholder Engagement (M&C)
A

Root Cause Analysis

A root cause may underlie more than one variance, defect, or risk.

20
Q

A data analysis technique in which key quantitative assumptions and computations are changed systematically to assess their effect on the final outcome. Employed commonly in evaluation of the overall risk or in identification of critical factors, it attempts to predict alternative outcomes of the same course of action.

See also what-if analysis.

Used in:

Perform Quantitative Risk Analysis (P)

A

Sensitivity Analysis

21
Q

A data analysis technique commonly used in risk management. In quantitative risk analysis, this involves the use of a model that simulates the combined effects of individual project risks and other sources of uncertainty to evaluate their potential impact on achieving project objectives. Simulations are typically performed using a Monte Carlo analysis.

Used in:

Develop Schedule (P)
Perform Quantitative Risk Analysis (P)
A

Simulation

22
Q

A data analysis technique to analyze a list of stakeholders and determine relevant information such as their positions in the organization, roles on the project, expectations, attitudes (their levels of support for the project), and their interest in information about the project.

Used in:

Identify Stakeholders (I)
Plan Risk Management (P)
Monitor Stakeholder Engagement (M&C)

A

Stakeholder Analysis

23
Q

A data analysis technique that examines the project from the perspectives of strengths, weaknesses, opportunities, and threats to identify risks.

Used in:

Identify Risks (P)

A

SWOT Analysis

24
Q

A data analysis technique used in risk processes to compare technical accomplishments during project execution to the schedule of technical achievement.

Used in:

Monitor Risks (M&C)

A

Technical performance analysis

25
Q

A data analysis technique used in controlling processes to forecast future performance based on past results.

Used in:

Monitor and Control Project Work (M&C)
Control Scope (M&C)
Control Schedule (M&C)
Control Costs (M&C)
Control Resources (M&C)
Control Procurements (M&C)
Close Project or Phase (C)
A

Trend Analysis

26
Q

A data analysis technique used to review the differences between planned and actual performance.

Used in:

Monitor and Control Project Work (M&C)
Control Scope (M&C)
Control Schedule (M&C)
Control Costs (M&C)
Close Project or Phase (C)
A

Variance Analysis

27
Q

A data analysis technique that employs different qualitative assumptions (associated with probable events or phenomenon) to paint different scenarios, and tries to come up with the most optimal responses under the circumstances.

Also called contingency analysis.

See also sensitivity analysis.

Used in:

Develop Schedule (P)
Control Schedule (M&C)
A

What-If Scenario Analysis

PMP - Study Guide (40 decks)

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