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IIBA-AAC Agile Analyst

Test Detail:
The IIBA-AAC (Agile Analyst) exam is offered by the International Institute of Business Analysis (IIBA) and is designed to assess the knowledge and skills of professionals working as Agile Analysts. The exam focuses on various aspects of agile methodologies, agile analysis, and collaboration within agile teams.

Course Outline:
The Agile Analyst course provides comprehensive training on agile principles, practices, and techniques, with a specific focus on the role of the analyst within an agile environment. The course covers syllabus such as agile methodologies, agile requirements management, user stories, backlog grooming, and collaboration techniques. The following is a general outline of the key syllabus covered:

1. Introduction to Agile Analysis:
- Understanding agile principles and values.
- Roles and responsibilities in agile teams.
- Agile planning and estimation techniques.

2. Agile Requirements Management:
- Techniques for eliciting and capturing requirements in agile projects.
- User stories and acceptance criteria.
- Backlog management and prioritization.
- Agile requirements documentation.

3. Agile Analysis Techniques:
- Facilitation techniques for agile workshops and meetings.
- Collaboration and communication in agile teams.
- Analyzing and decomposing user stories.
- Agile modeling and prototyping.

4. Agile Team Collaboration:
- Building effective agile teams.
- Stakeholder engagement and communication.
- Agile testing and quality assurance.
- Continuous improvement and retrospectives.

Exam Objectives:
The IIBA-AAC exam assesses the candidate's knowledge and skills in the following areas:

1. Agile Principles and Mindset:
- Understanding and applying agile principles.
- Embracing an agile mindset and values.
- Incorporating customer-centricity in agile analysis.

2. Agile Analysis Techniques:
- Eliciting, analyzing, and prioritizing requirements in an agile context.
- Utilizing techniques such as user stories, story mapping, and backlog grooming.
- Applying agile modeling and prototyping techniques.

3. Agile Practices and Methods:
- Understanding different agile methodologies (e.g., Scrum, Kanban).
- Participating effectively in agile ceremonies and rituals.
- Collaborating with cross-functional agile teams.

4. Agile Team and Stakeholder Engagement:
- Facilitating effective communication and collaboration in agile teams.
- Engaging stakeholders throughout the agile project lifecycle.
- Supporting agile testing and quality assurance activities.

Exam Syllabus:
The IIBA-AAC exam syllabus provides a detailed breakdown of the syllabus covered in the exam. It includes specific knowledge areas, tasks, and techniques that candidates are expected to understand and apply. The syllabus may cover the following areas:

- Agile Mindset and Principles
- Agile Analysis and Planning
- Elicitation and Collaboration in Agile
- Requirements Life Cycle Management
- Strategy Analysis in Agile
- Requirements Analysis and Design Definition
- Solution Evaluation
Agile Analyst
IIBA Analyst information source

Other IIBA exams

CBAP Certified Business Analysis Professional 2023
CCBA Certification of Competency in Business Analysis
IIBA-AAC Agile Analyst
ECBA Entry Certificate in Business Analysis

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Agile Analyst
Through ongoing collaboration with stakeholders the team continues to uncover new information. This is leading to changes to the products that are being produced. The team should:
A. Stop all work until stakeholders can decide what they need
B. Schedule additional review sessions to speed up stake holder decisions
C. Accept all changes but delay additional solution development work to minimize rework
D. Continue as is since the process is working
Correct Answer: B
During a backlog refinement meeting, the team uses the appropriate technique to focus discussion on backlog items and their:
A. Technical designs and related details
B. Related users, user goals, user activities and their importance
C. Estimates determined by the delivery teamD. Resource requirements and availability for work.
Correct Answer: D
QUESTION 78 While reviewing criteria for a well-written story, the team discusses the
following criteria:
A. Detailed persona characteristics
B. Cost-benefit valuation
C. Alignment to the organization’s vision statement
D. Achievable unit of development
Correct Answer: D
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (55)
The team is discussing the initiative and thinking about what solution increments are worth doing. An appropriate technique for them to use is:
A. Backlog refinement
B. Portfolio kanban
C. Purpose alignment model
D. Story elaboration
Correct Answer: B
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (39)
QUESTION 80 While using Kano Analysis to determine what features to include in the MVP, the delivery team decides to include characteristics which if omitted will cause intense dissatisfaction. A team member indicates that these are
referred to as:
A. Performance characteristics
B. Threshold characteristics
C. Minimum characteristics
D. Excitement characteristics
Correct Answer: B
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (74)
The team is discussing what analysis performed at the initiative level should include. They realize this analysis will support a number of key decisions, particularly decisions around the:
A. Needs and the solution that will satisfy those needs
B. Objectives and strategies to meet those objectives
C. Problem and the system that will address that problem
D. Strategy and identifying actions that will address that strategy
Correct Answer: A
Good analysis practices at the Strategy Horizon facilitate the transfer of relevant knowledge between teams to:
A. Better understand what features will be delivered
B. Cancel initiatives that no longer provide value
C. Stimulate collaboration and continuous improvement.
D. Prioritize and sequence features for delivery
Correct Answer: C
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (38)
The team is considering which of several solution paths they should invest in. They are working only from conjecture and opinion, not data and facts. A practitioner with an agile mindset would remind them to:
A. Perform a value analysis of real options
B. Discover what works by trying things out
C. Consider analysis at multiple horizons
D. Collaborate more to create new ideas
Correct Answer: C
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (24)
The team is struggling with how to best design and explore options for moving forward. They settle on a time-boxed research approach which is often referred to as a:
A. Simulation
B. Wasteful
C. Spike
D. Incremental
Correct Answer: C
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (99)
QUESTION 85 At the Initiative Horizon, we see the concept of adaptive planning expressed when a
solution owner:
A. Ensures technical documentation is updated in response to changes
B. Seeks guidance and direction from senior stakeholders for remaining work
C. Uses feedback to make decisions about remaining solution components or initiatives
D. Meets with stakeholders to gather feedback about delivered solution components
Correct Answer: C
Reference: https://www.agilealliance.org/wp-content/uploads/2017/08/AgileExtension_V2-Member-Copy.pdf (29)
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IIBA Analyst information source - BingNews https://killexams.com/pass4sure/exam-detail/IIBA-AAC Search results IIBA Analyst information source - BingNews https://killexams.com/pass4sure/exam-detail/IIBA-AAC https://killexams.com/exam_list/IIBA Sources of Information for SWOT Analysis

Kenneth Oster's leadership experience includes an Air Force career, pastoral leadership, and business ownership in the automotive repair industry. He has a MBA from Western Governors University, and is working toward a DBA degree from Northcentral University. Oster authored the book, "The Complete Guide to Preserving Meat, Fish and Game: Step-by-Step Instructions to Freezing, Canning, Curing and Smoking."

Tue, 21 Aug 2012 09:05:00 -0500 en-US text/html https://smallbusiness.chron.com/sources-information-swot-analysis-52495.html
SWOT Analysis: How To With Table and Example

What Is SWOT Analysis?

SWOT (strengths, weaknesses, opportunities, and threats) analysis is a framework used to evaluate a company's competitive position and to develop strategic planning. SWOT analysis assesses internal and external factors, as well as current and future potential.

A SWOT analysis is designed to facilitate a realistic, fact-based, data-driven look at the strengths and weaknesses of an organization, initiatives, or within its industry. The organization needs to keep the analysis accurate by avoiding pre-conceived beliefs or gray areas and instead focusing on real-life contexts. Companies should use it as a guide and not necessarily as a prescription.

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Key Takeaways

  • SWOT analysis is a strategic planning technique that provides assessment tools.
  • Identifying core strengths, weaknesses, opportunities, and threats leads to fact-based analysis, fresh perspectives, and new ideas.
  • A SWOT analysis pulls information internal sources (strengths of weaknesses of the specific company) as well as external forces that may have uncontrollable impacts to decisions (opportunities and threats).
  • SWOT analysis works best when diverse groups or voices within an organization are free to provide realistic data points rather than prescribed messaging.
  • Findings of a SWOT analysis are often synthesized to support a single objective or decision that a company is facing.

Investopedia / Xiaojie Liu

Understanding SWOT Analysis

SWOT analysis is a technique for assessing the performance, competition, risk, and potential of a business, as well as part of a business such as a product line or division, an industry, or other entity.

Using internal and external data, the technique can guide businesses toward strategies more likely to be successful, and away from those in which they have been, or are likely to be, less successful. Independent SWOT analysts, investors, or competitors can also guide them on whether a company, product line, or industry might be strong or weak and why.

SWOT analysis was first used to analyze businesses. Now, it's often used by governments, nonprofits, and individuals, including investors and entrepreneurs. There is seemingly limitless applications to the SWOT analysis.

Components of SWOT Analysis

Every SWOT analysis will include the following four categories. Though the elements and discoveries within these categories will vary from company to company, a SWOT analysis is not complete without each of these elements:


Strengths describe what an organization excels at and what separates it from the competition: a strong brand, loyal customer base, a strong balance sheet, unique technology, and so on. For example, a hedge fund may have developed a proprietary trading strategy that returns market-beating results. It must then decide how to use those results to attract new investors.


Weaknesses stop an organization from performing at its optimum level. They are areas where the business needs to Strengthen to remain competitive: a weak brand, higher-than-average turnover, high levels of debt, an inadequate supply chain, or lack of capital.


Opportunities refer to favorable external factors that could supply an organization a competitive advantage. For example, if a country cuts tariffs, a car manufacturer can export its cars into a new market, increasing sales and market share.


Threats refer to factors that have the potential to harm an organization. For example, a drought is a threat to a wheat-producing company, as it may destroy or reduce the crop yield. Other common threats include things like rising costs for materials, increasing competition, tight labor supply. and so on.

SWOT Table

Analysts present a SWOT analysis as a square segmented into four quadrants, each dedicated to an element of SWOT. This visual arrangement provides a quick overview of the company’s position. Although all the points under a particular heading may not be of equal importance, they all should represent key insights into the balance of opportunities and threats, advantages and disadvantages, and so forth.

The SWOT table is often laid out with the internal factors on the top row and the external factors on the bottom row. In addition, the items on the left side of the table are more positive/favorable aspects, while the items on the right are more concerning/negative elements.

How to Do a SWOT Analysis

A SWOT analysis can be broken into several steps with actionable items before and after analyzing the four components. In general, a SWOT analysis will involve the following steps.

Step 1: Determine Your Objective

A SWOT analysis can be broad, though more value will likely be generated if the analysis is pointed directly at an objective. For example, the objective of a SWOT analysis may focused only on whether or not to perform a new product rollout. With an objective in mind, a company will have guidance on what they hope to achieve at the end of the process. In this example, the SWOT analysis should help determine whether or not the product should be introduced.

Step 2: Gather Resources

Every SWOT analysis will vary, and a company may need different data sets to support pulling together different SWOT analysis tables. A company should begin by understanding what information it has access to, what data limitations it faces, and how reliable its external data sources are.

In addition to data, a company should understand the right combination of personnel to have involved in the analysis. Some staff may be more connected with external forces, while various staff within the manufacturing or sales departments may have a better grasp of what is going on internally. Having a broad set of perspectives is also more likely to yield diverse, value-adding contributions.

Step 3: Compile Ideas

For each of the four components of the SWOT analysis, the group of people assigned to performing the analysis should begin listing ideas within each category. Examples of questions to ask or consider for each group are in the table below.

Internal Factors

What occurs within the company serves as a great source of information for the strengths and weaknesses categories of the SWOT analysis. Examples of internal factors include financial and human resources, tangible and intangible (brand name) assets, and operational efficiencies.

Potential questions to list internal factors are:

  • (Strength) What are we doing well?
  • (Strength) What is our strongest asset?
  • (Weakness) What are our detractors?
  • (Weakness) What are our lowest-performing product lines?

External Factors

What happens outside of the company is equally as important to the success of a company as internal factors. External influences, such as monetary policies, market changes, and access to suppliers, are categories to pull from to create a list of opportunities and weaknesses.

Potential questions to list external factors are:

  • (Opportunity) What trends are evident in the marketplace?
  • (Opportunity) What demographics are we not targeting?
  • (Threat) How many competitors exist, and what is their market share?
  • (Threat) Are there new regulations that potentially could harm our operations or products?
1. What is our competitive advantage?
2. What resources do we have?
3. What products are performing well?
1. Where can we improve?
2. What products are underperforming?
3. Where are we lacking resources?
1. What new technology can we use?
2. Can we expand our operations?
3. What new segments can we test?
1. What regulations are changing?
2. What are competitors doing?
3. How are consumer trends changing?

Companies may consider performing this step as a "white-boarding" or "sticky note" session. The idea is there is no right or wrong answer; all participants should be encouraged to share whatever thoughts they have. These ideas can later be discarded; in the meantime, the goal should be to come up with as many items as possible to invoke creativity and inspiration in others.

Step 4: Refine Findings

With the list of ideas within each category, it is now time to clean-up the ideas. By refining the thoughts that everyone had, a company can focus on only the best ideas or largest risks to the company. This stage may require substantial debate among analysis participants, including bringing in upper management to help rank priorities.

Step 5: Develop the Strategy

Armed with the ranked list of strengths, weaknesses, opportunities, and threats, it is time to convert the SWOT analysis into a strategic plan. Members of the analysis team take the bulleted list of items within each category and create a synthesized plan that provides guidance on the original objective.

For example, the company debating whether to release a new product may have identified that it is the market leader for its existing product and there is the opportunity to expand to new markets. However, increased material costs, strained distribution lines, the need for additional staff, and unpredictable product demand may outweigh the strengths and opportunities. The analysis team develops the strategy to revisit the decision in six months in hopes of costs declining and market demand becoming more transparent.

Use a SWOT analysis to identify challenges affecting your business and opportunities that can enhance it. However, note that it is one of many techniques, not a prescription.

Benefits of SWOT Analysis

A SWOT analysis won't solve every major question a company has. However, there's a number of benefits to a SWOT analysis that make strategic decision-making easier.

  • A SWOT analysis makes complex problems more manageable. There may be an overwhelming amount of data to analyze and relevant points to consider when making a complex decision. In general, a SWOT analysis that has been prepared by paring down all ideas and ranking bullets by importance will aggregate a large, potentially overwhelming problem into a more digestible report.
  • A SWOT analysis requires external consider. Too often, a company may be tempted to only consider internal factors when making decisions. However, there are often items out of the company's control that may influence the outcome of a business decision. A SWOT analysis covers both the internal factors a company can manage and the external factors that may be more difficult to control.
  • A SWOT analysis can be applied to almost every business question. The analysis can relate to an organization, team, or individual. It can also analyze a full product line, changes to brand, geographical expansion, or an acquisition. The SWOT analysis is a versatile tool that has many applications.
  • A SWOT analysis leverages different data sources. A company will likely use internal information for strengths and weaknesses. The company will also need to gather external information relating to broad markets, competitors, or macroeconomic forces for opportunities and threats. Instead of relying on a single, potentially biased source, a good SWOT analysis compiles various angles.
  • A SWOT analysis may not be overly costly to prepare. Some SWOT reports do not need to be overly technical; therefore, many different staff members can contribute to its preparation without training or external consulting.

SWOT Analysis Example

In 2015, a Value Line SWOT analysis of The Coca-Cola Company noted strengths such as its globally famous brand name, vast distribution network, and opportunities in emerging markets. However, it also noted weaknesses and threats such as foreign currency fluctuations, growing public interest in "healthy" beverages, and competition from healthy beverage providers.

Its SWOT analysis prompted Value Line to pose some tough questions about Coca-Cola's strategy, but also to note that the company "will probably remain a top-tier beverage provider" that offered conservative investors "a reliable source of income and a bit of capital gains exposure."

Five years later, the Value Line SWOT analysis proved effective as Coca-Cola remains the 6th strongest brand in the world (as it was then). Coca-Cola's shares (traded under ticker symbol KO) have increased in value by over 60% during the five years after the analysis was completed.

To get a better picture of a SWOT analysis, consider the example of a fictitious organic smoothie company. To better understand how it competes within the smoothie market and what it can do better, it conducted a SWOT analysis. Through this analysis, it identified that its strengths were good sourcing of ingredients, personalized customer service, and a strong relationship with suppliers. Peering within its operations, it identified a few areas of weakness: little product diversification, high turnover rates, and outdated equipment.

Examining how the external environment affects its business, it identified opportunities in emerging technology, untapped demographics, and a culture shift towards healthy living. It also found threats, such as a winter freeze damaging crops, a global pandemic, and kinks in the supply chain. In conjunction with other planning techniques, the company used the SWOT analysis to leverage its strengths and external opportunities to eliminate threats and strengthen areas where it is weak.

What Is SWOT Analysis?

SWOT (strengths, weaknesses, opportunities, and threats) analysis is a method for identifying and analyzing internal strengths and weaknesses and external opportunities and threats that shape current and future operations and help develop strategic goals. SWOT analyses are not limited to companies. Individuals can also use SWOT analysis to engage in constructive introspection and form personal improvement goals.

What Is an Example of SWOT Analysis?

Home Depot conducted a SWOT analysis, creating a balanced list of its internal advantages and disadvantages and external factors threatening its market position and growth strategy. High-quality customer service, strong brand recognition, and positive relationships with suppliers were some of its notable strengths; whereas, a constricted supply chain, interdependence on the U.S. market, and a replicable business model were listed as its weaknesses.

Closely related to its weaknesses, Home Depot's threats were the presence of close rivals, available substitutes, and the condition of the U.S. market. It found from this study and other analysis that expanding its supply chain and global footprint would be key to its growth.

What Are the 4 Steps of SWOT Analysis?

The four steps of SWOT analysis comprise the acronym SWOT: strengths, weaknesses, opportunities, and threats. These four aspects can be broken into two analytical steps. First, a company assesses its internal capabilities and determines its strengths and weaknesses. Then, a company looks outward and evaluates external factors that impact its business. These external factors may create opportunities or threaten existing operations.

How Do You Write a Good SWOT Analysis?

Creating a SWOT analysis involves identifying and analyzing the strengths, weaknesses, opportunities, and threats of a company. It is recommended to first create a list of questions to answer for each element. The questions serve as a guide for completing the SWOT analysis and creating a balanced list. The SWOT framework can be constructed in list format, as free text, or, most commonly, as a 4-cell table, with quadrants dedicated to each element. Strengths and weaknesses are listed first, followed by opportunities and threats.

Why Is SWOT Analysis Used?

A SWOT analysis is used to strategically identify areas of improvement or competitive advantages for a company. In addition to analyzing thing that a company does well, SWOT analysis takes a look at more detrimental, negative elements of a business. Using this information, a company can make smarter decisions to preserve what it does well, capitalize on its strengths, mitigate risk regarding weaknesses, and plan for events that may adversely affect the company in the future.

The Bottom Line

A SWOT analysis is a great way to guide business-strategy meetings. It's powerful to have everyone in the room discuss the company's core strengths and weaknesses, define the opportunities and threats, and brainstorm ideas. Oftentimes, the SWOT analysis you envision before the session changes throughout to reflect factors you were unaware of and would never have captured if not for the group’s input.

A company can use a SWOT for overall business strategy sessions or for a specific segment such as marketing, production, or sales. This way, you can see how the overall strategy developed from the SWOT analysis will filter down to the segments below before committing to it. You can also work in reverse with a segment-specific SWOT analysis that feeds into an overall SWOT analysis.

Although a useful planning tool, SWOT has limitations. It is one of several business planning techniques to consider and should not be used alone. Also, each point listed within the categories is not prioritized the same. SWOT does not account for the differences in weight. Therefore, a deeper analysis is needed, using another planning technique.

Wed, 31 Mar 2021 00:17:00 -0500 en text/html https://www.investopedia.com/terms/s/swot.asp
Management Information Systems Flowchart

Year 1



Co - Curricular Unit

 See options for PE credits here.

Year 2



Year 3



MIS 3200 - Systems Analysis and Design

Provides an understanding of the IS development and modification process and the evaluation choices of a system development methodology. Emphasizes effective communication with users and team members and others associated with the development and maintenance of the information system. Stresses analysis and logical design of departmental-level information system.

  • Credits: 3.0
  • Lec-Rec-Lab: (0-3-0)
  • Semesters Offered: Spring
  • Pre-Requisite(s): MIS 2000(C) or MIS 2100(C) or CS 1122 or CS 1131

Year 4



MIS 4100 - Information Systems Projects

MIS capstone course. Applies IS practices and artifacts as solutions to business problems using student-led project teams under faculty supervision. Students develop a working prototype of a business solution using good design and management practices.

  • Credits: 3.0
  • Lec-Rec-Lab: (0-3-0)
  • Semesters Offered: Spring
  • Restrictions: Must be enrolled in one of the following Class(es): Senior
  • Pre-Requisite(s): (MIS 2100 and MIS 3100 and MIS 3200) or (CS 2321 and CS 3141 and CS 3425) or (MIS 2100 and MIS 3100 and MA 3720)

Major Electives

Domain Electives

Download the Flowchart

Tue, 10 Nov 2020 22:01:00 -0600 en text/html https://www.mtu.edu/business/undergraduate/advising/requirements/major-flowcharts/mis-flowchart/
Information Security Analyst No result found, try new keyword!Information security analysts are responsible for protecting information in an organization’s computer systems from data breaches and cyberattacks. Since lots of sensitive data is stored ... Wed, 24 May 2023 04:00:00 -0500 https://money.usnews.com/careers/best-jobs/information-security-analyst Fox News Voter Analysis

Mon, 26 Dec 2022 22:05:00 -0600 Fox News en text/html https://www.foxnews.com/elections/2022/midterm-results/voter-analysis How To Overcome The 'Analysis Paralysis' Of Decision-Making

Nobody likes being wrong. The need to feel valued is an intrinsic human desire that manifests itself through the choices we make and how we communicate those choices to others. When it comes to making a decision, it’s natural to want to be “right.” After all, making the wrong statement or otherwise contributing in a wrongful way is about as fun as failing at a competitive sport (remember Martina Navratilova's quote: "whoever said, 'it's not whether you win or lose that counts,' probably lost.").

Decision-making is similar insofar as the choices you make are a reflection of the values, beliefs, morals and intentions that not only shape your behavior, but also identify you as a person as well impact others.

What, then, do you do in today’s world where there is so much information to navigate? After all, trying to stay up to date with the latest viewpoints and updates is akin to the human version of an information hamster wheel: you can run along it all day but never actually arrive anywhere. Rather, it’s up to you to decide when to stop.

To help avoid the pitfalls of analysis paralysis, here are five considerations to keep in mind when inundated with so many bright, shiny balls of information:

Set a “drop dead” date. In today’s interconnected world, nobody makes decisions in a vacuum. In other words, the decisions made by one leader have vertical and horizontal effects both internal and external to the organization, and if people or departments are waiting on you then progress is at a stalemate. Determine the last possible timeframe by which a decision must either be made or removed from the decision-making table.

Get a sanity check. Including others in the decision making process serves multiple purposes. First, it shares your thought process as a leader and thus serves as a coaching tool for up-and-comers. After all, what leader doesn’t want to Strengthen his/her people? (Well, the toxic ones, that’s who). Second, you build diversity of thought that affords you greater context that only adds to your decision-making repertoire for next time. Now, I'm not advocating a democratic leadership style by any means--nor condoning one either, as leadership is situational. Obviously you can’t enlist alternative viewpoints all the time (i.e. when time is of the essence) but when you can, it only serves the effectiveness of the outcome.

Curb your curiosity. One of the culprits contributing to analysis paralysis are details; specifically, the desire to excavate deeper and deeper every new detail that arrives on scene. To satiate the intellectual curiosity that yearns for more information (and therefore stalls progress), set yourself parameters for what you need to know (now) and what you’d like to know (in the future). If the information you have now answers the call, it's time to move forward.

Recognize that the moons will never align. No matter how much information you have, there will always be more. Decisions will ever be optimal for this very reason—ever. There are, however, optimal moments during which decisions can be made. Remember, just because you arrive at one conclusion doesn’t mean you can never adapt to a new one.

Stair step your decisions. Rather than looking at the decision to be made as a one-time, main event, consider smaller yet actionable decisions that can be made now or that lead up to the main one. Even just the tiniest shift of momentum can have a positive snowball effect that wriggles you out of the paralysis associated with making the “perfect” decision.

In the military, Decisions are never final for the simple fact that change is never absolute. Rather, change is ongoing. To stay competitive and progress at the rate of change requires adaptive decisions that can be iterated and improved upon on the fly.

Fri, 20 Mar 2015 06:06:00 -0500 Jeff Boss en text/html https://www.forbes.com/sites/jeffboss/2015/03/20/how-to-overcome-the-analysis-paralysis-of-decision-making/
Information Management and Analysis

The IMA office of the Graduate School oversees all computer-related equipment and software applications, as well as electronic processes, within the Graduate School. This includes the Graduate School's website, and all associated sites, the POS generator, workshop registration, and all aspects of the Graduate School Database. The IMA staff also provides graduate student information and analytical support for departmental and University-wide data requests and reporting, including external surveys.

Wed, 12 Aug 2020 13:10:00 -0500 en text/html https://www.purdue.edu/gradschool/ima/index.html
What Is Statistical Analysis?

 Many businesses rely on statistical analysis to organize collected information and predict future trends based on that data. While organizations have lots of options on what to do with their big data, statistical analysis is a way to examine that data as a whole, as well as break it down into individual samples.

Statistical analysis is the cornerstone of successful business intelligence. We’ve put together the following primer to explain statistical analysis and how it can help your business grow, as well as some of the most popular statistical analysis tools you can use to get started. 

What is statistical analysis? 

Statistical analysis, or statistics, is the process of collecting and analyzing data to identify patterns and trends, remove bias and inform decision-making. It’s an aspect of business intelligence that involves the collection and scrutiny of business data and the reporting of trends.

There are several ways businesses can use statistical analysis to their advantage, including determining the top-performing product lines, identifying poorly performing sales staff and getting a sense of how sales performance varies among different regions of the country.

Statistical analytic tools can help with predictive modeling. Rather than show simple trend predictions that can be affected by a number of outside factors, statistical analysis tools allow businesses to dig deeper to see additional information. 

Statistical analysis helps you identify data trends and patterns. You can use this to achieve a better understanding of various aspects of your company, as well as to extrapolate potential future trends.

What are the types of statistical analysis?

There are two main types of statistical analysis: descriptive and inferential, also known as modeling.

Descriptive statistics

Descriptive statistics is what organizations use to summarize their data. This type typically involves summary charts, graphs and tables depicting the data for easier comprehension, rather than relying on raw, unorganized data. Among some of the useful data that comes from descriptive statistics are the mode, median and mean, as well as range, variance and standard deviation. That said, descriptive statistics are not meant to draw conclusions.

Inferential statistics

Inferential statistics offer a way to take the data from a representative trial and use it to draw larger truths. It allows organizations to extrapolate beyond the data set, going a step further than descriptive statistics. Statistical inference relies heavily on finding as representative a trial as possible from which to draw conclusions about a wider population. As there will always be uncertainty about extrapolating from a limited set of data to a wider population, statistical inference relies upon estimating uncertainty in predictions.

If you want to hire someone to handle statistical analysis for your business, consider candidates who have one of the top big data certifications. These certifications are hard evidence of their analytics skills.

The conclusions of a statistical inference are a statistical proposition. Some common forms of statistical proposition include the following.

  • Estimates: An estimate is a particular value that best approximates some parameter of interest.
  • Confidence interval: An interval constructed using a data set drawn from a population so that, under repeated sampling of such data sets, such intervals would contain the true parameter value with the probability at the stated confidence level is defined as a confidence interval. In other words, the confidence interval is a measure of how well the model predicts the data that is actually recorded.
  • Credible intervals: A set of values containing, for example, 95% of posterior belief is referred to as a credible interval. It’s a way of standardizing confidence intervals. When you read about a study with 95% confidence, they are referencing a credible interval.

Descriptive statistics are used to describe data, while inferential statistics are used to infer conclusions and hypotheses about the same information.

What are the benefits of statistical analysis?

Is it really worth investing in big data and statistical analysis? The best way to answer that question is to explore the benefits. 

In general, statistics can help business owners identify trends that would escape notice without these methods. The analysis also injects objectivity into decision-making. With good statistics, gut decisions are not necessary. [Read related article: Techniques and Tools to Help You Make Business Decisions]

Here are some of the specific business benefits of using statistical analysis.

Cut operating costs.

Statistical analysis can help companies more accurately analyze their data and costs, as well as recognize spending trends. After accurately identifying this information, businesses can extrapolate insights about potential future costs or cost-saving techniques to limit spending and cut waste. 

Say you lease a vending machine in your lobby for clients and employees to enjoy drinks and snacks, but you aren’t sure if it’s getting enough use to justify the expense. A statistical analysis can help you quantify the frequency of purchases and the amount of money brought in versus the cost of the machine and the price of keeping it stocked. You may find the machine isn’t getting much use and it’s an expense you can cut from your budget without negatively impacting your operations.

Perform market analysis.

Statistical analysis can also help businesses perform accurate market analysis. The data can show where the most sales happen, where the sales have the most value and what marketing is attached to those sales. It allows for improved efficiency in every aspect of sales and marketing.

Consider a business owner with a successful café who is looking to open a second location. The company could perform a market analysis to come up with estimates of how much foot traffic there may be in a certain neighborhood, how much disposable income the residents of the area may possess, and what tastes the potential patrons may have. This information paints a clear picture of the possible location’s viability, allowing the business owner to make an educated decision.

Business intelligence and market intelligence can work hand in hand to provide valuable insights about your company’s internal and external operations.

Boost workplace efficiency.

Statistical analysis can Strengthen work efficiency. For example, we know that providing the right tools can get the best work out of employees. Statistical analysis can help employers scrutinize each tool’s efficacy to focus on those that drive the best performance. Business leaders can also use statistical analysis to identify variables that may help or harm workplace efficiency, such as whether or not co-workers eat lunch together or participate in employee networking events.

A particularly useful instance of employing statistical analysis to analyze workplace efficiency would be measuring employee output after adopting a new tool or practice. For example, a company could see whether adopting workplace virtualization increases worker efficiency. 

Improve decision-making.

Statistical analysis is the backbone of business intelligence and informed decision-making. Descriptive statistics paired with A/B testing provides a clear view into what choices resonate with clients or leads. This is particularly important for companies seeking to grow their offerings or client lists, as well as for businesses that don’t have a steady stable of clients. 

Every major business decision should be made only after testing the idea and reviewing the data. Website redesign is one example of this. Instead of launching a brand-new site, a business should first soft-launch a potential new design to select visitors in an A/B test. The organization can use this process to gather insightful information such as the duration of site visits, potential click-throughs, and whether sales increased or decreased with the new design. Then, they can use statistical analysis to compare these values to the old site and see whether the redesign should be fully rolled out, tweaked further or scrapped altogether. 

What is statistical analysis software?

Since not everyone is a mathematical genius who can easily compute the needed statistics on the mounds of data a company acquires, most organizations use some form of statistical analysis software. This software can deliver the specific analysis an organization needs to better its business.

Such software is able to quickly and easily generate charts and graphs when conducting descriptive statistics while at the same time running the more sophisticated computations that are required when conducting inferential statistics.

The more popular statistical analysis software services include IBM’s SPSS, SAS, Revolution Analytics’ R, Minitab, Stata and Tableau, which is now part of Salesforce. You can learn more about the latter vendor in our review of the Salesforce CRM.

Software features

The two most important features of statistical software are analysis and presentation. Analysis features include statistical tools that do the heavy lifting when it comes to calculations. Typical analytical functions include standard modeling, confidence intervals and probability calculations. They provide the core value of statistical software and are the primary reason to invest in such systems in the first place. Despite that, analytical features should not be your primary concern when shopping for statistical analysis software.

Presentation is arguably more important. This is what populates charts and graphs. It allows for real-time reporting and all of the visual features that make the statistical results accessible. Statistical presentation should always be a major consideration when choosing statistical analysis software.

What is the importance of statistical analysis and business intelligence?

Business intelligence, of which statistical analysis is just one part, is critical for sustainability. A business owner who isn’t regularly taking stock of their enterprise cannot adequately address problems, replicate success, or plan for the future. Companies should regularly conduct self-assessments for a better understanding of the organization. In addition to statistical analysis, we recommend doing a Pareto analysis to Strengthen efficiency and decision-making.

Chad Brooks contributed to the writing and reporting in this article. 

Sun, 12 Nov 2023 09:59:00 -0600 en text/html https://www.businessnewsdaily.com/6000-statistical-analysis.html
The Importance of Information Sources at the Workplace

Lainie Petersen writes about business, real estate and personal finance, drawing on 25 years experience in publishing and education. Petersen's work appears in Money Crashers, Selling to the Masses, and in Walmart News Now, a blog for Walmart suppliers. She holds a master's degree in library science from Dominican University.

Wed, 18 Jul 2018 17:18:00 -0500 en-US text/html https://smallbusiness.chron.com/importance-information-sources-workplace-13809.html
Ph.D. in Behavior Analysis

ABAI Accreditation Doctoral SealABAI VCS program sealABAI VCS Virtual Course Sequence program seal

The Association for Behavior Analysis International has Tested the following courses toward the coursework requirements for eligibility to take the Board Certified Behavior Analyst® or Board Certified Assistant Behavior Analyst® examination. Applicants will need to meet additional requirements before they can be deemed eligible to take the examination.

University of Nevada, Reno Mission Statement:

Inspired by its land-grant foundation, the University of Nevada, Reno provides outstanding learning, discovery, and engagement programs that serve the economic, social, environmental, and cultural needs of the citizens of Nevada, the nation, and the world.  The University recognizes and embraces the critical importance of diversity in preparing students for global citizenship and is committed to a culture of excellence, inclusion, and accessibility.

The philosophy and program

The aim of the Behavior Analysis Program is to provide comprehensive training in behavior analysis, out of which more specialized basic, applied, and theoretical interests can be developed. A balance of basic, applied, and theoretical training is sought. The faculty and students strive to:

  • Preserve the accumulated knowledge of behavior science by imparting it to others.
  • Develop the science of behavior through the production of new knowledge.
  • Contribute to the betterment of society by the application of this knowledge.
  • Assure the viability of the profession through participation in its governance.

Behavior analysis is an approach to psychology emphasizing the study of behavior in its historical and situational contexts. Behavior analysis training at the University of Nevada, Reno is conducted via a junior-colleague model and includes supervised experience and instruction in:

  • Philosophies of behaviorism
  • Theory and methodology of behavior analysis
  • Basic and applied research in human behavior
  • Basic research in animal behavior
  • Application of behavioral principles to organizational administration and consultation, instructional design and technology, parent and teacher training, and clinical populations
  • Participatory governance and fiscal management

Here are just a few reasons why you should apply to the University of Nevada, Reno Behavior Analysis Program:

  • The success of our program depends on the students and faculty cooperating with one another and therefore our community of students and faculty make it a point to maintain a harmonious environment. We value cooperation over competition.
  • The Behavior Analysis Program operates in part on a self-capitalization plan. This means that the program is partially funded by the entrepreneurial efforts of the faculty and graduate students. Most of the resources for the program, including student support, staff support, equipment, and operations expenses are generated through these efforts. Moreover, the program follows an open-book management approach, and students are encouraged to take an active interest and role in the managerial and financial aspects of our programmatic services. Students work in these services to develop skills that will assist them in future careers. Although most students have been funded to date, funding is not guaranteed and must be arranged by the faculty Behavior Analysis Training Committee.
  • Behavior analysis is noted for its unique focus on historical and contextually situated behavior-environment relations. Its method is experimental, with aims of description, prediction, and influence over its subject matter. It is characterized by distinctive, widely applicable, and effective behavioral technologies that may be applied across a variety of areas of applications such as intellectual and developmental disabilities (including autism), performance management, behavioral systems analysis, cultural behavior analysis, and dissemination of behavior analysis. These areas of research and application are represented areas of training in the Behavior Analysis Program at UNR.

Degree programs

The University of Nevada, Reno Behavior Analysis Program is an entirely on-campus program that offers some of the best behavior analytic training in the world. Our program offers Master’s (M.S.) and Doctoral (Ph.D.) degrees. Off-campus training options in behavior analysis (M.S. and BCBA/BCaBA course sequences) are offered through a separate program operated by the Global Institute for Behavior Analysis. We take pride in the breadth of our research, the depth of our coursework, and the expertise of our faculty and students. Hear about our program from faculty and students in a podcast recorded by ABA Technologies.

Doctoral Program in Behavior Analysis

The University of Nevada, Reno doctoral program in Behavior Analysis trains graduates to teach, do research and work as consultants or administrators in the public and private sectors. This degree requires 89 graduate credits, is accredited by the Association for Behavior Analysis International (see our annual report data here ), and has a Board Certified Behavior Analyst (BCBA) Approved Course Sequence through the Behavior Analyst Certification Board. Below are links to the Doctoral Program Handbook describing degree requirements and trial syllabi:

List of Practicum Sites & Projects

  • FIT Learning
  • SPIN: Psychology 101
  • University of Nevada, Reno Medical School
  • Applied Behavior Science in Organizations
  • Spectrum Learning Center
  • Behavioral and Education Consultation Services (BECS) with Washoe County School District
  • NV Rural Regional Center
  • Animal Behavior Laboratory
  • Human Operant Laboratory

Learning Outcome Achievements

  • Annual reporting period: 2018-19
  • Number of students whose degrees were conferred by the program: 1
  • Median years until graduation for students whose degrees were conferred by the program: 8  
    • The number depicts the average years across the last 5 years of our doctoral training across different faculty members' labs. The doctoral degree is ordinarily achieved in six years (post-Bachelor degree).
  • Number of students enrolled in the program: 27
  • Number of students no longer enrolled for any reason other than conferral of degree: 0
  • Number of completed applications received: 28
  • Number of students admitted: 4
  • Median undergraduate grade point average (GPA) for applicants admitted (reported on a 4-point scale): 3.45
  • Median graduate grade point average (GPA) for applicants admitted (reported on a 4-point scale): 3.98
  • Median standardized test scores: GRE Verbal 155; GRE Quantitative 148; GRE Writing 4.8
  • Number of years to completion: Mean: 7 years; Median: 7 years; Range: 8 years

Academic Advising

When students enter the program, they are assigned to one of the core behavior analysis faculty who will serve as their academic advisor for the first semester of study or until an advisement arrangement with a research advisor is arranged. The student and advisor should work out a tentative program of study, including the transfer of previous graduate courses. The academic advisor also serves as the liaison between the student and the faculty Behavior Analysis Training Committee, as well as a source of support for counseling, tutoring, or other assistance.

Research Advising

Advisory responsibilities are assumed by the student's primary research advisor as soon as their interests develop. Students will be required to approach the faculty member with whom they wish to conduct their research prior to the beginning of the second semester. Upon receiving the permission of the faculty member, they will join their research laboratory.

Research Experiences

Applied Research in the Context of Service Delivery; Advancement of Evidence-Based Practice of ABA: Bethany Contreras

Our lab focuses on applied research in the context of service delivery, primarily for individuals with autism and other neurodevelopmental disabilities. This broad area of research includes lines of inquiry regarding reinforced variability and its role in problem-solving, enhancing the efficiency and fidelity of skill acquisition procedures, supporting families of individuals with autism, and promoting independent language, play, and daily living skills of individuals with autism. In addition to conducting clinical research with participants, our lab engages in scholarly work to promote Evidence-Based Practice of ABA through systematic literature reviews and publications geared towards practice recommendations.

Basic, Translational, and Interdisciplinary Research: Matthew Lewon

The work in this lab largely occurs in three interrelated research domains. The first is basic research pertaining to fundamental Pavlovian and operant learning processes, particularly in the areas of antecedent and contextual control of behavior. The second is translational, i.e., basic and conceptual research that is relevant to the application and applied research that informs our understanding of the basic principles of behavior. The third is an interdisciplinary collaboration with investigators outside of behavior science, with a particular interest in studying how physiological/biological variables interact with environmental variables during learning.

Complex Human Behavior: Linda Hayes

The scholarly work in our lab is focused on the philosophy of behavior science, its implications for the interpretation of complex human behavior, theory and experimental analyses of cultural events, and investigative work on basic processes in humans. Our research on human behavior covers a wide range of syllabus though usually has something to do with verbal behavior, or substitutional processes more generally. The research we do on cultural events looks at the evolution of symbolic systems and the logic of scientific systems concerned with understanding culture.

Contextual Psychology and Verbal Relations: Steve Hayes

The primary focus of this lab is on the development of a functional contextual account of human language and cognition, Relational Frame Theory, and its extension into behavioral, clinical, and evolution science. The lab is a vertically integrated scholarly team composed of undergraduates, graduate students, both junior and senior, and myself. At times postdoctoral trainees and sabbaticals join us as well.

Behavioral Systems Analysis, Organizational Behavior Management, & Cultural Behavior Analysis:  Ramona A. Houmanfar / Performance System Technologies Lab

The primary focus of our collaborative team is on the interdisciplinary developments and applications of behavioral systems analysis with an emphasis on verbal and communication networks in organizations. This focus has guided our conceptual and experimental work on implicit bias, cooperation, situational awareness, decision making, and value-based governance. The outcomes associated with these areas of scholarly work have contributed to our development of instructional design technologies and broad-scale training programs in the private and public sectors. 

Experimental Analysis of Behavior: Matthew Locey

The focus of this lab is on the experimental analysis of choice - particularly between alternatives that differ in reinforcement type, delay, magnitude, and/or probability. Current projects include both basic human operant and questionnaire-based studies. Planned expansions over the next three years include behavioral pharmacology with rodents and contingency management of gambling and drug use.


The Behavior Analysis program seeks students committed to a behavioral orientation in psychology, who show research and scholarly potential, and who show potential as teachers, scientists, and practitioners. Faculty members value ability and accomplishment in the selection process. Students learn a great deal from each other. Consequently, the program seeks a heterogeneous student population. Based on these values, students who are offered admission are accepted to the program before they become a part of a specific faculty member’s laboratory (see “Academic Advising" section above). Therefore, the applicants do not rank-order or specify their preferred faculty/lab groups and should prepare their applications accordingly.

To be considered for admission to the University of Nevada, Reno Behavior Analysis Program, interested applicants must meet the requirements and apply through The Graduate School.

Please see below for information on how to apply.

Application deadline: Our program has one admissions cycle per year. Applications are due December 1st for consideration for admission in August of the following year. Selected applicants will be invited to our Interview Weekend event in February.

Graduate School Admissions Requirements

  • Completed application for Graduate School Admission
  • Nonrefundable application fee
  • One copy of official transcripts from all universities and/or colleges attended
  • Official GRE scores (GENERAL SCORES ONLY)
  • Three letters of recommendation
  • A curriculum vitae (CV)
  • A brief statement of purpose

The Graduate School application process is entirely online. They organize and screen your application, along with obtaining any additional required information they might need from you. The Graduate School is your best source of information regarding the application process.

If you have questions about the graduate admissions process and associated requirements, please contact the Chair of Admissions Committee. Dr. Matthew Lewon

If you have questions regarding the application process and materials, please contact the Graduate School as they handle the entire application process.

International Student Admissions

The University of Nevada, Reno Behavior Analysis Program has a strong commitment to the international dissemination of behavior analysis and currently has several international students from various countries around the world seeking advanced degrees in behavior analysis. Qualified international applicants are required to submit extra admissions materials depending on their country of origin in addition to the materials listed above. For up-to-date information and resources for foreign student admission, interested international applicants should visit the website and contact The University of Nevada, Reno Office of International Students and Scholars.

Sat, 03 Jun 2023 09:43:00 -0500 en-us text/html https://www.unr.edu/psychology/graduate/behavior-analysis-phd

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