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Data Science and Analytics Consulting

//Data Science and Analytics Consulting
Data Science and Analytics Consulting 2017-07-25T19:07:55+00:00

AMSTAT Consulting’s Four Areas of Expertise

AMSTAT Consulting has become nationally recognized for helping Fortune 500 companies turn data into value without the hassle of managing complex infrastructure, systems, and tools. From implementation to data migration to tuning and optimization to data engineering and advanced analytics, the AMSTAT Consulting Professional Services team will work with you every step of the way. Our clients cite these reasons for choosing to work with us:

  • AMSTAT Consulting employs the best and brightest data scientists in the big data industry.
  • Our experts have PhD in statistics at leading universities including Harvard, Stanford, and Columbia.
  • They have extensive backgrounds in statistics and over 100 years of practical experience in quantitative methods.
  • AMSTAT Consulting augments its in-house expertise by collaborating with industry experts and  certified service providers to ensure you get the best Hadoop experience.
  • We are experts in statistical analysis such as traditional regression, logistic regression, multinomial logistic regression, probit regression, time series analysis survival analysis, discriminant analysis, multivariate adaptive regression splines, globally-optimal classification tree analysis, geospatial predictive modeling, and discrete choice models.
  • We are experts in statistical programming languages such as SAS, R, SPSS, STATA, and Access.
  • Our fees usually pale in comparison to the savings and/or additional profits that our work produces for our clients.
  • Over 90% of our clients request our assistance more than once, as our clients are almost universally happy with our different brand of consulting.
  • We are more reasonably priced than most other consultants offering big data consulting.
  • We offer personalized, comprehensive, and friendly support during and after your consultation with us.
  • We offer ultra-fast turnaround times.

PhD in Statistics at Harvard, Stanford, and Columbia

All of our principals have PhD in statistics at leading universities including Harvard, Stanford, and Columbia.

PhD in Statistics at Harvard, Stanford, and Columbia

All of our principals have PhD in statistics at leading universities including Harvard, Stanford, and Columbia.

The Best and Brightest Data Scientists

AM Statistical Consulting employs the best and brightest data scientists in the big data industry.

The Best and Brightest Data Scientists

AM Statistical Consulting employs the best and brightest data scientists in the big data industry.

Extensive Backgrounds in Statistics

They have extensive backgrounds in statistics and over 100 years of practical experience in quantitative methods.

Over 100 Years of Practical Experience in Quantitative and Qualitative Methods

They have extensive backgrounds in statistics and over 100 years of practical experience in quantitative methods.

The Best Hadoop Experience

AM Statistical Consulting augments its in-house expertise by collaborating with industry experts and certified service providers to ensure you get the best Hadoop experience.

The Best Hadoop Experience

AM Statistical Consulting augments its in-house expertise by collaborating with industry experts and certified service providers to ensure you get the best Hadoop experience.

Our Services

We are happy to provide the help you need at any or all of the following steps in earning the data-based answers you request:

  • Assessing your business needs
  • Defining the business case
  • Setting the strategic rationale for a company’s analytics journey
  • Creating advanced algorithms
  • Establishing methodologies for efficiently accessing, classifying, assessing and prioritizing data
  • Deploying analytical models for business users to incorporate into routine business operations
  • Collaborating with the IT organization to facilitate model deployment
  • Testing model accuracy
  • Maintaining analytical models so that they retain their accuracy
  • Determining which data to collect, and having a sound rationale for doing so
  • Identifying the best way to transform and structure raw data
  • Inputting, organizing, and cleaning the data
  • Exploring large data sets in real-time
  • Developing advanced analytics strategies
  • Bringing analytical rigor through the expertise of our team, which can support a multitude of analyses, including: predictive modeling, customer segmentation, experimental design, pricing optimization and more.
  • Deploying advanced analytics for decision support
  • De-mystifying and simplifying analytics for business users
  • Implementing advanced analytics algorithms
  • Identifying the analytics use cases that present the highest value opportunities
  • Finding hidden patterns with advanced analytics algorithms
  • Visualizing and reporting results
  • Deriving business insight from the data
  • Monetizing business insight
  • Institutionalizing an analytics culture and associated behaviors among business users
  • Helping clients build the advanced analytics organization and capabilities required to execute strategies
  • Managing the ongoing storage and computing requirements associated with the ever growing volume of data
  • Allowing unlimited e-mail and phone support
  • Supporting until project is complete

Our approach to big data analytics insights offers you:

  • Enhanced decision making by assessing the likely outcomes of alternatives
  • More accurate forecasting and planning
  • Insight into patterns that improve customer satisfaction and sales
  • Dynamic, potentially automated decision making
  • Earlier identification of risks and other critical factors

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  • Use Case Discovery

As part of our Advanced Analytical services, we will send a Data Scientist to your site who will conduct a use case discovery session in order to gain a clear understanding of business priorities as well as existing workflows/data sources available for analytics. From there, we will identify use cases, and will create a road map for big data development and training so that you can become self-sufficient.

  • Statistical Methods

We can work in SQL, Python, Scala, Java, and R – with a wide range of advanced analytics algorithms. We can be instantly productive with real-time analysis of large-scale datasets on topics ranging from user behavior to customer funnel. We can easily publish these results and complex visualizations. We can design and perform the required statistical analyses. We bring analytical rigor through the expertise of our team, which can support a multitude of analyses, including:

  • Predictive Modeling
  • Customer Segmentation
  • Experimental Design
  • Pricing Optimization

We can design and perform the required statistical analyses.  Here is a sample of some of the analytical tools with which we are familiar:

  • Traditional Regression
  • Logistic Regression
  • Multinomial Logistic Regression
  • Probit Regression
  • Time Series Analysis
  • Survival Analysis
  • Discriminant Analysis
  • Multivariate Adaptive Regression Splines,
  • Globally-Optimal Classification Tree Analysis
  • Geospatial Predictive Modeling
  • Discrete Choice Models

We have expertise in virtually every statistical software package, including but not limited to:

  • SAS
  • R
  • SPSS
  • Stata
  • Access.

We can assess key aspects of your big data analytics environment, such as data inventory, accessibility, data quality, coverage, accuracy, and automation.

With AMSTAT Consulting’s solution, financial services companies can incorporate online web data and third-party data with extensive historical customer information to develop the most complete customer profile that extends across all channels. Understanding and predicting both known and unknown customer behavior can lead to the presentation of the most appropriate financial product content that is aligned with decisions and events taking place in the lives of consumers and clients. We can:

  • Deploy advanced graph algorithms to detect and prevent money laundering and other fraudulent activities
  • Evaluate the risk in your portfolio through Monte Carlo simulations
  • Recommend personalized new products and services based on a 360-degree view of the customer
  • Use several decades worth of customer data to detect fraud without having to build out dedicated systems or limit our view to a small sample size
  • Store massive data on each user to comply with regulatory requirements, secure it to assure customer privacy, and make the data available to the business all from a single source

Improving the quality of health and wellness is top of mind for consumers today – ranging from nutrition information to a broad range of user-centric consumer applications. To handle the vast number of datasets and sources, broad user base, billions of data points, you need a data platform that can make sense of the complexity to scale with the growing number of applications and user demand. We can:

  • Develop data-driven health or lifestyle recommendations using advanced machine learning algorithms
  • Provide a tailored and personalized view of health data for each individual you serve
  • Keep a decade of EMRs online to comply with HIPAA requirements, and also make that data available for analysis alongside generic industry data and new patient data
  • Prevent adverse effects using the massive trial data available on thousands of drugs, millions of compounds, and countless individual genetic variations
  • Personalize healthcare and minimize unnecessary ED visits by collecting and storing patient data from remote, wearable sensors in real time

Population Health Management

We can improve population health outcomes and lower costs through data aggregation and insight driven prioritization, risk stratification, coordination, and management of patient-centered care. Whether it is dashboards/visualizations or advanced analytics like natural language processing and deep learning, our experts can help.

  • Population Risk Management
  • Population Care Management:
  • Patient Engagement:
  • Clinical Outcomes Management
  • Activity Based Costing

Hospital Management and Administration

We can reduce cost, improve productivity, and increase growth with information from across the healthcare continuum.

  • Clinical Performance
  • Marketing
  • Financial Forecasting, Budgeting and Risk Management
  • Physician Practice Assessment and Alignment:
  • Medical Staff Optimization
  • Hospital Resource Allocation
  • Planning
  • Readmission Reduction

Health Insurance Analytics

We can implement data-driven innovations for better plan design, proactive care management, and pay-for-performance initiatives which lead to increased market share.

  • Healthcare Reform
  • Enterprise Decision Support
  • Provider Partnerships
  • Acquisition Marketing
  • Membership Management
  • Health Plan Trends
  • Payment Integrity for Health Plans

Interoperability

Without interoperability, big data and analytics are useless. Healthcare systems must achieve high degrees of interoperability and data sharing for big data to impact real-time clinical decision making. Disparate systems need to work together. 

  • Healthcare Reform
  • Enterprise Decision Support
  • Provider Partnerships
  • Clinical Outcome Assessment 
  • Activity Based Costing

AMSTAT Consulting is dedicated to using Big Data to figure out what customers are saying about you and what they are saying about your competition. We can use this newly found insight to figure out how this sentiment impacts the decisions you are making and the way your company engages. More specifically, we can determine how sentiment is impacting sales, the effectiveness or receptiveness of your marketing campaigns, the accuracy of your marketing mix (product, price, promotion, and placement), and so on. We can:

  • Answer what is ultimately a more important question: “Why are people saying what they are saying and behaving in the way they are behaving?”
  • Look at the interaction of what people are doing with their behaviors, current financial trends, actual transactions that you are seeing internally, and so on
  • Get to the core of why your customers are behaving a certain way that requires merging information types in cost-effective ways, especially during the initial exploration phase of the project

Social Media Analytics

We can enable companies to incorporate understanding of the textual content, providing critical competitive advantage over their peers, providing key areas of improvement and increased vigil to streamline workflows. Key areas include:

  • Opinion Mining & Sentiment Analysis
  • Brand Monitoring & Competitive Analysis
  • Lead Generation 
  • Trend Analysis

Content Analytics

By unlocking the value of content, we can deliver smarter solutions for brand monitoring, sentiment analysis, competitive and market intelligence, customer experience management, healthcare surveillance, early warning, eCommerce, eDiscovery and much more. Key applications include:

  • Concept Extraction
  • Entity Extraction
  • Text Similarity
  • Article Extraction
  • Sentiment Analysis
  • Language Detection
  • Summarization

Retailers must analyze a great deal of data for each marketing campaign to meet time-sensitive windows of opportunity for converting customer purchases and improving operational processes. We can:

  • Work with retailers and eCommerce sites to deliver solutions that leverage big data to provide a 360° view of consumer behavior, extending current analytics platforms to incorporate predictive and prescriptive analytics
  • Build a unified view of your customer behavior based on their online and offline behavior
  • Infer hidden propensities and recommend next product to buy using machine learning algorithms
  • Build reports in real-time to provide actionable intelligence for your customers
  • Manage inventory across all our brick-and-mortar outlets and online fulfillment centers for a new SKU from a small, foreign manufacturer
  • Optimize key metrics like same-store-sales and promotion efficacy by combining our online and offline data from social, surveillance, point-of-sale, and marketing
  • Model predictive indicators that identify anomalies and help prevent the massive security attacks that cost you billions every year and dilute customer sentiment

We can ingest and process streaming data from a vast network of sensors in real-time. We can:

  • Develop new products based on information hidden in the sensor data
  • Deploy sophisticated algorithms to production
  • Achieve tangible improvements based on insights discovered

Smart Cities

We can enable smart use of resources by using them only when needed, building and empowering systems that save time, energy, and money, and improve the overall quality of life:

  • Smart Lighting
  • Water Management
  • Transport Management
  • Noise Pollution
  • Structural Health Monitoring
  • Citizen Information System
  • Waste Management

Smart Manufacturing

We can connect your machines, data, and people to streamline your operations and bring ground-breaking improvements to your overall manufacturing processes and productivity. We have deep domain knowledge and skills to help you across the IoT application spectrum. Some of the IoT applications in manufacturing are:

  • Asset Monitoring and Optimization
  • Industrial Automation
  • Energy Management
  • Predictive Maintenance
  • Supply Chain Optimization

Smart Healthcare

IoT is an enabler to achieve improved care for patients and providers. It could drive better asset utilization, new revenues, and reduced costs. Additionally, it has the potential to change how health care is delivered:

  • Image Management
  • Visualization
  • Health Care Delivery System
  • Population Health Management
  • Healthcare Asset Tracking
  • Patient Flow Analysis

Oil and Gas – Power Generation and Distribution

We can navigate through the influx of big data and help you capture it, manage it and extract insights that matter:

  • Massive Collection, Management, and Analytics of Exploration Data
  • Predictive Maintenance
  • Operation Optimization
  • Downstream Analysis
  • Upstream Energy Trading
  • Finance and Commercial

Smart Aviation

We can provide prescriptive actions to recover effectively from disruptive events; significant reduction of unplanned downtime through real-time aircraft prognostics and recommended actions; and the optimization of customer service, capacity, operational costs, and maintenance costs:

  • Fuel Management System
  • Flight Risk Management
  • Flight Planning
  • Flight Crew Planning
  • Airport Network Analytics
  • Airport Profitability Analysis

Smart Transportation

We can provide analytics for advanced applications that integrate live data and feedback from a number of other sources, such as parking guidance and information systems, weather information, and bridge de-icing systems:

  • Predictive Maintenance Optimization
  • Capacity and Pricing Optimization

The growth of digital advertising and marketing services has created a plethora of opportunities. Your business can exploit these opportunities if you have the right tools to analyze and process the vast amount of data generated faster than the competition. We can:

  • Integrate structured as well as unstructured data from disparate sources
  • Analyze key metrics to troubleshoot and optimize your product
  • Develop and deploy machine learning algorithms for optimal ad placement
  • Speed up delivery of your analytics product

Customer Segmentation & Profile

We use both demographic segmentation data and advanced clustering segmentation techniques to:

  • Conduct market segmentation to unveil meaningful and measurable segments or microsegments according to customers needs, behaviors, demographics and social profiles
  • Determine the revenue potential of each segment and target segments according to their profit potential and the ability of your company to serve them
  • Obtain a complete customer profile to help predict future behavior through a 360° customer view
  • Use target market analysis to tailor products, services, marketing and distribution strategies to match the needs of each segment
  • Measure performance of each segment and optimize your segmentation approach over time

Personalized & Customer Driven Marketing

By learning where, when, and how buyers are most likely to shop, and which offers and products will appeal to them, you can determine product offerings and personalized marketing campaigns to extract maximum value from both high and low-profit customers. You can optimize your marketing mix, driving channels and redefining customer relationships. Here are some of the applications:

  • Recommendation engine and product recommendation
  • Faceted search and navigation
  • Personalized emails
  • Webpage curation
  • Targeted alerts and offers
  • Deliver personalized and seamless shopping experience across all channels and devices where consumers shop
  • Customer Value Campaigns
  • Mobile Commerce

Marketing Mix and ROI

We can quantify the potential value of all marketing inputs and use predictive analytics to identify marketing investments that are most likely to produce long-term revenue growth.

  • Use predictive analytics to optimize future marketing investments and drive growth in sales, profits and market share
  • Balance short-term marketing and promotion tactics with long-term brand building needs
  • Understand marketing ROI for each offline and online media channel, campaign and execution (i.e., search vs. circular vs. TV)
  • Optimize allocation of traditional media vs. digital media and determine the synergies between the two with marketing mix modeling
  • Quantify the value and impact of emerging/new digital media (Facebook, Groupon, Foursquare, mobile apps, etc.) with a personalized digital marketing strategy
  • Determine which media vehicles and campaigns are most effective at driving revenue, profits, share and consumer segments
  • Quantify the ROI of improving marketing effectiveness in terms of sales, profits, share and target consumer growth

Product Portfolio Management

Our experts help you understand which product combinations are being purchased together by your customers, and in what sequence. Understanding the product combinations and the strength of these relationships is valuable information that can be used for cross selling and upselling, offering coupons and promotions, and making recommendations. 

We indicate, among other things:

  • How to exploit the potential of the strongest products (higher margin, higher turnover)
  • Which products may be withdrawn (low potential, unprofitable products)
  • How to optimally place goods on the shelves at various points of sale (product placement, shelf storage)
  • How one can improve indicators, including the rate of sale (ROS)

Market Sizing & Opportunity Analysis

Our experts can synthesize information from syndicated reports, secondary data, social media intelligence, internal data and other sources to provide a complete picture of your market. Our approach leverages a variety of sources to formulate market.

Competitor Analysis

From strategic overviews of your company’s competitive landscape to specific competitor profiles – our experts can enhance your offerings and go-to-market strategies against competition. We can analyze information from various sources such as sales logs, surveys, social media, and primary data to help you understand your competitor’s next move and stay ahead.

Market Segmentation

We can conduct segmentation analysis to pinpoint the segment that will generate the highest return. A market segmentation designed by our experts will provide an unrivaled informational foundation for growth:

  • Customer Segmentation
  • Demand Analysis
  • Marketing Mix Modeling
  • Digital Media Marketing

Brand Equity

By integrating customer survey data and predictive modeling, our experts can identify optimal routes to strong brand equity that has several dimensions like brand awareness (strength of brand in consumer’s memory), brand image (consumer perception and preferences for a brand), customer perceived value and brand association and help you address the following:

  • Demonstrate the impact of strong brand equity – in terms of market share, customer acquisition, brand loyalty and other desirable outcomes
  • Develop a single measure of brand equity that can feed into management scorecards
  • Determine the impact of all business drivers (marketing, economic, competition, operations) on brand KPIs and sales
  • Understand the effect of change in brand KPIs on other brand KPIs and consumer behavior
  • Calculate the financial value (ROI) of a change in brand KPIs
  • Find the right marketing mix to drive brand objectives
  • Determine the future impact of a change in the marketing and messaging strategy
  • Map your brand’s equity against that of key competitors to help you stay one step ahead
  • Establish a reliable and valid framework to pulse the health of your brand over time

Market Risk Management

We can assist you in identifying and managing the complex risks associated with the development, deployment, and maintenance of intricate models used for risk management, valuation, and financial/regulatory reporting purposes. Market Risk Management services include Value at Risk (VaR) Assessment, Scenario Analysis, Potential Future Exposure and Trading Support, Model Back Testing, Stress Testing, Correlation Analysis, and Volatility Correction. Market Risk Services span across the following areas:

  • Governance, Risk, and Compliance
  • Model Development and Validation
  • Asset Liability Management
  • Risk Monitoring and Reporting
  • Risk-Based Decision Making

Credit Risk Management

Credit Risk Management Consulting covers the entire spectrum, including risk identification through diagnostic review analysis, risk assessment through corporate and retail scoring model development, risk measurement through estimation of Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD) and Credit VaR models, as well as overall risk management, including collateral management, risk-based pricing, and reporting frameworks.

  • Governance, Risk, and Compliance
  • Model Development and Validation
  • Credit VaR Estimation Framework
  • Risk Monitoring and Reporting
  • Risk-Based Decision Making

Retail Fraud Detection

Analysis of transactions and activities such as purchasingaccounts payable, POS, sales projections, warehouse movements, employee shift records, returns, store level video and audio recordings, and other data across your company can help you to identify fraudulent activity and develop appropriate priorities for case management and investigation.

  • Ethical Cultural Assessment
  • Monitoring & Analyzing Loss Prevention Metrics
  • Profiling
  • Monitoring Vendor/Supplier Related Issues
  • Predictive Modeling
  • Retail Shrinkage

Insurance Fraud Detection

Fraudulent claims that are a serious financial burden on insurers cause higher overall insurance costs. Here are a few examples of the way data analysis can be applied to fight fraud in the insurance industry:

  • Medical Billing Fraud
    • Identify excessive billing — same diagnosis, same procedure
    • Identify excessive number of procedures, per day or place of service/day
    • Identify multiple billing of same procedure, same date of service
    • Locate age inappropriate treatments — too young/old for treatment
    • Identify duplicate charges on patient bills
    • Find doctor and patient with same address
  • Claims Fraud
    • Identify duplicate claims
    • Review submission of multiple/inflated claims
    • Find fraudulent family members: i.e., five dependent children born within a two year period.
    • Highlight incorrect gender specific treatments
    • Flag mutually exclusive procedures: e.g. if appendix removed on 01/10/14, then it would be impossible to have appendicitis on 01/02/15.
    • Highlight failure to disclose pre-existing condition (where applicable)
  • Life Insurance Fraud
    • Determine patterns of overpayment of premiums
    • Review transaction payments comprising more than one type of payment instrument
    • Report multiple accounts to collect funds or payment to beneficiaries
    • Report purchase of multiple products in a short period of time
    • Review beneficiaries with multiple policies
    • Isolate transactions for follow-up where employees are beneficiaries
    • Determine agents/brokers with statistically high numbers of claim payouts
    • Calculate benefit payments paid for lapsed policies
    • Find policy loans that are greater than face value
    • Report unauthorized policy changes
    • Identify missing, duplicate, void or out-of-sequence check numbers

The energy sector provides many Big Data use case challenges in how to deal with the massive volumes of sensor data from remote installations. We can:

  • Figure out the insight
  • Take action on this valuable insight
  • Take action on the identified valuable data while it is at rest and also take action while things are actually happening

Build multitenant apps with Azure’s cloud database

AMSTAT Consulting is dedicated to knowing that the time/quality resolution metrics and trending discontent patterns for a call center weeks after the fact. If someone is on the phone and has a problem, we will know about it right away from an enterprise perspective and we will know that people are calling about this new topic or that we are seeing new and potentially disturbing trending in your interactions within a specific segment.

We have been asked by a number of clients for help with this pattern, which is well suited for Big Data. Call centers of all kinds want to find better ways to process information to address what is going on in the business with lower latency. This is a really interesting Big Data use case, because it uses analytics-in-motion and analytics-at-rest. We can:

  • Build these models and find out what is interesting based on the conversations that have been converted from voice to text or with voice analysis as the call is happening by using in-motion analytics means
  • Build up these models and then promote them back in to Streams to examine and analyze the calls that are actually happening in real time by using at-rest analytics

The modern assembly line is made up of highly instrumented machines, with millions of sensors reporting billions of data points. We can:

  • Improve quality control by parsing sensor data in real-time
  • Increase machine uptime with preventative maintenance using advanced machine learning algorithms

To handle the vast number of data sources, broad user base, and billions of data points created by millions of interactions, you need a data platform that can cope with the growing scale and complexity of your data. We can:

  • Gain a holistic view of your users by easily aggregating data from wearables, digital properties, or other relevant data sources
  • Develop data-driven recommendations using advanced machine learning algorithms to increase customer engagement
  • Provide a tailored and personalized view of pertinent data for each individual you serve

Service providers are among the world’s biggest aggregators of consumer data and work under the most uncertain regulatory conditions. Securely storing billions of records and providing transparent, real-time customer access has historically required multiple expensive systems to handle the huge size, complexity, and variety of data. We can

  • Keep down costs and extend our existing systems as our data grows to trillions of records per year
  • Monetize the terabytes of real-time geo-location, mobile interaction, content partner, Bluetooth, and external data we collect every day
  • Speed up our data processing pipelines by at least an order of magnitude to serve our custom­ers and partners better and remain competitive

Monitoring web behavior and user intent can be critical for a number of federal, state and local Government websites. AM Stat Consulting’s solution moves beyond the functionality afforded in traditional digital web analytics tools so government organizations can predict behaviors and monitor and manage the use of internal and external websites. This advanced data insight ensures that published sites are being used properly and gives authorities access to real-time performance data. We can:

  • Combine real-time data with decades of historical records from old systems as the backbone of one massively scalable user-facing system
  • Analyze video frame-by-frame in real time to detect threats and combine that with geospatial, signals intelligence, and other data to paint a complete security picture

I have worked closely with AMSTAT Consulting on the data analysis/results of two research projects so feel as though I am knowledgeable about their expertise. On all accounts, the company provided me with reliable statistical analysis and results that I could translate into publishable format. They are conscientious experts who provide keen insights into appropriate statistical analysis given various data sets. I highly recommend them for your statistical support needs!

Prof. Vincent Salyers, Dean, Faculty of Nursing, MacEwan University

We have been very pleased with working with AMSTAT Consulting. The service was custom tailored and on time completion. The statistical report was detailed with excellent graphics. The cost of the services was affordable for a start-up company such as EndoLogic! Dr. Ann is very detail oriented and likes to know the project thoroughly that is being analyzed.

Dr. Zamir S. Brelvi MD, PhD., CEO & Co-Founder, EndoLogic

Dr. Ann has been instrumental in helping with our statistical needs. In addition to her professionalism, she has been prompt and thorough with all of our requests. Dr. Ann’s work is impeccable, and I would recommend her services to anyone in need of assistance with statistical methods or interpretation. We plan on using Dr. Ann for all of our future needs, and I am thrilled to have been introduced to her.

Dr. Raj Singhal, MD., Director, Pediatric Anesthesiology, Phoenix Children's Hospital

My project required the analysis of a complex survey that required a great deal of help in organizing the data and analyses. In addition, the project required a quick turn-around. AMSTAT Consulting asked all the right questions, made realistic and helpful suggestions, and completed the project in a timely manner. They were professional and helpful throughout the process. I highly recommend them.

Dr. Nancy Allen, Curriculum and Technology Consultant

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Dr. David Fetterman
Dr. David FettermanAdvisory Board (Fetterman & Associates, President)
EDUCATION

Ph.D., Stanford University
Master’s Degree, Stanford University,
Master’s Degree, Stanford University

EXPERIENCE

Stanford University, Professor
School of Medicine, Stanford University, Director of Evaluation

HONORS (selected)

American Educational Research Association Research on Evaluation Distinguished Scholar Award, 2013
American Evaluation Association Advocacy and Use Evaluation Award, 2014
George and Louise Spindler Award, American Anthropological Association and the Council on Anthropology and Education, 1990 (educational anthropology)
Lazarsfield Award for Contributions to Evaluation Theory, American Evaluation Association, 2000
Mensa Education and Research Foundation Award for Excellence, 1990.
Myrdal Award for Cumulative Contributions to Evaluation Practice, American Evaluation Association, 1995
Outstanding Higher Education Professional, Neag School of Education, University of Connecticut, 2008
Who’s Who in America, 1990, 1995-1996, 1999, 2008-2012
Who’s Who in American Education, 1989 90, 1995-96, 2003
Who’s Who in Science and Engineering, 2010, 2011
Who’s Who in the World, 2011, 2012, 2013

BOOKS (selected)

Fetterman, D.M., Rodriguez-Campos, L., and Zukowski, A. (in press). Collaborative, Participatory, and Empowerment Evaluation: Stakeholder Involvement Approaches to Evaluation. New York: Guilford Publications.
Fetterman, D.M., Kaftarian, S., and Wandersman, A. (2015). Empowerment Evaluation: Knowledge and Tools for Self-assessment, Evaluation Capacity Building, and Accountability. Thousand Oaks, CA: Sage.
Fetterman, D.M. (2013). Empowerment Evaluation in the Digital Villages: Hewlett-Packard’s $15 Million Race Toward Social Justice. Stanford: Stanford University Press.
Fetterman, D.M. (2010). Ethnography: Step by Step (Third Edition). Thousand Oaks, CA: Sage.
Fetterman, D.M. and Wandersman, A. (2005). Empowerment Evaluation Principles in Practice. New York: Guilford Publications. (Preview.)
Fetterman, D.M. (2001). Foundations of Empowerment Evaluation. Thousand Oaks, CA: Sage. (Preview.)
Fetterman, D.M. (1998). Ethnography: Step by Step. (Second Edition). Thousand Oaks, CA: Sage. (Preview.)
Fetterman, D.M., Kaftarian, S., Wandersman, A. (Eds.) (1996). Empowerment Evaluation: Knowledge and Tools for Self-assessment and Accountability. Newbury Park, CA: Sage.
(Preview.)
Fetterman, D.M. (Ed.) (1993). Speaking the Language of Power: Communication, Collaboration, and Advocacy. London, England: Falmer Press. (Preview.)
Fetterman, D.M. (Ed.). (1991) Using Qualitative Methods in Institutional Research. San Francisco: Jossey-Bass.
Fetterman, D.M. (1989). Ethnography: Step by Step. Newbury Park, CA: Sage Publications (13th printing).
Fetterman, D.M. (Ed.) (1988). Qualitative Approaches to Evaluation in Education: The Silent Scientific Revolution. New York: Praeger Publications.
Fetterman, D.M. (1988). Excellence and Equality: A Qualitatively Different Perspective on Gifted and Talented Education. New York: State University of New York Press. (Chapter 7 reprinted in Mensa Research Journal.) (Preview.)
Fetterman, D.M. (Ed.) (1987). Perennial Issues in Qualitative Research, Education and Urban Society (Special Topic Edition), 20(1).
Fetterman, D.M. and M.A. Pitman. (Eds.) (1986). Educational Evaluation: Ethnography in Theory, Practice, and Politics. Newbury Park, CA: Sage Publications.
Fetterman, D.M. (Ed.) (1984). Ethnography in Educational Evaluation. Newbury Park, CA: Sage Publications.

CHAPTERS AND ARTICLES (selected – over 100)

Fetterman, D.M. (in press). Empowerment Evaluation. The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation. Thousand Oaks, CA: Sage.
Fetterman, D.M. and Ravitz, J. (in press). Evaluation Capacity Building. The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation. Thousand Oaks, CA: Sage.
Fetterman, D.M. (in press). Empowerment Evaluation: Linking Theories, Principles, and Concepts to Practical Steps. In Secolsky, C. and Denison, D.B. (eds.) Handbook on Measurement, Assessment, and Evaluation in Higher Education (2nd edition). New York: Routledge.
Fetterman, D.M. (in press). Transformative Empowerment Evaluation and Freireian Pedagogy: Alignment with an Emancipatory Tradition. In Patton, M.Q. (ed.) Pedagogy of Evaluation: The Cpntributions of Paulo Freire to Global Evaluation Thinking and Practice. New Directions for Evaluation. San Francisco: Jossey-Bass.
Fetterman, D.M. (2015). Empowerment Evaluation. International Encyclopedia of the Social and Behavioral Sciences, 2nd edition.
Fetterman, D.M. (2015). Ethnography. International Encyclopedia of the Social and Behavioral Sciences, 2nd edition.
Fetterman, D.M. (2005). Empowerment Evaluation and Action Research: A Convergence of Values, Principles, and Purpose. In Bradbury, H. (ed.) The Handbook of Action Research. Thousand Oaks, CA: Sage.
Mansh, M., White, W., Gee-Tong, L., Lunn, M., Obedin-Maliver, J., Stewart, L., Goldsmith, E., Brenman, S., Tran, E., Wells, M., Fetterman, D.M., Garcia, G. (2015). Sexual and Gender Minority Identity Disclosure During Undergraduate Medical Education: “In the Closet” in Medical School. Academic Medicine, 90(5):634-644.
Wang JY, Lin H, Lewis PY, Fetterman DM, Gesundheit N. (2015). Is a career in medicine the right choice? The impact of a physician shadowing program on undergraduate premedical students. Acad Med. May, 90(5):629-33. doi: 10.1097/ACM.0000000000000615
White,W., Brenman, S., Paradis, E., Goldsmith, E.S., Lunn, M.R., Obedin-Maliver, J., Stewart, L., Tran, E., Wells, M., Chamberlain, L.J., Fetterman, D.M., and Garcia, G. (2015). Lesbian, Gay, Bisexual, and Transgender Patient Care: Medical Students’ Preparedness and Comfort. Teaching and Learning in Medicine: An International Journal. Volume, 27, Issue 3: 254-263
Obedin-Maliver, J., Goldsmith, E.S., Stewart, L., White, W., Tran, E., Brenman, S., Wells,M., Fetterman, D.M., Garcia, G., Lunn, M.R. (2011). Lesbian, Gay, Bisexual, and Transgender-Related Content in Undergraduate Medical Education. JAMA, 306(9):971-977.
Fetterman, D.M., Kaftarian, S., and Wandersman, A. (2015). Empowerment evaluation is a systematic way of thinking: A response to Michael Patton Empowerment evaluation: Knowledge and tools for self-assessment, evaluation capacity building, and accountability. Evaluation and Program Planning 52 (2015) 10–14
Fetterman, D.M., Rodriguez-Campos, L., Wandersman, A., and Goldfarb O’Sullivan, R. (2014). Collaborative, Participatory, and Empowerment Evaluation: Building a Strong Conceptual Foundation for Stakeholder Involvement Approaches to Evaluation (A Response to Cousins, Whitmore, and Shulha, 2013), American Journal of Evaluation, 35(1):142-146. DOI: 10.1177/1098214013509875
Fetterman, D.M. (2012). Empowerment evaluation: learning to think like an evaluator. In Alkin, M. (ed.) Evaluation Roots: A Wider Perspective of Theorists’ Views and Influences (Second Edition). Thousand Oaks, CA: Sage.
Fetterman, D.M. (2011). Empowerment Evaluation and Accreditation Case Examples: California Institute of Integral Studies and Stanford University. In Secolsky, C. and Denison, D.B. (eds.) Handbook on Measurement, Assessment, and Evaluation in Higher Education. New York: Routledge.
Fetterman, D.M., Deitz, J., and Gesundheit, N. (2010). Empowerment evaluation: A collaborative approach to evaluating and transforming a medical school curriculum. Academic Medicine, 85(5):813-820.
Fetterman, D.M. (2009). Empowerment evaluation at the Stanford University School of Medicine: Using a Critical Friend to Improve the Clerkship Experience. Ensaio: Avaliação e Políticas Públicas em Educação. Rio je Janeiro, 17(63):197-204.
Fetterman, D. and Wandersman, A. (2007). Empowerment Evaluation: Yesterday, Today, and Tomorrow. American Journal of Evaluation, 28(2):179-198.
Fetterman, D.M. (2004). Empowerment Evaluation’s Technological Tools of the Trade. Harvard Family Research Project. The Evaluation Exchange, X 3, p. 8-9.
Fetterman, D.M. (2003). Ethnography. In Lewis-Beck, M., Bryman, A., and Liao, T.F. (eds.), Encyclopedia of Research Methods for the Social Sciences. Thousand Oaks, CA: Sage.
Fetterman, D.M. (in press). Qualitative Approaches to Evaluating Education. In Burgess, R. (ed.) Encyclopedia of Social Science Research. London, England: Falmer Press.
Fetterman, D.M. (2003). Fetterman-House. A Process Use Distinction and a Theory. In Christie, C.A. (ed.) The Practice-Theory Relationship in Evaluation. No. 97, Spring. San Francisco: Jossey-Bass.
Fetterman, D.M. (2003). Empowerment Evaluation Strikes a Responsive Chord. In S. Donaldson & Scriven, M. (Eds.) Evaluating social programs and problems: Visions for the new millennium. Hillsdale, NJ: Erlbaum.
Fetterman, D.M. and Bowman, C. (2001). Experiential Education and Empowerment Evaluation: Mars Rover Educational Program Case Example. Journal of Experiential Education.
Fetterman, D.M. (2002). Web surveys to Digital Movies: Technological Tools of the Trade. Educational Researcher, 31(6):29-37 or http://aera.net
Fetterman, D.M. (2002). Book Review of Qualitative Research: A Personal Skills Approach by Gary D. Shank, Education Review.
Fetterman, D.M. (1999). Reflections on Empowerment Evaluation: Learning from Experience. Canadian Journal for Program Evaluation, Special Issue, pp. 5-37.
Fetterman, D.M. (1998). Teaching in the Virtual Classroom at Stanford University. The Technology Source.
Fetterman, D.M. (1998). Webs of Meaning: Computer and Internet Resources for Educational Research and Instruction. Educational Researcher, 27(3):22-30.
Fetterman, D.M. (1998). Learning with and about technology: A middle school nature area. Meridian, 1(1)
Fetterman, D.M. (1997). Empowerment Evaluation: A Response to Patton and Scriven. Evaluation Practice, 18(3):253-266.
Fetterman, D.M. (1997). A Response to Sechrest’s Review of Empowerment Evaluation. Environment and Behavior, 29(3):427-436.
Fetterman, D.M. (1997). Ethnography. In Bickman, L. and Rog, D. (eds.) Handbook of Applied Social Research Methods. Thousand Oaks, CA: Sage.
Fetterman, D.M. (1997). Good care includes educational activities. The Philadelphia Inquirer. Saturday, May 31, p. A 11.
Fetterman, D.M. (1997). Empowerment Evaluation and Accreditation in Higher Education. In Chelimsky, E. and Shadish, W. (eds.) Evaluation for the 21st Century: A Resource Book. Thousand Oaks, CA: Sage.
Fetterman, D.M. (1997). Videoconferencing Over the Internet. Qualitative Health Research, 7(1):154-163.
Fetterman, D.M. (1996). Empowerment Evaluation: An Introduction to Theory and Practice. In Fetterman, D.M., Kaftarian, S., and Wandersman, A. (eds.) Empowerment Evaluation: Knowledge and Tools for Self-Assessment and Accountability. Newbury Park, CA: Sage.
Fetterman, D.M. (1996). Conclusion: Reflections on Emergent Themes and Next Steps. In Fetterman, D.M., Kaftarian, S., and Wandersman, A. (eds.) Empowerment Evaluation: Knowledge and Tools for Self-Assessment and Accountability. Newbury Park, CA: Sage.
Fetterman, D.M. (1996). Videoconferencing On-Line: Enhancing Communication Over the Internet. Educational Researcher, 25(4)
Fetterman, D.M. (1996). Ethnography in the Virtual Classroom. Practicing Anthropology, 18(3):2, 36-39.
Fetterman, D.M. (1995). Empowerment Evaluation: A Learning Tool for Systemic Change. In Jenlink, P. (ed.), Systemic Change: Touchstones for the Future School Palatine, IL: IRI/Skylight Publishing.
Fetterman, D.M. (1995). In Response to Dr. Daniel Stufflebeam’s: “Empowerment Evaluation, Objectivist Evaluation, and Evaluation Standards: Where the Future of Evaluation Should Not Go and Where It Needs to Go,” Evaluation Practice, June 1995, 16(2):179-199.
Fetterman, D.M. (1994). Ethnographic Evaluation in Education. In T.Husen and T.N. Postlethwaite, The International Encyclopedia of Education. Oxford, England: Pergamon Press.
Fetterman, D.M. (1994). Gifted and Talented Education Program Evaluation. In Sternberg, R.J. (ed.) Encyclopedia of Human Intelligence. New York, NY: Macmillan Publishing Company.
Fetterman, D.M. (1994). The Terman Study. In Sternberg, R.J. (ed.) Encyclopedia of Human Intelligence. New York, NY: Macmillan Publishing Company.
Dennis, M.L., Fetterman, D.M. and Sechrest, L. (1994). Integrating Qualitative and Quantitative Evaluation Methods in Substance Abuse Research. Evaluation and Program Planning, 17(4):419-427.
Fetterman, D.M. (1994). Keeping Research on Track. New Directions for Program Evaluation. No. 63, Fall. San Francisco, CA: Jossey-Bass, pp. 103-105.
Fetterman, D.M. (1994). Steps of Empowerment Evaluation: From California to Cape Town. Evaluation and Program Planning, 17(3):305-313.
Fetterman, D.M. (1994). Empowerment Evaluation. Presidential Address. Evaluation Practice, 15(1):1-15.
Fetterman, D.M. (1993). Empowerment Evaluation (Theme for 1993 Annual Meeting), Evaluation Practice, 14(1):115-117.
Fetterman, D.M. (1993) Evaluate Yourself: Executive Summary. Storrs, CT: National Research Center on the Gifted and Talented.
Fetterman, D.M. (1992) Investigative Evaluation and Litigation. In N. Smith (Ed.) Varieties of Investigative Evaluation. New Directions for Program Evaluation. San Francisco, CA: Jossey-Bass, No. 56, Winter 1992, pp. 15-28.
Fetterman, D.M. (1993). Confronting a Culture of Violence: South Africa Nears a Critical Juncture. San Jose Mercury, October 3, pp. 1C, 4C.
Fetterman, D.M. (1993). Ethnography and Policy: A Catalytic Combination for Change. In E. Jacob and C. Jordan, Minority Education: Anthropological Perspectives. New Jersey: Ablex.
Fetterman, D.M. (1992). Hevrah: Our Intellectual Community. Anthropology and Education Quarterly, 23(4):271-274.
Fetterman, D.M. (1992) Theory in Evaluation: We Think, Therefore We Theorize (An Ethnographer’s Perspective). In Chen, H. and Rossi, P.H. (Eds.) Using Theory to Improve Program and Policy Evaluations. New York, NY: Greenwood Press.
Fetterman, D.M. (1992) Evaluate Yourself. Storrs, CT: National Research Center on the Gifted and Talented.
Fetterman, D.M. (1991). Auditing as Institutional Research: A Qualitative Focus. In Fetterman, D.M. (Ed.). Using Qualitative Methods in Institutional Research, New Directions for Institutional Research. San Francisco: Jossey-Bass.
Fetterman, D.M. (1991) Qualitative Resource Landmarks. In Fetterman, D.M. (ed.). Using Qualitative Methods in Institutional Research, New Directions for Institutional Research. San Francisco: Jossey-Bass.
Fetterman, D.M. (1991). A Walk Through the Wilderness: Learning to Find Your Way. In Shaffir, W.B. and Stebbins, (Eds.) Experiencing Fieldwork: An Inside View of Qualitative Research. Newbury Park, CA: Sage.
Fetterman, D.M. (1991). Evaluation in Multi-Site and Multi-Focus Projects. Revitalizing Rural America: New Strategies for the Nineties. Georgia Center for Continuing Education. Athens, GA: The University of Georgia.
Fetterman, D.M. (1990). Ethnographic Auditing. In Tierney, W.G. (ed.) Assessing Academic Climates and Cultures, New Directions for Institutional Research. San Francisco: Jossey-Bass, 68:19-34.
Fetterman, D.M. (1990). Health and Safety Issues: Colleges Must Take Steps to Avert Serious Problems. The Chronicle of Higher Education, March 21, A48.
Fetterman, D.M. (1989). Anthropology Can Make a Difference. In Trueba, H., G. Spindler, and Spindler, L. (Eds.) What Do Anthropologists Have to Say About Dropouts? New York, NY: Falmer Press, 1989.
Fetterman, D.M. (1989). Ethnographer as Rhetorician: Multiple Audiences Reflect Multiple Realities. Practicing Anthropology, 11(2):2, 17-18.
Fetterman, D.M. (1988). Stanford Special Review on Health and Safety Phase II: A Report on Allegations. Internal Audit Department. Stanford, CA: Stanford University.
Fetterman, D.M. (1988). Qualitative Approaches to Evaluating Education. Educational Researcher, 17(8):17-23.
Fetterman, D.M. (1988). Gifted and Talented Education. In Gorton, R.A., Schneider, G.T., and Fisher, J.C. (Eds.) Encyclopedia of School Administration and Supervision. Phoenix, AZ: Oryx Press.
Fetterman, D.M. (1987). A Rainbow of Qualitative Approaches and Concerns. In Fetterman, D.M. (Ed.), Perennial Issues in Qualitative Research, Education and Urban Society (Special Topic Edition), 20 (1):3-8.
Fetterman, D.M. (1987). A National Ethnographic Evaluation of the Career Intern Program (an alternative high school program for dropouts). In B. Wulff and S.J. Fiske (ed.) Anthropological Praxis: Translating Knowledge into Action. Boulder, CO: Westview Press, 1987.
Fetterman, D.M. (1987). Ethnographic Educational Evaluation. In G.D. Spindler (Ed.), Interpretive Ethnography of Education: At Home and Abroad. New Jersey: Lawrence Erlbaum Associates, pp. 81 -106.
Fetterman, D.M. (1986). The Ethnographic Evaluator. In Fetterman, D.M. and Pitman, M.A. (Eds.) Educational Evaluation: Ethnography in Theory, Practice, and Politics. Beverly Hills, CA: Sage Publications, pp. 21-47. Reprinted in E. Eddy and W. Partridge, Applied Anthropology in America, New York: Columbia University Press, 1987, pp. 340-365
Fetterman, D.M. (1986). The Role of Informed Criticism in Scholarly Review. Evaluation and Program Planning, 9:183-4.
Fetterman, D.M. (1986). Gifted and Talented Education: A National Test Case in Peoria. Educational Evaluation and Policy Analysis, 8(2):155-166.
Fetterman, D.M. (1986). Conceptual Crossroads: Methods and Ethics in Ethnographic Research. In D.D. Williams, (Ed.) Naturalistic Evaluation, New Directions for Program Evaluation. San Francisco, CA: Jossey-Bass Inc., pp. 23-36.
Fetterman, D.M. (1986). Operational Auditing in a Teaching Hospital: A Cultural Approach, Internal Auditor, 43(2):48-54.
Fetterman, D.M. (1986). Gifted and Talented Education in the Soviet Union, Gifted Education International, 5(1):180-183.
Fetterman, D.M. (1986). Beyond the Status Quo in Ethnographic Educational Evaluation. In D.M. Fetterman and M.A. Pitman (Eds.), Educational Evaluation: Ethnography in Theory, Practice, and Politics. Newbury Park, CA: Sage Publications, pp. 13-20.
Fetterman, D.M. (1986). The Evolution of a Discipline. In D.M. Fetterman and M.A. Pitman (Eds.), Educational Evaluation: Ethnography in Theory, Practice, and Politics. Newbury Park, CA: Sage Publications, pp. 215-222.
Fetterman, D.M. (1986). Evaluating Organizational Culture in a Teaching Hospital: The Use of Cultural Concepts and Techniques. In K. Sedgwick (Ed.), Association of College and University Auditors. Logan, Utah: Utah State University.
Fetterman, D.M. (1985). Focusing on a Cross-Cultural Lens in Evaluation. Evaluation Research Society Newsletter, Invited special topic article, 9(2):3-5.
Fetterman, D.M. (1984). Doing Ethnographic Educational Evaluation. In D.M. Fetterman (Ed.), Ethnography in Educational Evaluation. Newbury Park, CA: Sage Publications, Inc.
Fetterman, D.M. (1984). Guilty Knowledge, Dirty Hands, and Other Ethical Dilemmas: The Hazards of Contract Research. Human Organization, 42 (3):214-224. Reprinted in Conner, R.F. (Ed.) Evaluation Studies Review Annual, Vol. 9, 1984. Also reprinted in Fetterman, D.M. (Ed.) Ethnography in Educational Evaluation. Newbury Park, CA: Sage Publications, Inc.
Fetterman, D.M. (1982). Ibsen’s Baths: Reactivity and Insensitivity (A misapplication of the treatment-control design in a national evaluation). Educational Evaluation and Policy Analysis, 4 (3):261-279.
Fetterman, D.M. (1982). Ethnography in Educational Research: The Dynamics of Diffusion. Educational Researcher, 11 (3):17-29. Also reprinted in Fetterman, D.M. (Ed.) Ethnography in Educational Evaluation. Newbury Park, CA: Sage Publications, Inc., 1984.
Fetterman, D.M. (1981). CIP is Hip: A National Ethnographic Evaluation of an Alternative High School Program for Dropouts. Doctoral dissertation, Stanford University.
Fetterman, D.M. (1981). New Perils for the Contract Ethnographer. Anthropology and Education Quarterly, 7(1):71-80.
Fetterman, D.M. (1981). Protocol and Publication: Ethical Obligations. Anthropology and Education Quarterly, 7(1):82-83.
Fetterman, D.M. (1981). Blaming the Victim: The Problem of Evaluation Design, Federal Involvement, and Reinforcing World Views in Education. Human Organization, 40(1):67-77. Also reprinted in Evaluation Studies Review Annual, 1982, 7:65-75.
Fetterman, D.M. (1980). Ethnographic Techniques in Educational Evaluation: An Illustration. In A. Van Fleet (Ed.), Anthropology of Education: Methods and Applications. Special topic edition of the Journal of Thought, Fall, 15(3):31-48.
Fetterman, D.M. & Alvarez, R.R. (1979). Anthropological Approaches to Evaluating Education: An Ethnographic Guide for Program Evaluation. CA: United Teachers of Santa Clara Press.
Fetterman, D.M. (1976). An Urban Secondary School Ethnography. Storrs, Connecticut: University of Connecticut.

BLOGS (selected)

Fetterman, D.M. (2014) David Fetterman on Google Glass Part I: Redefining Communications. AEA365. American Evaluation Association. http://aea365.org/blog/david-fetterman-on-google-glass-part-i-redefining-communications/ (April 17.)
Fetterman, D.M. (2014) David Fetterman on Google Glass Part II: Using Glass as an Evaluation Tool. AEA365. American Evaluation Association. http://aea365.org/blog/david-fetterman-on-google-glass-part-ii-using-glass-as-an-evaluation-tool/ (April 18.)
Fetterman, D.M. (2013). In These Uncertain Times, Charities Need a Survival Plan. The Chronicle of Philanthropy. March 10. http://philanthropy.com/article/In-These-Uncertain-Times/137741/
Fetterman, D.M. (2013). Surviving the Fiscal Cliff: The one thing every nonprofit should do in the face of federal tax increases and spending cuts. Stanford Social Innovation Review. http://www.ssireview.org/blog/entry/surviving_the_fiscal_cliff (January).
Fetterman, D.M. (2012). Empowerment Evaluation in the Digital Villages. Stanford Social Innovation Review. http://www.ssireview.org/articles/entry/empowerment_evaluation_in_the_digital_villages_hewlett_packards_15_million (December)
Fetterman, D.M. (2012). Corporate Philanthropy Tackles the Digital Divide. Stanford Social Innovation Review. http://www.ssireview.org/blog/entry/corporate_philanthropy_tackles_the_digital_divide (November)

RADIO INTERVIEWS (recent at: http://www.davidfetterman.com/RadioInterviews.htm)

Empowerment Evaluation in the Digital Villages (book), KAZI FM, Houston, Texas, March 29, 2013.
Chronicle of Philanthropy article about evaluation and nonprofit survival (Chronicle), WPFM FM, Washington, D.C. March 25, 2013.
Empowerment Evaluation in the Digital Villages (book), Kathryn Zox Show, March 13, 2013.
Empowerment Evaluation in the Digital Villages (book), Money Matters Network, Host Stu Taylor, January 28, 2013.
Empowerment Evaluation in the Digital Villages (book), WKXL-AM, Concord, New Hampshire, Host Bill Kearney, January 17, 2013.
Empowerment Evaluation in the Digital Villages (book), WPHM-AM Detroit, Host Paul Miller, January 14, 2013.
Empowerment Evaluation in the Digital Villages (book), Business Matters Radio, Host Thomas White, January 14, 2013.

ENCYLOPEDIA (selected): The International Encyclopedia of Education, Encyclopedia of Human Intelligence, and The Sage Encyclopedia of Qualitative Research Methods

PROFESSIONAL ASSOCIATION PRESENTATIONS (selected from over 100): American Evaluation Association, American Educational Research Association, American Anthropological Association, Association of American Medical Colleges, and AAMC Western Group on Educational Affairs.

Research Design 100%
Dr. Ann E.K. Um
Dr. Ann E.K. UmPresident and CEO
EDUCATION

Doctorate Degree, Columbia University
Master’s Degree, Stanford University
Master’s Degree, Columbia University

EXPERIENCE

Harvard Medical School, Research Data Manager
Harvard Medical School, Brigham and Women’s Hospital, Research Data Manager
The University of Texas, Assistant Professor

PUBLICATIONS (selected)

Autonomy Support, Self-Concept, and Mathematics Performance: A Structural Equation Analysis. Saarbrucken, Germany: VDM Verlag, 2010.
Motivation and Mathematics Achievement: A Structural Equation Analysis, Saarbrucken. Saarbrucken, Germany: VDM Verlag, 2008.
Motivation and Mathematics Performance: A Structural Equation Analysis. Michigan, Ann Arbor: ProQuest, 2006.
Motivation and Mathematics Performance: A Structural Equation Analysis (doctoral dissertation). Columbia University, New York, 2005.

PRESENTATIONS (selected)

Motivation and Mathematics Performance: A Structural Equation Analysis, National Council on Measurement in Education, Montreal, Quebec, Canada, 2005.
Comparing Eighth Grade Diagnostic Test Results for Korean and American Students, National Council on Measurement in Education, Chicago, Illinois, 2003.

Big Data Consulting 100%
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