Quantitative Analysis
We live in a data driven society where people are increasingly looking to numbers to describe, explain, and predict phenomena in our businesses, charities, sports, education, personal lives, and more. Quantitative analysis is the most comprehensive way to draw conclusions from direct observation and measurement. Our extensive quantitative analytic services empower you to collect and analyze data to answer your most pressing research needs.
Advanced Analysis
What is it? Advanced analytics are the foundation for leveraging big data to discover deeper insights, make predictions, or generate recommendations. As such, they yield complex models using sophisticated techniques and tools such as data mining, machine learning, forecasting, visualization, neuro network, simulation, and multivariate statistics.
If you want to make predictions about future events, you need predictive analytics. This type of analytics uses machine learning and data mining techniques to define the likelihood of future trends and behaviors based on current and historical data. Businesses use predictive analysis to minimize risks, save costs, and increase competition.
Prescriptive analytics aims for optimal recommendations, answering “what should be done?” This type of analytics, pulling together descriptive and predictive analytics, is widely used in business to identify the best options for a specific situation. Prescriptive analytics uses techniques such as simulation, algorithms, machine learning, graph analysis, and more.
Let our consultants help you improve your efficiency and overall work through advanced analytics.
How can we help you?
- Evaluate and select the appropriate models and statistical analysis methods
- Discover unknown properties in the data (e.g. data mining)
- Identify and segment data into groups representing key attributes (including using k-mean or hierarchical clustering analytics)
- Create predictive models about future events using predictive modeling
- Provide recommendations on finding best course of actions in a scenario given the available data
- Build statistical models using machine learning. This includes supervised and unsupervised machine learning
- Supervised: Regression and classification. It includes both linear and tree-based models
- Unsupervised: Principal component analysis, cluster analysis
- Perform spatial analysis to explain patterns and its spatial expression in terms of geometry
- Analyze RNA-seq or microbiome data (including quality control and DE analysis)
Related Services
Customized Dashboards
A dashboard is a management tool that visually tracks, analyzes, and displays key points by combing multiple data views and graphs.
Learn MoreResults Presentation
Instrument development refers to the development of new measurement scales, while instrument modification or enhancement may refer to improving existing instrument.
Learn MoreSurvey Collection
Instrument development refers to the development of new measurement scales, while instrument modification or enhancement may refer to improving existing instrument.
Learn MoreInstrument Development
Instrument development refers to the development of new measurement scales, while instrument modification or enhancement may refer to improving existing instrument.
Learn MoreArticles and White Papers About Advanced Analysis
Why You Should Go Beyond Microsoft Excel (Part 2)
Articles and White Papers About Software The Problem with Relying Solely on Dashboards Read More Why You Should Go Beyond Microsoft Excel (Part 2) Read More Why You Should Go Beyond Microsoft Excel (Part 1) Articles and White Papers About Software The Problem with Relying Solely on Dashboards Read More...
Read More
Why You Should Go Beyond Microsoft Excel (Part 1)
Articles and White Papers About Software The Problem with Relying Solely on Dashboards Read More Why You Should Go Beyond Microsoft Excel (Part 2) Read More Why You Should Go Beyond Microsoft Excel (Part 1) Articles and White Papers About Monitoring & Evaluation To RCT or Not? Randomized Control Trials...
Read More
Which Six Assumptions Of Multiple Regression Should You Always Test?
Articles and White Papers About Quantitative Statistical Analysis Why You Should Go Beyond Microsoft Excel (Part 2) Read More Which Six Assumptions Of Multiple Regression Should You Always Test? Read More Addressing Challenges in Chemical Engineering: Using Six Sigma to Reduce Defects Articles and White Papers About Quantitative Research Design...
Read MoreFAQ About Advanced Analysis
Everyone knowingly or unknowingly misses out on major data opportunities. Determining the usefulness and costs of acquiring or ignoring data opportunities generally requires a multidisciplinerian team of individuals with diverse research background and connection to data systems and sources.
There are many academic, philanthropic, governmental, and professional sources of data that are available for free, at low costs as well as higher costs. Understanding the benefit, need, and fit for these alternate data sources will help determine which sources can be practical and profitable for your needs.
Data reviews will generally save time and money that reasonably and affordably replicate research that is helpful, necessary, or enlightening in areas of a program or project that will impede, expedite, or ignore critical components of whatever you are trying to do.
Research that is not practical or readily adaptible for implementation is wasteful. Determining the correct advanced analytics that are ready for actionable steps is a critical part of research design and methodology.
Effective research design will consider the cost benefit analyses of multiple types of analytic approaches before determining the right approach. The best approach may encompass several methods, but trying too many methods will likely result in wasting an excessive amount of time and resources.
What Our Clients Say About Us
Peggy Ostrander, DNPc, APRN, FNP-C Plano, Texas