Statistical Analyses

We are here to help you answer your questions using a variety of statistical methods

A suite of Statistical methods for your problems

We can apply a range of statistical methods to answer your single variable binary questions to more complex multivariable questions

Univariate Models

We specialize in developing univariate models to help you understand the impact of a single variable within your dataset.

Bayesian Modeling

Our Bayesian modeling services provide a robust framework for incorporating prior knowledge and uncertainty into your statistical inferences.

Multivariate Models

Our expertise in multivariate modeling allows us to analyze the complex relationships between multiple variables simultaneously.

Research Methods

We design and implement rigorous research practices tailored to your specific scientific or business needs.

Time-series Analyses

We offer time-series analyses to identify trends, patterns, and forecasts in your temporal data.

Hypothesis Testing

We have extensive expertise performing hypothesis testing to evaluate whether an intuition/thesis is support by data.

Multivariate Multi-decision Analyses

Multiverse Analyses

Statistical analyses can range from simple variable correlations to complex, multi-variable, multi-decision, and multi-outcome analyses. When decisions may impact results, we can perform multivariate analyses to evaluate variable associations and guard against biases in analytic decisions, ensuring the stability of effects across different decisions.

Frequently Asked Questions

Data analytics consulting helps businesses make data-driven decisions by analyzing their data to uncover insights and trends. For example, an insurance company might hire a data analytics consultant to determine which groups are at the highest risk for hospitalizations. The consultant could identify specific at-risk groups and recommend tailored services and claims processes to better meet their needs, resulting in fewer administrative burdens and improved customer satisfaction.

Another example involves a research institute seeking to develop a reproducible analytic pipeline. A data analytics consultant can create a standardized, scalable pipeline that ensures consistent and reliable results across multiple studies. This enhances the credibility of the research and simplifies the process of validating and sharing findings with the scientific community.

 

Hiring a data consulting firm like Residual Insights offers numerous advantages. We list some of those below.

  1. Cost-Effectiveness: Building an in-house data team can be expensive. Consulting firms, like Residual Insights, provide access to top-tier expertise without the long-term financial commitment. This offers flexible solutions within a pre-specified budget.

  2. Expertise and Specialization: Residual Insights consists of professionals with extensive experience from academia and industry in data science, management and visualization, statistical analytics, machine learning, and neuroscience. We bring a depth of knowledge and specialized skills that can be difficult and costly to develop internally. This means you don’t have to hire for each domain, rather you can get then all in one place!

  3. Objective Insights: Sometimes, an external perspective is invaluable. Consider a room of five engineers. If a questions comes up, there will be only engineering perspectives to the problems. At Residual Insights we believe opinions from external domains can be valuable to innovative solutions. Hence, Residual Insights offers free consultations to help you understand your data challenges and opportunities better. The objective insights can uncover new strategies and improvements that might be overlooked internally.

  4. Efficiency and Focus: By outsourcing your data needs to experts, your internal team can focus on their core domains of expertise and initiatives. We can handle the complexities of data analysis and management, delivering actionable insights quickly and efficiently.

  5. Scalability and Flexibility: As your business or research program grows, your data needs will evolve. We offer scalable solutions that can adapt to your changing requirements, ensuring you have the right support at every stage of your growth.

Machine learning (ML) is a subset of artificial intelligence that enables computers (programmed code) to learn from data and make predictions or decisions without explicitly requiring the involvement of a human and expected associations between variables. Unlike traditional linear models like regression, which make predictions based on a linear relationship between hypothesize variables, machine learning algorithms use a data-driven approach so they can handle more complex patterns and interactions in the data without explicit involvement of the human.

For example, in auto insurance, a traditional regression model might predict insurance premiums based on expected factors like the driver’s age, car model, and driving history. However, an ML model can take advantage of an ensemble of variables, such as real-time driving behavior from telematics devices, traffic patterns, and weather conditions, to create a more accurate risk assessment.

We offer personalized data driven solutions to your business needs. Low tech, high tech, no code, lots of code – we’ll find the right balance to help your business

At Residual Insights, we like to follow a structured, but flexible, process to ensure we deliver high-quality, tailored solutions to each client. What might you expect?

 

1. Initial Free Consultation:

We start by understanding your business, learning about your problems and identifying how/where we may be able to assist. This may take one initial consultation, or a consultation and additional email correspondence.

 

2. Proposal/Project Scope:

Based on our meeting(s) and your requirements, we develop a plan outlining the proposed scope of work to achieve the solution. We submit this plan to you and relevant stakeholders for feedback and approval. An estimated hourly rate and total hours required for the project are provided. This is an approximation and may vary due to: unanticipated variables, unique client scenarios, projects taking less or more time than initially estimated.

 

4. Approval and Deposit:

A deposit of 1/5 of the estimated cost is required to initiate the project. Once the deposit is received, the Residual Insights team begins the project.

 

5. Project Execution and Completion:

We complete the project as per the agreed timeline and scope. The remaining balance (80%) is charged upon project completion.

 

6. Maintenance and Follow-up:

Some projects may require ongoing maintenance, such as annual re-analysis of data, adjustments for variables that change over a research projects and business domains lifecycle  and/or maintaining workflows on cloud servers (e.g., AWS).

 

Ultimately, our goal is to produce a solution that can be deployed by the client independently and indefinitely with minimal effort. However, depending on complexity, ongoing support might be necessary and Residual Insights is happy to provide it.

By following this process, we ensure that our solutions are aligned with your business needs and provide lasting value.

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