Ongoing Support to Keep You Ahead of the Curve

Stay focused on growth while we handle your data challenges.

Key Features:

Flexible retainer plans to meet your evolving needs.

Proactive insights and expert consultations.

BOOK YOUR STATISTICIAN ON RETAINER

ADVANCED STATISTICAL MODELING:

INITIAL CONSULTATION:

  • In-depth discussions to understand the client's research questions and objectives.
  • Assessment of the available data sources and their quality.

Scope Definition:

  • Clear definition of the scope and goals of the advanced statistical modeling project.
  • Identification of key variables and factors to be considered in the analysis.

Data Preparation:

  • Data cleaning and preprocessing to ensure the data is suitable for modeling.
  • Imputation of missing values and handling outliers to improve data quality.

Model Selection:

  • Exploration of various statistical models suitable for the specific problem.
  • Consideration of factors such as linear regression, logistic regression, time series models, machine learning algorithms, etc.

Model Development:

  • Implementation of the selected statistical models using appropriate software tools (e.g., R, Python, SAS).
  • Iterative development with feedback loops to refine the models.

Validation and Testing:

  • Rigorous validation procedures to assess model performance.
  • Splitting the dataset into training and testing sets for evaluation.

Interpretation of Results:

  • Comprehensive interpretation of model outputs and statistical significance.
  • Insightful analysis of key findings and their implications.

Model Fine-Tuning:

  • Fine-tuning of model parameters for optimal performance.
  • Addressing any issues identified during the validation process.

DOCUMENTATION:

  • Preparation of detailed documentation outlining the methodology, assumptions, and limitations.
  • Clear explanations of model inputs, outputs, and key parameters.

INTEGRATION WITH SOFTWARE:

  • Integration of developed models into existing software systems if applicable.
  • Coordination with the programming and development team for seamless implementation.

CONSULTATION AND CLIENT FEEDBACK:

  • Consultation sessions with clients to explain model results and implications.
  • Incorporation of client feedback for model refinement.

Predictive Analytics:

  • If applicable, development of predictive models for forecasting future trends.
  • Assessment of model accuracy and reliability for predictive purposes.

Ongoing Support:

  • Post-implementation support for any issues related to model performance.
  • Periodic reviews and updates to the model as needed.

Collaborative Research:

  • Collaboration with clients on potential research publications or whitepapers based on the advanced statistical modeling results.
  • Assistance in preparing and submitting research findings for publication.