How do you set expectations for a statistical project?

1 Define the problem

The first step to set expectations for a statistical project is to define the problem that needs to be solved or the question that needs to be answered. This will help you to identify the objectives, assumptions, constraints, and criteria of the project. You should also clarify the roles and responsibilities of each stakeholder, such as who is the project owner, who is the data provider, who is the analyst, and who is the decision maker.

2 Choose the approach

The next step to set expectations for a statistical project is to choose the appropriate approach to address the problem or question. This will depend on the type, quality, and availability of the data, as well as the level of complexity and uncertainty of the analysis. You should also consider the ethical, legal, and practical implications of the approach, such as data privacy, consent, validity, and reproducibility. You should explain the rationale and limitations of the chosen approach to your client or collaborator.

3 Plan the process

The third step to set expectations for a statistical project is to plan the process of data collection, preparation, analysis, and presentation. This will help you to estimate the resources, time, and costs required for the project, as well as to identify the potential risks and challenges. You should also define the milestones, deliverables, and feedback mechanisms of the project, such as what are the expected outputs, formats, and deadlines, and how will you communicate and collaborate with your client or collaborator.

4 Manage the scope

The fourth step to set expectations for a statistical project is to manage the scope of the project, which refers to the extent and boundaries of the work to be done. You should avoid scope creep, which is the tendency for the project to grow beyond its original scope due to changing requirements, expectations, or requests. You should also avoid scope reduction, which is the tendency for the project to shrink below its original scope due to resource constraints, technical difficulties, or external factors. You should negotiate and document any changes to the scope with your client or collaborator.

5 Evaluate the results

The fifth step to set expectations for a statistical project is to evaluate the results of the analysis and compare them with the objectives and criteria of the project. You should also interpret and contextualize the results in relation to the problem or question, as well as to the relevant literature, theory, or practice. You should also assess the quality, reliability, and validity of the results, as well as the assumptions, limitations, and uncertainties of the analysis. You should present and discuss the results with your client or collaborator in a clear, concise, and honest manner.

6 Learn from the experience

The sixth and final step to set expectations for a statistical project is to learn from the experience and reflect on the outcomes and feedback of the project. You should also document and share the lessons learned, best practices, and recommendations for future projects. You should also acknowledge and appreciate the contributions and efforts of your client, collaborator, or team members, and celebrate the achievements and successes of the project.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?