class: center, middle, inverse, title-slide .title[ # Meeting with Clients: Asking Good Questions, Expectations, Delivery and Conflict ] .author[ ### Dr Thiyanga S. Talagala ] .author[ ### ] --- # How does the client form their first impression of you, as a consultant? Common courtesy and respect obviously go a long way towards creating a positive environment for our consultation meetings. Non-verbal communication and verbal communication matter a lot! Simple things you can do to help clients feel comfortable: - Greet the client - Introduce yourself --- ## Asking questions - Listen carefully to what the client says - Listen for what is not said - Listen `\(\rightarrow\)` think `\(\rightarrow\)` ask questions `\(\rightarrow\)` learn - Take notes **during** the consultation session --- ## Details about the client's project - Understand the context of a project from the client's perspective - Background of the project - Status of the project - Aims of the project - What does the client expect from us? - How well does the client understand the project? - How much statistical knowledge/ technical knowledge does the client possess? --- ## What makes a question good and what makes a good question great? A good question elicits the information necessary to provide a correct answer to the right scientific question. In the context of teaching statistics, a good question leads students to improve their understanding of statistics AND results in the instructor better understanding how well the students have learned the context. --- ## Some questions - Your research sounds interesting. Can you tell me more....? - Am I understanding correctly? **Paraphrasing the answer** - What type of investigation is this (designed experiment, sample survey, or observational study)? - At what stage is this investigation (planning or analysis stage)? - Do certain constraints exist in the process? - What motivated you to start this project? - Is this a pre-specified hypothesis you want to test, or would you rather explore what the data have to say about the relationships? - Who will be using these results and how? What impacts do you hope they have - What is the data type of each variable? - Are there outliers or missing values present? --- ## Issues - The sample size is too small for any meaningful analysis or is simply too large for our current computing resources. - The data is biased or poorly gathered and there is no opportunity for further planned data collection. - The client may not really understand their project or their expectations of the analysis results are unrealistic. - We may not understand the client's project or have limited expertise in the type of statistical analysis required for the project. --- ## Issues (cont.) - We have moral or ethical objections to the project. This includes statistical ethics such as a client who "requests" a particular method of analysis which is clearly inappropriate. Source: Cabrera, J., & McDougall, A. (2002). Statistical consulting. Springer Science & Business Media.