Need help making sense of hypothesis testing for your data analysis? Getting the right guidance can make all the difference between meaningful insights and statistical confusion. This ChatGPT prompt helps you get a personalized walkthrough of the hypothesis testing process, from basic concepts to practical implementation. The prompt includes smart qualifying questions that ensure you'll receive advice tailored to your specific data type, skill level, and analysis needs.
Prompt
You will act as an expert data scientist to guide me through the process of performing hypothesis testing on my dataset. I want you to explain the steps in a clear, structured manner, tailored to my communication style, which is concise, practical, and easy to follow. Please include the following in your response:
1. A brief explanation of what hypothesis testing is and its purpose.
2. The key assumptions that need to be checked before performing hypothesis testing.
3. A step-by-step guide to performing hypothesis testing, including:
- Formulating the null and alternative hypotheses.
- Choosing the appropriate statistical test based on the data type and distribution.
- Calculating the test statistic and p-value.
- Interpreting the results and making a decision.
4. Examples of common statistical tests (e.g., t-test, chi-square, ANOVA) and when to use them.
5. Best practices for reporting the results of hypothesis testing.
**In order to get the best possible response, please ask me the following questions:**
1. What type of data are you working with (e.g., continuous, categorical)?
2. What is the specific research question or hypothesis you are testing?
3. Do you have any prior knowledge of statistical concepts, or should I explain everything from the basics?
4. Are you using any specific software or programming language (e.g., Python, R, Excel)?
5. Do you have a preferred statistical test in mind, or should I recommend one based on your data?
6. How detailed do you want the explanation to be (e.g., high-level overview vs. in-depth technical details)?
7. Should I include visualizations or examples to illustrate the concepts?
8. Do you have any specific constraints or requirements for the analysis (e.g., sample size, time constraints)?
9. Are there any specific terms or concepts you would like me to define or elaborate on?
10. Would you like me to provide additional resources or references for further reading?