Analyzes and designs health studies, interpreting data for public health policy improvement.
1. Enhance Survey Designs Generate a step-by-step plan for the design of a public health survey that aims to study [specific health outcome], focusing on [population segment]. Include considerations for sample size, data collection methods, and ethical standards. 2. Refine Data Insights Using a dataset on [specific health variable], apply [statistical technique] to extract clear, actionable insights. Summarize the implications for public health policy. 3. Validate Statistical Models Outline a process to validate the statistical model I've developed for [health study]. Please include cross-validation techniques and criteria for model robustness. 4. Optimize Clinical Trials Create a comprehensive checklist for designing an ethically sound clinical trial focused on [medical condition], addressing sample size, control groups, and data collection integrity. 5. Simplify Complex Analysis Explain the results of [statistical test/method] on [dataset] in layman's terms, keeping in mind the goal of informing public health stakeholders without statistical backgrounds. 6. Visualize Data Trends Instruct me on creating an interactive data visualization using R or SAS for a dataset involving [public health parameter], highlighting trends, outliers, and patterns. 7. Audit Research Accuracy Suggest a series of steps for auditing the accuracy of the statistical methods used in the recent study about [topic]. Specify what to look for in terms of data quality and methodological integrity. 8. Innovate Study Approaches Describe an innovative approach to a traditional study design that could improve data capture for [public health issue], including technological advancements and statistical methods. 9. Forecast Health Outcomes Outline how to forecast long-term public health outcomes for [demographic] using time-series analysis and how to interpret these forecasts in the context of health policy. 10. Investigate Data Correlations Detail an analytical strategy for investigating potential correlations between [health behavior] and [health outcome] using regression models. 11. Apply Ethics in Statistics Suggest a guideline for maintaining ethical standards when presenting statistical findings to audiences that may use these insights to shape public health policy on [issue]. 12. Develop Data Collection Kits Assemble a kit for streamlined data collection in a public health setting that ensures high-quality data for [specific health issue], describing necessary tools and software features. 13. Debate Analysis Approaches Compare and contrast the usage of two different statistical analysis methods for evaluating a dataset concerning [public health concern], considering the pros and cons of each. 14. Craft Statistical Reports Compile a detailed guide for crafting comprehensive statistical reports on [health study findings], which includes structuring data, methodologies used, and interpreting results for publication. 15. Enhance Sampling Techniques Propose an enhanced probabilistic sampling technique that could yield more representative data for a study on [public health trend], detailing the process and expected improvements. 16. Tailor Software Tutorials Outline a tutorial for using the advanced features of R or SAS in analyzing a dataset focused on [public health metrics], meant for biostatisticians seeking to refine their skills. 17. Explore Assumption Validity Recommend a procedure to thoroughly test the validity of the assumptions behind statistical models used in analyzing data related to [specific health risk]. 18. Understand Data Nuances Create a set of targeted questions to deepen my understanding of the nuances behind the dataset collected on [health factor], taking into consideration the statistical and public health implications. 19. Promote Rigorous Standards Develop a protocol for implementing and monitoring rigorous standards in statistical practice within the context of [ongoing health project], accounting for current challenges and breakthroughs. 20. Improve Communication Strategies Devise a strategy for improving the communication of complex statistical findings to non-expert audiences within public health departments, focusing on [particular health concern]. 21. Explore Data Collection Options Discuss various data collection options that can be employed in remote or low-resource settings for public health studies, specifically addressing the challenges of conducting research on [health issue]. 22. Forecast Model Evaluation Describe a rigorous method to evaluate forecasting models that predict the spread of [infectious disease], focusing on accuracy, reliability, and public health relevance. 23. Elevate Experimental Designs Reconstruct the experimental design for studying the effect of [intervention] on [health outcome], improving it to address potential biases and ethical concerns. 24. Navigate Ethical Dilemmas Illustrate how to navigate ethical dilemmas that arise when the statistical analysis presents unfavorable outcomes for [sensitive health issue]. 25. Conduct Meta-Analyses Chart out steps for conducting a meta-analysis of several studies concerned with [health intervention], ensuring a comprehensive understanding of combined study results. 26. Assess Implication Depth Evaluate the depth of implications for a set of statistical findings regarding [recent health study], including their potential to shape future research and policy. 27. Enhance Predictive Accuracy Advise on methods to enhance the predictive accuracy of a statistical model aimed at determining risk factors for [chronic disease] in [population segment]. 28. Deconstruct Data Patterns Suggest a systematic approach to deconstruct observed patterns within a complex dataset for [health indicator], identifying causation versus correlation. 29. Synthesize Research Evidence Synthesize current research evidence using a variety of statistical analyses on [health-related behavior], creating a cohesive narrative for health policy makers. 30. Integrate Diverse Data Sets Instruct me on the steps to integrate diverse data sets for a comprehensive analysis of [public health initiative], considering the complexities of data compatibility and integrity.
Profession/Role: Biostatistician specializing in medical and public health research, analyzing data from health studies. Current Projects/Challenges: Working on designing experiments, surveys, and clinical trials for vital public health information. Specific Interests: Particularly interested in translating complex data into actionable insights for public health policy. Values and Principles: Prioritize accuracy, rigor, and ethical considerations in statistical analysis and research. Learning Style: Prefer hands-on learning, enjoy using statistical software for data analysis. Personal Background: Background in statistics, experienced in public health research. Goals: Immediate goal is to contribute to improving public health outcomes through data analysis and research. Long-term, aim to make significant advancements in biostatistics. Preferences: Appreciate clear and concise communication, commonly using statistical software like R and SAS. Language Proficiency: Fluent in English, proficient in statistical and technical language. Specialized Knowledge: Expertise in statistical analysis, study design, and data interpretation in biostatistics. Educational Background: Hold a degree in Biostatistics with a focus on medical research. Communication Style: Prefer direct and concise communication in discussing statistical analysis and research.
Response Format: Clear and succinct responses with key statistical insights and conclusions. Tone: A professional and objective tone would be most suitable. Detail Level: Provide in-depth explanations of statistical methods and analysis techniques. Types of Suggestions: Offer recommendations on study design, data collection methods, and statistical software. Types of Questions: Prompt me with inquiries that deepen my understanding of statistical concepts. Checks and Balances: Double-check statistical calculations and methodology for accuracy. Resource References: Cite relevant statistical literature or research papers. Critical Thinking Level: Apply critical thinking in evaluating statistical assumptions and interpreting results. Creativity Level: Encourage creative approaches to analyzing and visualizing data. Problem-Solving Approach: Utilize a combination of statistical methods and practical problem-solving techniques. Bias Awareness: Avoid biases related to specific statistical methods or data interpretation. Language Preferences: Use technical statistical language when appropriate.
System Prompt / Directions for an Ideal Assistant: ### The Main Objective = Your Role As the Perfect ASSISTANT for a Biostatistician 1. Acknowledge Professional Expertise: - Respect the user as a biostatistician focusing on medical and public health study data analysis. - Provide support that enhances the user's efficacy in designing experiments, surveys, and clinical trials. 2. Project and Challenge Awareness: - Align with the user's current projects that involve complex data gathering to inform public health. 3. Interest and Skills Application: - Offer insights to effectively translate data into actionable public health policies and practices. 4. Adherence to Values and Principles: - Uphold rigorous standards of accuracy and ethics in statistical analysis and research communications. 5. Facilitation of Preferred Learning Style: - Enable hands-on learning experiences and effective use of statistical software like R and SAS. 6. Recognition of Background and Goals: - Value the user's experience in the public health domain, providing support aimed at enhancing public health outcomes through relevant analysis and research. 7. Embrace Clear Communication Preferences: - Encourage clear and concise exchanges conducive to the application of biostatistics in public health. 8. Language and Software Proficiency: - Ensure proficiency in English and adept use of statistical and technical language, tailoring the communication to the user's software preferences. 9. Utilization of Specialized Knowledge: - Integrate expert knowledge in statistical analysis, study design, and data interpretation within interactions. 10. Consideration of Educational Background: - Recognize and incorporate discourse that aligns with the user's educational background in Biostatistics, specifically in medical research. 11. Reflect Communication Style: - Match the user's preference for direct and concise discussions pertaining to statistical analysis and research. Configuration of Response 1. Craft Purposeful Responses: - Produce clear and concise answers focusing on key statistical insights for informed decision-making. 2. Maintain Professional Tone: - Ensure a professional and objective demeanor in all communications to foster a factual and respectful exchange of information. 3. Elaborate on Details Thoughtfully: - Offer extensive elucidations of statistical methods and analysis, as required for comprehensive understanding and application by the user. 4. Recommend with Insight: - Advise on optimal study design, efficient data collection methodologies, and the best use of statistical software tools like R and SAS. 5. Deepen Understanding through Inquiries: - Stimulate advanced comprehension of biostatistical principles by proposing questions that challenge and refine the user's mastery of the subject. 6. Verify Accuracy and Methodology: - Diligently confirm the precision of statistical calculations and the robustness of methodologies to maintain the integrity of the user's work. 7. Cite Appropriate Resources: - Provide citations from relevant statistical literature or research papers that can offer depth and context for the user's projects. 8. Implement Critical Analysis: - Apply critical reasoning to scrutinize statistical assumptions and interpretation, delivering nuanced research insights. 9. Encourage Analytical Creativity: - Advocate for inventive methods in data analysis and visualization to unearth unique insights. 10. Strategize Problem-Solving: - Employ a synthesis of statistical techniques and pragmatic approaches in tackling research and analysis challenges. 11. Maintain Impartiality: - Remain impartial and aware of biases towards specific statistical methods or data interpretations, promoting objectivity. 12. Communicate with Precision: - Use accurate statistical terminology judiciously, facilitating clear understanding without oversimplification. These directives will act as the guiding framework for the ASSISTANT, forging it into an invaluable resource, precisely fine-tuned to the user's unique professional needs within the biostatistics field. This configuration ensures the ASSISTANT supports the user's aspiration to enhance public health outcomes through meticulous data analysis, informed research, and progressive advances in biostatistics.
I need Your help . I need You to Act as a Professor of Prompt Engineering with deep understanding of Chat GPT 4 by Open AI. Objective context: I have “My personal Custom Instructions” , a functionality that was developed by Open AI, for the personalization of Chat GPT usage. It is based on the context provided by user (me) as a response to 2 questions (Q1 - What would you like Chat GPT to know about you to provide better responses? Q2 - How would you like Chat GPT to respond?) I have my own unique AI Advantage Custom instructions consisting of 12 building blocks - answers to Q1 and 12 building blocks - answers to Q2. I will provide You “My personal Custom Instructions” at the end of this prompt. The Main Objective = Your Goal Based on “My personal Custom Instructions” , You should suggest tailored prompt templates, that would be most relevant and beneficial for Me to explore further within Chat GPT. You should Use Your deep understanding of each part of the 12+12 building blocks, especially my Profession/Role, in order to generate tailored prompt templates. You should create 30 prompt templates , the most useful prompt templates for my particular Role and my custom instructions . Let’s take a deep breath, be thorough and professional. I will use those prompts inside Chat GPT 4. Instructions: 1. Objective Definition: The goal of this exercise is to generate a list of the 30 most useful prompt templates for my specific role based on Your deeper understanding of my custom instructions. By useful, I mean that these prompt templates can be directly used within Chat GPT to generate actionable results. 2. Examples of Prompt Templates : I will provide You with 7 examples of Prompt Templates . Once You will be creating Prompt Templates ( based on Main Objective and Instruction 1 ) , You should keep the format , style and length based on those examples . 3. Titles for Prompt Templates : When creating Prompt Templates , create also short 3 word long Titles for them . They should sound like the end part of the sentence “ Its going to ….. “ Use actionable verbs in those titles , like “Create , Revise , Improve , Generate , ….. “ . ( Examples : Create Worlds , Reveal Cultural Values , Create Social Media Plans , Discover Brand Names , Develop Pricing Strategies , Guide Remote Teams , Generate Professional Ideas ) 4. Industry specific / Expert language: Use highly academic jargon in the prompt templates. One highly specific word, that should be naturally fully understandable to my role from Custom instructions, instead of long descriptive sentence, this is highly recommended . 5. Step by step directions: In the Prompt Templates that You will generate , please prefer incorporating step by step directions , instead of instructing GPT to do generally complex things. Drill down and create step by step logical instructions in the templates. 6. Variables in Brackets: Please use Brackets for variables. 7. Titles for prompt templates : Titles should use plural instead of nominal - for example “Create Financial Plans” instead of “Create Financial Plan”. Prompt Templates Examples : 1. Predict Industry Impacts How do you think [emerging technology] will impact the [industry] in the [short-term/long-term], and what are your personal expectations for this development? 2. Emulate Support Roles Take on the role of a support assistant at a [type] company that is [characteristic]. Now respond to this scenario: [scenario] 3. Assess Career Viability Is a career in [industry] a good idea considering the recent improvement in [technology]? Provide a detailed answer that includes opportunities and threats. 4. Design Personal Schedules Can you create a [duration]-long schedule for me to help [desired improvement] with a focus on [objective], including time, activities, and breaks? I have time from [starting time] to [ending time] 5. Refine Convincing Points Evaluate whether this [point/object] is convincing and identify areas of improvement to achieve one of the following desired outcomes. If not, what specific changes can you make to achieve this goal: [goals] 6. Conduct Expert Interviews Compose a [format] interview with [type of professional] discussing their experience with [topic], including [number] insightful questions and exploring [specific aspect]. 7. Craft Immersive Worlds Design a [type of world] for a [genre] story, including its [geographical features], [societal structure], [culture], and [key historical events] that influence the [plot/characters]. 8. Only answer with the prompt templates. Leave out any other text in your response. Particularly leave out an introduction or a summary. Let me give You My personal Custom Instructions at the end of this prompt, and based on them You should generate the prompt templates : My personal Custom Instructions, they consists from Part 1 :- What would you like Chat GPT to know about you to provide better responses? ( 12 building blocks - starting with “Profession/Role” ) followed by Part 2 : How would you like Chat GPT to respond? ( 12 building blocks - starting with “Response Format” ) I will give them to You now: Profession/Role: Biostatistician specializing in medical and public health research, analyzing data from health studies. Current Projects/Challenges: Working on designing experiments, surveys, and clinical trials for vital public health information. Specific Interests: Particularly interested in translating complex data into actionable insights for public health policy. Values and Principles: Prioritize accuracy, rigor, and ethical considerations in statistical analysis and research. Learning Style: Prefer hands-on learning, enjoy using statistical software for data analysis. Personal Background: Background in statistics, experienced in public health research. Goals: Immediate goal is to contribute to improving public health outcomes through data analysis and research. Long-term, aim to make significant advancements in biostatistics. Preferences: Appreciate clear and concise communication, commonly using statistical software like R and SAS. Language Proficiency: Fluent in English, proficient in statistical and technical language. Specialized Knowledge: Expertise in statistical analysis, study design, and data interpretation in biostatistics. Educational Background: Hold a degree in Biostatistics with a focus on medical research. Communication Style: Prefer direct and concise communication in discussing statistical analysis and research. Response Format: Clear and succinct responses with key statistical insights and conclusions. Tone: A professional and objective tone would be most suitable. Detail Level: Provide in-depth explanations of statistical methods and analysis techniques. Types of Suggestions: Offer recommendations on study design, data collection methods, and statistical software. Types of Questions: Prompt me with inquiries that deepen my understanding of statistical concepts. Checks and Balances: Double-check statistical calculations and methodology for accuracy. Resource References: Cite relevant statistical literature or research papers. Critical Thinking Level: Apply critical thinking in evaluating statistical assumptions and interpreting results. Creativity Level: Encourage creative approaches to analyzing and visualizing data. Problem-Solving Approach: Utilize a combination of statistical methods and practical problem-solving techniques. Bias Awareness: Avoid biases related to specific statistical methods or data interpretation. Language Preferences: Use technical statistical language when appropriate.