u/Select-Performance13
r/dataanalyst r/coolgithubprojects r/OpenaiCodex r/copilotstudio r/ExcelTips r/ArtificialNtelligence r/projects r/aimemes r/learndatascience r/humor r/LearnDataAnalytics r/microsoft_365_copilot r/Excel247 r/Copilot r/codex r/CodexHacks
I Created a ChatGPT for Excel Skill that help apply statistics for real business cases
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases. The biggest area I started refining was hypothesis testing. With Business cases like:
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
I expanded the workflow so the skill does not immediately jump into a statistical test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The main question I wanted to answer is:
“Can AI help a business, data or finance analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. I consider the hypothesis testing part finish, And I just finished correlation. Thanks to using AI, the project is moving fairly fast. Future improvements may include regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If you are interested in learning to apply statististics to bussines cases, You may like this project. I honestly can said that I have learn and undertood more statistics by working on this porject than the 2 times I have tried to learn statistics academically (for Psychology and my MBA.)
I want to invite people to join and participate in this project. We could use people to:
- Test the skill in your own bussines cases, and sharing if the answer where strong and appropiate
- Help include other statistical areas, like Regression or probability
- GIve ideas, suggestion or comments on how to make this skill more useful.
interested? please give me your feedback. I am using a open source license for the proyect. This mean you can use it, fork it, or modified to suit your needs. As a Excel user for more than 15 years and a and BI analyst for 10, I am very interested in your opinion on this. If you want to inspect the project repo, and download the skill, you can find it by googling: github Ogzapatah1 statistical-analysis-skill-for-excel
u/Select-Performance13 — 2 days ago
▲ 3 r/Excel247
I Created a ChatGPT for Excel Skill that help apply statistics for real business cases
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases. The biggest area I started refining was hypothesis testing. With Business cases like:
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
I expanded the workflow so the skill does not immediately jump into a statistical test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The main question I wanted to answer is:
“Can AI help a business, data or finance analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. I consider the hypothesis testing part finish, And I just finished correlation. Thanks to using AI, the project is moving fairly fast. Future improvements may include regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If you are interested in learning to apply statististics to bussines cases, You may like this project. I honestly can said that I have learn and undertood more statistics by working on this porject than the 2 times I have tried to learn statistics academically (for Psychology and my MBA.)
I want to invite people to join and participate in this project. We could use people to:
- Test the skill in your own bussines cases, and sharing if the answer where strong and appropiate
- Help include other statistical areas, like Regression or probability
- GIve ideas, suggestion or comments on how to make this skill more useful.
interested? please give me your feedback. I am using a open source license for the proyect. This mean you can use it, fork it, or modified to suit your needs. As a Excel user for more than 15 years and a and BI analyst for 10, I am very interested in your opinion on this. If you want to inspect the project repo, and download the skill, you can find it by googling: github Ogzapatah1 statistical-analysis-skill-for-excel
u/Select-Performance13 — 2 days ago
▲ 1 r/OpenaiCodex
I Created a ChatGPT for Excel Skill that help apply statistics for real business cases
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases. The biggest area I started refining was hypothesis testing. With Business cases like:
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
I expanded the workflow so the skill does not immediately jump into a statistical test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The main question I wanted to answer is:
“Can AI help a business, data or finance analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. I consider the hypothesis testing part finish, And I just finished correlation. Thanks to using AI, the project is moving fairly fast. Future improvements may include regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If you are interested in learning to apply statististics to bussines cases, You may like this project. I honestly can said that I have learn and undertood more statistics by working on this porject than the 2 times I have tried to learn statistics academically (for Psychology and my MBA.)
I want to invite people to join and participate in this project. We could use people to:
- Test the skill in your own bussines cases, and sharing if the answer where strong and appropiate
- Help include other statistical areas, like Regression or probability
- GIve ideas, suggestion or comments on how to make this skill more useful.
interested? please give me your feedback. I am using a open source license for the proyect. This mean you can use it, fork it, or modified to suit your needs. As a Excel user for more than 15 years and a and BI analyst for 10, I am very interested in your opinion on this. If you want to inspect the project repo, and download the skill, you can find it by googling: github Ogzapatah1 statistical-analysis-skill-for-excel
u/Select-Performance13 — 2 days ago
I Created a Skill for AI in Excel that help apply statistics for real business cases
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases. The biggest area I started refining was hypothesis testing. With Business cases like:
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
I expanded the workflow so the skill does not immediately jump into a statistical test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The main question I wanted to answer is:
“Can AI help a business, data or finance analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. I consider the hypothesis testing part finish, And I just finished correlation. Thanks to using AI, the project is moving fairly fast. Future improvements may include regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If you are interested in learning to apply statististics to bussines cases, You may like this project. I honestly can said that I have learn and undertood more statistics by working on this porject than the 2 times I have tried to learn statistics academically (for Psychology and my MBA.)
I want to invite people to join and participate in this project. We could use people to:
- Test the skill in your own bussines cases, and sharing if the answer where strong and appropiate
- Help include other statistical areas, like Regression or probability
- GIve ideas, suggestion or comments on how to make this skill more useful.
interested? please give me your feedback. I am using a open source license for the proyect. This mean you can use it, fork it, or modified to suit your needs. As a Excel user for more than 15 years and a and BI analyst for 10, I am very interested in your opinion on this. If you want to inspect the project repo, and download the skill, you can find it by googling: github Ogzapatah1 statistical-analysis-skill-for-excel
u/Select-Performance13 — 2 days ago
Title: AI is not just helping me “vibe code.” It is helping me finally build things.
Yes, I know about “vibe coding,” but that is not really what is happening to me.
I am still creating relatively simple projects, and I mostly understand what I am building. But the projects are getting bigger, more ambitious, more useful and, unfortunately, also more complex.
I had a GitHub account for about four years and barely published anything. I treated it like an abandoned garage: technically mine, but mostly full of dust, vague intentions, and the occasional motivational README.
Now, with AI assistance, I am actually building things:
· Recently, I created a statistical analysis skill for ChatGPT in Excel. The goal is not just to ask AI for a statistical test, but to guide it to first understand the actual business problem. It should help choose the right statistical approach, answer the real business question, and give practical recommendations instead of only producing a technically correct statistical answer.
· I also started a Python Data Science Lab, with an HTML front end that guides someone through learning data science with Jupyter notebooks for practicing Python, statistics, visualization, and machine learning. The idea was simple: study a topic, practice it in notebooks, then return to the front end to answer questions and test understanding.
· And then, because apparently I now enjoy making my life more complicated, I started a Lua game project too. That one is still in development. I have been acting more like the game designer: describing the idea, mechanics, and direction, while the AI writes a lot of the logic.
But I am not just accepting whatever the AI gives me. I am not building blindly. I design things first, refine my goals, ask why the code is structured a certain way, question the design, propose alternatives, and push back when something does not make sense.
I keep going until I understand the logic well enough to feel like I am actually learning from it.
So I would not describe myself as a traditional programmer or a software developer.
But then, what is this role I am stepping into?
I would describe myself as an AI-assisted builder. And honestly, that feels strange.
Part of me is excited and surprised. I am building things I never imagined I could build before. AI is clearly accelerating my learning, but even more than that, it is accelerating my ability to create real, working, useful projects.
But another part of me is slightly frightened, because now I can create more projects than I can properly finish, polish, document, and maintain.
It is a very strange feeling: I feel more capable than before, sometimes honestly very powerful, but also much more overwhelmed. Like someone handed me a small construction company when I was only trying to learn how to use a hammer.
So my question for the community is:
- For those of you using AI to build and learn at the same time, how do you prioritize your projects?
- How do you avoid creating a graveyard of half-finished AI-assisted experiments?
- And how do you make sure you are not just producing more things, but actually learning deeply, polishing your work, and moving in a useful direction?
I am curious whether others are experiencing this same mix of excitement, productivity, occasional delusions of grandeur, confusion, and mild existential GitHub anxiety.
u/Select-Performance13 — 2 days ago
▲ 1 r/dataanalyst
I Created a ChatGPT for Excel Skill that help apply statistics for real business cases
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases. The biggest area I started refining was hypothesis testing. With Business cases like:
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
I expanded the workflow so the skill does not immediately jump into a statistical test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The main question I wanted to answer is:
“Can AI help a business, data or finance analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. I consider the hypothesis testing part finish, And I just finished correlation. Thanks to using AI, the project is moving fairly fast. Future improvements may include regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If you are interested in learning to apply statististics to bussines cases, You may like this project. I honestly can said that I have learn and undertood more statistics by working on this porject than the 2 times I have tried to learn statistics academically (for Psychology and my MBA.)
I want to invite people to join and participate in this project. We could use people to:
- Test the skill in your own bussines cases, and sharing if the answer where strong and appropiate
- Help include other statistical areas, like Regression or probability
- GIve ideas, suggestion or comments on how to make this skill more useful.
interested? please give me your feedback. I am using a open source license for the proyect. This mean you can use it, fork it, or modified to suit your needs. As a Excel user for more than 15 years and a and BI analyst for 10, I am very interested in your opinion on this. If you want to inspect the project repo, and download the skill, you can find it by googling: github Ogzapatah1 statistical-analysis-skill-for-excel
u/Select-Performance13 — 2 days ago
Would people be interested in a ChatGPT for Excel skill that help apply and automate statistical analysis for real business cases?
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases. The biggest area I started refining was hypothesis testing. With Business cases like:
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
I expanded the workflow so the skill does not immediately jump into a statistical test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The main question I wanted to answer is:
“Can AI help a business, data or finance analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. I consider the hypothesis testing part finish, And I just finished correlation. Thanks to using AI, the project is moving fairly fast. Future improvements may include regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If you are interested in learning to apply statististics to bussines cases, You may like this project. I honestly can said that I have learn and undertood more statistics by working on this porject than the 2 times I have tried to learn statistics academically (for Psychology and my MBA.)
I want to invite people to join and participate in this project. We could use people to:
- Test the skill in your own bussines cases, and sharing if the answer where strong and appropiate
- Help include other statistical areas, like Regression or probability
- GIve ideas, suggestion or comments on how to make this skill more useful.
interested? please give me your feedback. I am using a open source license for the proyect. This mean you can use it, fork it, or modified to suit your needs. As a Excel user for more than 15 years and a and BI analyst for 10, I am very interested in your opinion on this. If you want to inspect the project repo, and download the skill, you can find it here: https://github.com/Ogzapatah1/statistical-analysis-skill-for-excel
u/Select-Performance13 — 2 days ago
Would people be interested in a ChatGPT for Excel skill that help apply statistics for real business cases?
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases, such as:
- A/B testing campaign results
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
The biggest area I started refining is hypothesis testing.
I expanded the workflow so the skill does not immediately jump into a formula or test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The desired output is something like:
- Business question being tested
- Statistical test selected and why
- Null and alternative hypotheses in plain English
- Assumptions and caveats
- Result and p-value
- Effect size or business impact
- Decision: reject or fail to reject the null hypothesis
- Practical interpretation
- Recommended business action
To test the skill, I created an Excel workbook with different business scenarios, and test it on ChatGPT for Excel using the /statistical-analysis prompt
The main question I wanted to answer is: “Can AI help a business analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. My current focus is making the hypothesis testing section more reliable and useful inside Excel. Future improvements may include correlation and regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If interested, please give me your feedback. As a Excel user for more than 15 years I am very interested in your opinion on this. If you want to inspect the project repo, you can find it here: https://github.com/Ogzapatah1/statistical-analysis-skill-for-excel
u/Select-Performance13 — 5 days ago
▲ 0 r/ExcelTips
A ChatGPT for Excel skill that help apply statistics for real business cases
I’m working on a small project to adapt a statistical analysis skill for use inside ChatGPT in Excel.
The original skill came from Claude and already had a solid statistical foundation. It covered descriptive statistics, trend analysis, outlier detection, and hypothesis testing. However, when I started testing it in a spreadsheet environment, I noticed a gap.
The answers were often technically reasonable, but not always structured in a way that was useful for a business analyst, financial analyst, or FP&A user working inside Excel.
The goal is not to turn Excel into an academic statistics lab. The goal is to make statistical reasoning more usable for real business cases, such as:
- A/B testing campaign results
- Comparing sales performance between two segments
- Testing before/after changes after a training, promotion, or process improvement
- Comparing conversion rates
- Checking whether two categorical variables are related
- Identifying outliers or unusual business behavior
- Explaining whether a difference is likely real or just normal business noise
The biggest area I started refining is hypothesis testing.
I expanded the workflow so the skill does not immediately jump into a formula or test. Instead, it should first interpret the business question, identify the correct type of comparison, define the null and alternative hypotheses in plain language, check assumptions, select the right test, and then produce a structured business-readable conclusion.
The desired output is something like:
- Business question being tested
- Statistical test selected and why
- Null and alternative hypotheses in plain English
- Assumptions and caveats
- Result and p-value
- Effect size or business impact
- Decision: reject or fail to reject the null hypothesis
- Practical interpretation
- Recommended business action
To test the skill, I created an Excel workbook with different business scenarios, and test it on ChatGPT for Excel using the /statistical-analysis prompt
The main question I wanted to answer is: “Can AI help a business analyst choose the right statistical method, explain it clearly, and turn the result into a better business decision?
This project is still an early iteration. My current focus is making the hypothesis testing section more reliable and useful inside Excel. Future improvements may include correlation and regression workflows, more finance-oriented examples, and better output formatting for spreadsheet-based reporting.
If interested, please give me your feedback. As a Excel user for more than 15 years I am very interested in your opinion on this. If you want to inspect the project repo, you can find it here: https://github.com/Ogzapatah1/statistical-analysis-skill-for-excel
u/Select-Performance13 — 5 days ago