👩‍💻 Your task:

1. Do the calculations yourself (mean, median, mode).

2. Ask AI:
   “What are the mean, median, and mode for streams and session length in this dataset?”

3. Post a sticky note with:

   • Your numbers

   • The AI’s numbers

   • Which seems more reliable? Why?

👩‍💻 Your task:

1. Look at the dataset we’ve uploaded (CSV).

2. Ask an AI tool (ChatGPT, Copilot, NotebookLM, etc.):

   • “Summarise the key features of this dataset. What variables are included, and what do you notice?”

3. Post a sticky note with:

   • One observation you made yourself

   • One observation the AI made

   • Whether you trust the AI’s summary (why or why not)

👩‍💻 Your task:

1. Choose one pattern to test yourself, for example:

   • Do Premium users stream more than Free users?

   • Do older users listen longer?

   • Does skip rate affect likes?

2. Then ask AI:
   “Find patterns in this dataset. Are there differences by plan, age, or skip rate?”

3. Post a sticky note with:

   • Your finding

   • The AI’s finding

   • Did AI agree with you, or did it miss something?

👩‍💻 Your task:

1. Predict August streams based on July values. What do you expect?

2. Ask AI:
   “Predict August streams from July data. Did AU’s campaign have an effect?”

3. Post a sticky note with:

   • Your prediction

   • AI’s prediction

   • A recommendation for StreamWave (what they should change).

👩‍💻 Your task:

1. Inspect the dataset yourself: spot duplicates, missing values, or outliers.

2. Ask AI:
   “Check this dataset for data quality issues. What problems do you see, and how would you fix them?”

3. Post a sticky note with:

   • One issue you found

   • One issue AI found

   • Do you agree with the AI’s fix?