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Calculate the mean, median, and mode for streams and session length. Post your results.

👩‍💻 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?

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Here’s the StreamWave dataset with user activity (streams, skip rate, session length, likes, reviews).

👩‍💻 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)

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Now look for patterns and comparisons between groups

👩‍💻 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?

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Use the dataset to forecast August streams and recommend improvements.

👩‍💻 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).

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Not all data is clean — some is messy, duplicated, or missing.

👩‍💻 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?