challenge and extra reading

pull/34/head
Jen Looper 4 years ago
parent b5f802fcef
commit 2b5730a7ad

@ -347,11 +347,11 @@ plt.show()
A very nice plot, showing a model with good accuracy. Well done!
## 🚀Challenge
TBD
## [Post-lecture quiz](link-to-quiz-app)
Dig into the ways to test the accuracy of a Time Series Model. We touch on MAPE in this lesson, but are there other methods you could use? Research them and annotate them. A helpful document can be found [here](https://otexts.com/fpp2/accuracy.html)
## [Post-lecture quiz](link-to-quiz-app)
## Review & Self Study
TBD
This lesson touches on only the basics of Time Series Forecasting with ARIMA. Take some time to deepen your knowledge by digging into [this repository](https://microsoft.github.io/forecasting/) and its various model types to learn other ways to build Time Series models.
**Assignment**: [Assignment Name](assignment.md)
**Assignment**: [A new ARIMA model](assignment.md)

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# [Assignment Name]
# A new ARIMA model
## Instructions
Now that you have built an ARIMA model, build a new one with fresh data (try one of [these datasets from Duke](http://www2.stat.duke.edu/~mw/ts_data_sets.html). Annotate your work in a notebook, visualize the data and your model, and test its accuracy using MAPE.
## Rubric
| Criteria | Exemplary | Adequate | Needs Improvement |
| -------- | --------- | -------- | ----------------- |
| | | | |
| Criteria | Exemplary | Adequate | Needs Improvement |
| -------- | ------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------- | ----------------------------------- |
| | A notebook is presented with a new ARIMA model built, tested and explained with visualizations and accuracy stated. | The notebook presented is not annotated or contains bugs | An incomplete notebook is presented |

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