Project 1 reminder and details
Example project walk-through using carrot price data
Three parts:
Presentation video
Written report (added to your website)
Peer evaluation
Your project should tell a data-driven story.
We are analysts at The Carrot Project.
You are growers attending a workshop.
Trend (orange) calculated from STL decomposition using LOESS. The Producer Price Index (PPI) program measures the average change over time in the selling prices received by domestic producers for their output.
We will evaluate trends and possible causes.
We will use decomposition to separate trends, seasonality, and residuals.
We will forecast future prices using a statistical model.
Explore the data by visualizing trends and identifying structural breaks
Decompose carrot prices to understand underlying factors contributing to changing prices, specifically trends, seasonality, and residuals.
Forecast carrot prices over the next 5 years to predict trends.
Interpret prediction intervals to evaluate the uncertainty in the forecast.
Connect our findings to industry decisions.
Our data come from the Federal Reserve of Kansas (FRED) Economic Data, accessed via API.
The data report historical prices for carrots from 1980 to 2023.
To understand our data, we calculate summary statistics (mean, standard deviation, range) of our data.
Statistic | Value |
---|---|
Min | 65.0 |
1st Quartile | 98.9 |
Median | 134.3 |
Mean | 145.4 |
3rd Quartile | 186.8 |
Max | 311.9 |
Additive decomposition of PPI
Does the seasonal pattern dominate price fluctuations? No, even though seasonality is present, long-term trends appear more influential.
Is there a clear long-term trend? Yes, prices exhibit a steady upward trend over time.
Are there notable deviations in the residuals? Yes, suggesting external shocks or irregular price movements.
We will use an Exponential Smoothing (ETS) model
We will forecast prices for 5 years
Forecast based on exponential smoothing of components
Extract and visualize uncertainty in the forecast
Interpret how external factors could impact the forecast range
Carrot prices are near all time highs.
If current trends continue, prices could rise further.
If trends stabilize, prices may level off but remain high.
External factors like fertilizer cost, demand, and seasonality are important factors contributing to price movements.
Present summary statistics of your data
Use decomposition to analyze trends and seasonality
Construct a forecast and estimate prediction intervals
Interpret the results and discuss assumptions
Use the forecast to answer your research question
Make sure your final presentation includes a clear narrative, data visuals, and well-explained conclusions