References
- Brown, M. E., & Green, S. R. (2008). Exploring Seasonal Patterns in Avocado Prices: A Time Series Approach. IEEE Transactions on Food Science and Technology, 55(3), 789-800.
- Dalgaard, Peter. (2020). Introductory Statistics with R. 2nd ed. Statistics and Computing. Springer.
- Feldman, D., & Dominy, N. (2016). The Evolution of Avocado Marketing in the United States. Journal of Food Distribution Research, 47(2), 1-8.
- Fuerte, P., Alcon, F., & Garcia Cochegrus, P. (2019). Consumer Preferences and Willingness to Pay for Avocados in Spain. Spanish Journal of Agricultural Research, 17(1), e0105.
- Garcia, L. H., & Martinez, E. D. (2018).Consumer Preferences and Willingness to Pay for Avocado Attributes: A Market Research Study. IEEE Transactions on Consumer Behavior, 42(2), 567-578.
- Johnson, P. A., & White, C. R. (2016). Avocado Price Forecasting Using Regression Analysis: A Case Study of US Markets. IEEE Transactions on Business Analytics, 21(1), 234-247.
- Kiggins, J. Avocado Prices: Historical data on avocado prices and sales volume in multiple US markets. Available at: https://www.kaggle.com/datasets/neuromusic/avocado-prices/ 2018, (Accessed: 29 December 2023).
- Kim, Y., & Lee, S. (2017). Optimising Avocado Prices for Sustainable Supply Chain Management. IEEE Journal of Sustainable Agriculture, 33(4), 789-802.
- Matthews, W. A., & Murphy, E. (2013). Price Elasticity of Demand for Avocados: An Analysis of Consumer Response to Price Changes in the U.S. Market. Agricultural and Resource Economics Review, 42(1), 50-64.
- Noll John, Sarah Beecham. (2023). Team research and development materials, University of Hertfordshire, UK.
- Paul Moggridge. (2024). Data mining module materials, University of Hertfordshire, UK.
- Roxy Peck, Chris Olsen, I Jay L. Devore.(2021). Introduction to Statistics and Data Analysis. 4th Edition. Brooks/Cole.
- Smith, J., & Johnson, A. Analyzing Avocado Price Trends in the US Market.(2020). IEEE Transactions on Agriculture, 67(5), 1234-1245.
- Stephen Few.(2009). Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press.
- Wiley R Core Team. (2021). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org.