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ARC Presentation Proposal:

The Statistical Analysis of Organic and Conventional Produce Prices

Teri Cameron, Woody Depew and Emile Phommavongsy would like to present our research from Professor Gina Reed’s Honors Statistics 2400. Our research determines statistical significance through hypothesis testing and statistical analysis of the question proposed by GA Organic, a local non-profit: Can conventional prices be used to predict organic prices? Further, we will present our findings using PowerPoint and statistical software, Minitab, demonstrating our findings by graphs and charts during our presentation.

Our research focuses on three elements of yearly statistical data for produce prices. Each presenter will model the relationship between the two variables of Organic and Conventional prices by examining produce prices from the United States Department of Agriculture (USDA). The USDA reports the averages of conventional and organic prices in major markets across the US. This data can be interpreted to analyze price trends over time. Consequently, the Atlanta, Georgia market will provide data for our variables: Romaine lettuce in 2012, Romaine lettuce in 2013, and Sweet potatoes in 2012.

We believe there is a strong positive linear relationship between organic and conventional prices. Accordingly, we present our statistical evidence through summary statistics, such as mean, median, interquartile range, and standard deviation, as well as, descriptive and inferential methods of analysis. The coefficient of determination will be used to measure “the goodness of fit” by the regression equation, illuminating a proportion of variability in the linear relationship between “x” and “y.” Our conclusion will state whether there is statistical significance between the prices of organic and conventional produce.


This is a metadata-only record.



  • Subject
    • Mathematics

  • Institution
    • Gainesville

  • Event location
    • Robinson Ballroom A

  • Event date
    • 1 April 2015

  • Date submitted

    18 July 2022

  • Additional information
    • Acknowledgements:

      Gina Reed