/Boxplots-Hypothesis-Testings-for-Fruit-Fly-Behaviour

Conducting one-factor analysis of variance and its assumptions (normality and homogeneity of variance) with R if two groups of data show statistically different behavior. Visualizing data with boxplots to understand if the given state of the fly (fed/starved) affects the feeding and resting pattern.

Primary LanguageR

Fruit Fly Behaviour: Creating Boxplots and applying ANOVA

A research team at the University of Ottawa studied the resting and eating behaviour of fed and starved fruit flies in a closed lab settting. Data was collected at the lab and was segmented as either eating or resting intervals. Data was cleaned and analyzed with R. Then, the data is tested for normality and homogeneity of variance, which are assumptions to the one-factor analysis of variance. Lastly, the data is visualized using boxplots to understand if the given state of the fly (fed/starved) affects the feeding and resting pattern.

  • Read key.pdf for details on the objective, assumptions and method of the analysis
  • Script 1. prepare_data.R cleans and prepares the excel file data for analysis
  • The transformed dataset is saved as compare_boxes.txt which is obtained after running the script 1. prepare_data.R
  • Script 2. visualize_data.R visualizes the data as boxplots
  • Script 3. analyze_data.R statistically analyzes the data and tests the assumptions associated with the analysis
  • Finally, results.pdf summarizes the restuls and their interpretation

Please contact me at yjeon009@uottawa.ca for inquiries!