Data in delimited text files can be separated by comma, tab or semicolon. For example, Excel data can be exported in .csv (comma separated) or .tab (tab separated) format. A template of the spreadsheet can be found here

Warning: The maximum file size should not exceed 10MB

Warning: The uploaded file must have a column named Experiment. A template of the spreadsheet can be found here

Click the checkbox if file has a header:

The sample data included here mimics the structure of a dataset the students will have after following the experiments in class. A template of the spreadsheet can be found here.

Mosaic plot: Plot to visualize contigency tables of frequencies among categorical variables

Data Visualization:

Please select the two variables to use in the plot and click on the button to generate the plot.

About colors: Click the FAQ tab in the left sidebar for more details on the color palettes

Violin Plot: Plot a numerical variable ("Quantity") by groups ("Group variable"). It is similar to the box plot but it also shows the distribution and spread of the data.

Data Visualization:

Please select the two variables to use in the plot and click on the button to generate the plot.

Add data points: This option allows the user to add a scatterplot of the data where each dot corresponds to one observation (row) in the dataset.

About colors: Click the FAQ tab in the left sidebar for more details on the color palettes

Box Plot: Plot a numerical variable ("Quantity") by groups ("Group variable"). Solid black line in the box represents the median, and the upper and lower edges of the box represent the 3rd and 1st quartiles respectively.

Data Visualization:

Please select the two variables to use in the plot and click on the button to generate the plot.

Add data points: This option allows the user to add a scatterplot of the data where each dot corresponds to one observation (row) in the dataset.

About colors: Click the FAQ tab in the left sidebar for more details on color palettes

Scatter Plot: Plot that shows the relationship between two numerical variables

Data Visualization:

Please select the two variables to use in the plot and click on the button to generate the plot.

About colors: Click the FAQ tab in the left sidebar for more details on the color palettes

Densities Plot: Plot that represents the distribution of a numeric variable (like a smoothed histogram)

Data Visualization:

Please select the two variables to use in the plot and click on the button to generate the plot.

About colors: Click the FAQ tab in the left sidebar for more details on the color palettes

Statistical summary: We present a table with the number of plants (count), average (mean) and standard deviation (sd) for the selected plant phenotype (Quantity) by different treatments (Group Variable)

Linear model test: We test whether different treatments (Group Variable) have different values of a measured plant phenotype (Quantity) with a t test.

How to interpret the result? The group variable represents the different treatments in the experiment which is internally encoded as binary variables. For example, for the light experiment in the sample data, there are two treatments: light (L) and dark (D). In the coefficients table, there is an intercept which corresponds to the average estimated quantity (whatever plant phenotype chosen) for the dark treatment, and a Group_VariableL which corresponds to the difference in averages between the dark treatment and the light treatment. If this coefficient is close to zero, then we do not have evidence of different plant phenotypes on different treatments.