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

Warning: The maximum file size should not exceed 10MB

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 described in the webinar. Each row corresponds to a plant, and we count the number of cotelydons. The generation column identifies if the plant is "parent" (p) or "offspring" (O). The parents column shows which were the parents of that plant. For example, 2x2 means that both parents had 2 cotelydons.

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

Data Analysis Option:

Equal variance: The standard t test assumes equal variances on the two groups. If the user checks this option, the standard t test is run, but if the user unchecks this option, then the Welch t test is run instead (that does not assume equal variances).

T test: Statistical test of the null hypothesis of equality of means of a numerical variable ("Quantity") on two groups ("Group variable"). If the selected group variable has more than two categories, the user will select the two groups to compare.

How to interpret the result? If the p-value is less than 0.05, we reject the null hypothesis of equality of means. The confidence interval represents the interval for the difference of means.

Assumptions of t test: The t test assumes normality, equal variance and independence. Take a look at this link that illustrate how important normality and independence are in the t test results.

Chi-square test: Pearson's chi-square test is used to determine whether there is a statistically significant difference between the expected frequencies and the observed frequencies in one or more categories of a contingency table

How to interpret the result? If the p-value is less than 0.05, we reject the null hypothesis that in the population there is no difference between the classes (reject independence).