Data Sets


Critical Values for Pearson's r


Description: Given an r and degrees of freedom, one is able to determine if r is significant at a given level.

Critical Values for Tukey’s Post Hoc Comparison Test


Description: A given result is significant if it is equal to or greater than the value found at the appropriate degrees of freedom and number of groups.

Critical Values for the F Distribution


Description: An F is significant at a level of it equals or exceeds the value shown in the table at that level and the appropriate degrees of freedom.

Critical Values for the t Distribution


Description: A given *t* is statistically significant if it is equal to or greater than the value in a row in the following table for the corresponding degrees of freedom.

Critical Values for the Chi-Square Distribution


Description: Given the degrees of freedom and an *X²* value, one can use the table below to find the statistical significance for a given result.

Code Frequency Descriptor Bubble Plot & Your Qualitative Data Analysis

Description: Mixed Methods Charts We have had requests from users on Facebook and Twitter for an explanation of charts, graphs, and bubble plots in particular. Here is an in depth look at one of our bubble plot!

Descriptor Series Part 4: Adding Descriptors via Excel in 5 Steps

Description: Using the features in Excel to add descriptor data can save you a great deal of time in your mixed methods or qualitative data analysis.

Break up with Data Dumping! - Reducing Data Dumps in Dedoose


Description: This article is for all you data dumpers out there. You know who you are. You get all the materials for your qualitative data analysis together and you upload EVERYTHING into Dedoose…all at once.

What Is Quantitative Research?

Description: As opposed to the broad-based, open-ended approach of qualitative research, the fundamental purpose of quantitative research is to seek specific answers to specific questions

What in the World is a Descriptor?

Description: Are you confused by descriptors? No worries, many people are, but they can be very useful in seeing your qualitative data from entirely new directions.

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