Statistix vs BlueSky Statistics: Which is a better fit?

Speed and reliability of results is the most stunning result from this software.

Error recovery is a bit harsh. If you encounter an error, the module shuts down and you need to start over.

I really like the menu-driven format. In this age of programs like "R", it is really nice to be able to do some processes without programming.

Statistix limits the ability to perform ANOVA with uneven group sizes. In addition, error messages sometimes not clear and identifying the error for repair can be tricky.

Great program for someone without the best math background or just someone looking to have data analyzed in a quick and easy way.

There is very little that I dislike about Statistix when using it for data exploration.

The assistance i get for basic statistics is enourmous and its user friendly features makes it very easy to use even for starters. I am also impressed by the speed at which it executes a task.

The only time I couldn't use Statistix for a publishable analysis was when I had a two-factor, repeated-measures design with unequal sample sizes per treatment (because of plant mortality).

It is well thought out combining the best features from both SPSS and R into a single packageAnd outstanding support team with technical understanding of both the software and statistical methods.

The user interface can be any enemy sometimes. I struggle to set it up with smaller displays.

I had a good experience with bluesky statistics. I have difficulties with stats and this application is pretty useful.

Poor editing or seting up variables. Not able to connect to R without a lot of problems.

Johnny M. J

Data Scientist

I personally appreciate the ability to build and save models for subsequent implementation and deployment while having the option to tune the models with R code.

Image export is awkward- sometimes slow to launch.

Bluesky statistical software is an incredibly powerful tool that has been widely recognized for its ability to perform complex statistical analyses with ease.

In ANCOVA it had some deficits. For example it was hard to find the source of differences.