Is there a good statistical package that is not too expensive?

[JenniferMurphy]

Can anyone recommend a good statistical package that is not too expensive or too difficult to master? My immediate need is the ability to test some experimental data to see if it is normally distributed -- that is if it follows (fits) a normal distribution curve. And if it does, what the mean and std dev are.

I would prefer an Excel add-in, but a separate statistical package is also OK. I also need it to have a learning curve that does not require going back to school for an advanced degree. I have seen several recommendations for R, but also caveats about the learning curve.

I do not expect it to be free, but I cannot afford hundreds of dollars.

Thanks for any leads.

 

[KRice]

I too would recommend R...free and open source. Some years ago, there was an RExcel add-in that provided a lot of R functionality through Excel, but I believe that package became commercialized. I don't know if it is still available. The advantage was that certain advanced functions from R could be run directly from an Excel worksheet and the results returned could be used in subsequent Excel formulas. More recently I looked into this and discovered a newer package, but I haven't tried it yet:

BERT | Basic Excel R Tookit

The Q-Q plot and the Tukey Lambda methodology are commonly used as normality assessments, shown in the video and illustrated in a file attached to another post that I just responded to at:

How to fit a truncated normal distribution to existing data?

I have some data that I have been collecting from a game of solitaire. When I plot it opn a scatter chart, it looks like a normal distribution -- actually a truncated normal distribution. I have been able to more or less fit a standard normal distribution to the data after some trial and error...

www.mrexcel.com

 

[JenniferMurphy]

I too would recommend R...free and open source. Some years ago, there was an RExcel add-in that provided a lot of R functionality through Excel, but I believe that package became commercialized. I don't know if it is still available. The advantage was that certain advanced functions from R could be run directly from an Excel worksheet and the results returned could be used in subsequent Excel formulas. More recently I looked into this and discovered a newer package, but I haven't tried it yet:

BERT | Basic Excel R Tookit

The Q-Q plot and the Tukey Lambda methodology are commonly used as normality assessments, shown in the video and illustrated in a file attached to another post that I just responded to at:

How to fit a truncated normal distribution to existing data?

I have some data that I have been collecting from a game of solitaire. When I plot it opn a scatter chart, it looks like a normal distribution -- actually a truncated normal distribution. I have been able to more or less fit a standard normal distribution to the data after some trial and error...

www.mrexcel.com

I have no doubt that R is the way to go. My concern is that it is over my head. This is just a little spare-time project that I am doing mostly out of curiosity. I'll check out the information you posted on the other thread. And if I get up the courage, I'l take a look at R.

Thanks so much.