I have a data which represents some items indices (x axis) and the mean rating (y axis). I want to draw a trendline to understand the tendency of the data. Please look at the following figure. I used polyfit method in numpy, the r square is 0.05.
How can I interpret this? What else you...
I am building an agent-based simulation,
There is no real data to construct the model, a data is used to generate some values helo to define agents' decision making. There is also some randomness added to the model. I need to know the best methods that allow me to design experiments and...
There should be some variation, but this is what I got. There are many outliers as appear from the boxplot. Maybe the distribution will be ok. My question is in general, how I can show my findings if the values are very close?
I need to analyze data that is produced from a simulation. The values are very close to each other, which makes it hard for me to interpret or choosing the right plot.
For example, the following boxplot, y-axis as confidence [0,1] values that is the average of multiple actors in many runs...
I understood that beta distribution has alpha and beta parameters which define the shape of the distribution. Values from beta distribution are between 0 and 1. It means there is a difference between upper and lower limits and beta parameters(a,b)?
I want the beta should only generate between 0,1. I am asking the question but not sure if it will be possible to use beta distribution. Because beta distribution has U-shaped, I thought it might serve, as I want to get a large probability with values close to the edges.