In order to answer this question it is important, first, to be certain that the theoretical probability (not probality!) can be calculated. For example, there is a probability that the first car that I see being driven on the next day [tomorrow] is black but I challenge anyone to calculate the theoretical probability. No one, not even I, know when I will wake up tomorrow (assuming that I live to wake up), when I draw my curtains and when look into the street. The number of black cars and non-black cars in my locality can be found, but it could be a car from somewhere else which just happens to drive past at the critical moment.
Assuming there was a theoretical probability, the experimental probability would be better than would be obtained from 999 trials and not as good as 1001 trials. Any other statements would depend on the distribution of the variable being observed.
Experimental probability is obtained by repeatedly carrying out an experiment. It is the ratio of the number of favourable outcomes and the total number of experiments. Theoretical probability is calculated from a model of the experiment using the laws of physics or nature (or whatever).
the experimental mole ratio has a bigger penis
Yes.
The control is the standard used to compare with the experimental results.
experimental control
You'll find her G spot someday son
The experimental group is use to compare with the control group, and viceversa. The experimental group is the group that we change the variable to experiment it's effects, as twcontrol group is the'original' experiment's results. Such a when we want to know the effect of changing a variable.
It is called the control variable. It is used to compare to your experimental results.
A hypothesis is an educated guess and a theory is close to what a hypothesis is. A theory is the scientific process that is thought to be true. An experimental conclusion is the results to an experiment.
A control sample or control group is used to compare with the experimental group or sample. The control sample ideally, should be exactly the same as the experimental sample except that you don't give your experimental treatment to the control sample. Afterwards you compare the 2 samples to see if your experimental treatment had any kind of effect. The control is like a reference point.
There are a number of statistical tests that are designed for this purpose. The Chi-squared and Kolmogorov-Smirnov tests are two of the better known ways.
Experimental data is an important component of any scientific paper.After looking at the data, we can compare that to our hypothesis and see if it matches to our tentative idea.Analysis of experimental data also helps us to draw a conclusion of an experiment.