The differ in their mean and variance. The mean determines how far left or right they are along the variable axis (the x axis). The variance determines how narrow or wide the so-called bell shape is.
Chat with our AI personalities
You cannot. There are hundreds of different distributions. The shapes of the distributions depend on their parameters so that the same distribution can be symmetric when the parameters have some specific value, but is highly skewed - in either direction - for other values.
true - Distributions that have the same shape on both sides of the center are called symmetric
The answer will depend on what the question actually is!
There may or may not be a benefit: it depends on the underlying distributions. Using the standard normal distribution, whatever the circumstances is naive and irresponsible. Also, it depends on what parameter you are testing for. For comparing whether or not two distributions are the same, tests such as the Kolmogorov-Smirnov test or the Chi-Square goodness of fit test are often better. For testing the equality of variance, an F-test may be better.
The word for this is "similar." The same shape and the same size is "congruent."