One quick way to test how similar a data set is to this mathematical object is to draw a Q-Q plot and look for a linear relationship. Because it is described by a variant of the function "e to the negative x squared", its CDF is based on the error function. This mathematical object is equal to the t-distribution in the limit when t goes to infinity. Z-scores are computed based on a standard version of it. The means of random variables from any distribution will follow one of these distributions, according to the central limit theorem. For 10 points, name this probability distribution that is described by the 68-95-99.7 rule and is shaped like
One quick way to test how similar a data set is to this mathematical object is to draw a Q-Q plot and look for a linear relationship. Because it is described by a variant of the function "e to the negative x squared", its CDF is based on the error function. This mathematical object is equal to the t-distribution in the limit when t goes to infinity. Z-scores are computed based on a standard version of it. The means of random variables from any distribution will follow one of these distributions, according to the central limit theorem. For 10 points, name this probability distribution that is described by the 68-95-99.7 rule and is shaped like a bell.
One quick way to test how similar a data set is to this mathematical object is to draw a Q-Q plot and look for a linear relationship.
normal distribution [or Gaussian distribution; accept standard normal distribution; accept z-distribution until "Z-scores" is read]