If you have a data set of n items, the data are continuous variables, the data set is unimodal, and the data set is too skewed to use the normal distribution, which probability distribution should you use to calculate probabilities? Discrete uniform distribution Binomial distribution Poisson distribution Hypergeometric distribution Geometric distribution Uniform continuous distribution Standard normal distribution Exponential distribution Triangular distribution None of the above
If you have a data set of n items, the data are continuous variables, the data set is unimodal, and the data set is too skewed to use the normal distribution, which probability distribution should you use to calculate probabilities? Discrete uniform distribution Binomial distribution Poisson distribution Hypergeometric distribution Geometric distribution Uniform continuous distribution Standard normal distribution Exponential distribution Triangular distribution None of the above
If you have a data set of n items, the data are continuous variables, the data set is unimodal, and the data set is too skewed to use the normal distribution, which probability distribution should you use to calculate probabilities? Discrete uniform distribution Binomial distribution Poisson distribution Hypergeometric distribution Geometric distribution Uniform continuous distribution Standard normal distribution Exponential distribution Triangular distribution None of the above
If you have a data set of n items, the data are continuous variables, the data set is unimodal, and the data set is too skewed to use the normal distribution, which probability distribution should you use to calculate probabilities?
Discrete uniform distribution
Binomial distribution
Poisson distribution
Hypergeometric distribution
Geometric distribution
Uniform continuous distribution
Standard normal distribution
Exponential distribution
Triangular distribution
None of the above
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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