Suppose two shots are fired at a target. Assume each shot hits with independent normally distributed coordinates, with the same means and equal unit variances. a) Find the mean of the distance between the points where the two shots strike. (Hint: You can relate this problem to the Rayleigh distribution discussed in the lecture to make the final calculations easier!) b) Find the variance of the distance between the points where the two shots strike.
Suppose two shots are fired at a target. Assume each shot hits with independent normally distributed coordinates, with the same means and equal unit variances. a) Find the mean of the distance between the points where the two shots strike. (Hint: You can relate this problem to the Rayleigh distribution discussed in the lecture to make the final calculations easier!) b) Find the variance of the distance between the points where the two shots strike.
Suppose two shots are fired at a target. Assume each shot hits with independent normally distributed coordinates, with the same means and equal unit variances. a) Find the mean of the distance between the points where the two shots strike. (Hint: You can relate this problem to the Rayleigh distribution discussed in the lecture to make the final calculations easier!) b) Find the variance of the distance between the points where the two shots strike.
Suppose two shots are fired at a target. Assume each shot hits with independent normally distributed coordinates, with the same means and equal unit variances. a) Find the mean of the distance between the points where the two shots strike. (Hint: You can relate this problem to the Rayleigh distribution discussed in the lecture to make the final calculations easier!) b) Find the variance of the distance between the points where the two shots strike.
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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