Do you know what all the symbols stand for? Re-write the two sentences below by replacing all symbols with the appropriate words and fill in the blank at the end with the correct numeric value to make the second sentence true. Assume that X represents the normal random variable described in the first sentence. Brain weights are normally distributed with σ = 0.11 kg and μ = 1.22 kg. The P(X > 1.4 kg) = _________.
Do you know what all the symbols stand for? Re-write the two sentences below by replacing all symbols with the appropriate words and fill in the blank at the end with the correct numeric value to make the second sentence true. Assume that X represents the normal random variable described in the first sentence. Brain weights are normally distributed with σ = 0.11 kg and μ = 1.22 kg. The P(X > 1.4 kg) = _________.
Do you know what all the symbols stand for? Re-write the two sentences below by replacing all symbols with the appropriate words and fill in the blank at the end with the correct numeric value to make the second sentence true. Assume that X represents the normal random variable described in the first sentence. Brain weights are normally distributed with σ = 0.11 kg and μ = 1.22 kg. The P(X > 1.4 kg) = _________.
Do you know what all the symbols stand for? Re-write the two sentences below by replacing all symbols with the appropriate words and fill in the blank at the end with the correct numeric value to make the second sentence true. Assume that X represents the normal random variable described in the first sentence.
Brain weights are normally distributed with
σ
= 0.11 kg and
μ
= 1.22 kg. The P(X > 1.4 kg) = _________.
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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