Respuesta :
Answer:
P(T<683) = 0.1587 = 15.87% ≈ 16%.
Step-by-step explanation:
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.
Sum of normal variables:
When two normal variables are added, the mean is the sum of the means, while the standard deviation is the square root of the sum of the variances.
The weights of these candles have a mean of 500g and a standard deviation of 15g. The weights of the candle stands have a mean of 200g and a standard deviation of 8g.
The package consists of one candle of each type. So
[tex]\mu = 500 + 200 = 700[/tex]
[tex]\sigma = \sqrt{15^2 + 8^2} = 17[/tex]
Find the probability that the total weight is under 683g.
This is the pvalue of Z when X = 683.
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
[tex]Z = \frac{683 - 700}{17}[/tex]
[tex]Z = -1[/tex]
[tex]Z = -1[/tex] has a pvalue of 0.1587
So
P(T<683) = 0.1587 = 15.87% ≈ 16%.
