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Answer :
To find [tex]P(X < 160)[/tex] for a normal random variable [tex]X[/tex], which represents the weight of a 40-year-old man, we know the mean ([tex]\mu = 165[/tex] pounds) and the standard deviation ([tex]\sigma = 30[/tex] pounds). We will use the properties of the normal distribution to calculate this probability.
Convert the raw score to a z-score:
The z-score formula is:
[tex]z = \frac{X - \mu}{\sigma}[/tex]Plug in the values:
[tex]z = \frac{160 - 165}{30} = \frac{-5}{30} = -0.1667[/tex]Find the probability from the z-table:
A z-score of [tex]-0.1667[/tex] corresponds to a position on the standard normal distribution. Use a standard normal distribution table (z-table) to find [tex]P(Z < -0.1667)[/tex].
The z-table gives the probability that a standard normal random variable is less than the given z-score.
For [tex]z = -0.1667[/tex], the probability [tex]P(Z < -0.1667) \approx 0.4345[/tex].
Interpret the result:
- This means that there is approximately a 43.45% probability that a randomly selected 40-year-old man weighing according to this normal distribution weighs less than 160 pounds.
Therefore, the probability [tex]P(X < 160)[/tex] is approximately 0.4345 when rounded to four decimal places.
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