Answer: 0.9996
Step-by-step explanation:
Given : The body temperatures of adults are normally distributed with a mean of 98.6° F and a standard deviation of 0.60° F.
Sample size : n=25
Let x be the random variable that represents the body temperatures of adults.
z-score :
For x= 99° F
Now, the probability that their mean body temperature is less than 99° F will be :-
Hence, the probability that their mean body temperature is less than 99° F = 0.9996
To find the probability that the mean body temperature of 25 randomly selected adults is less than 99°F, we can use the Central Limit Theorem and calculate the Z-score. The mean body temperature of adults is 98.6°F with a standard deviation of 0.60°F. The sample size is 25.
To find the probability that the mean body temperature of 25 randomly selected adults is less than 99°F, we can use the Central Limit Theorem. According to the Central Limit Theorem, the sampling distribution of the sample mean follows a normal distribution with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size.
In this case, the mean body temperature of adults is 98.6°F with a standard deviation of 0.60°F. The sample size is 25. So, the mean of the sampling distribution would still be 98.6°F, but the standard deviation would be 0.60°F divided by the square root of 25, which is 0.12°F.
Now, we can use the Z-score formula to find the probability that the mean body temperature is less than 99°F. The Z-score is calculated by subtracting the population mean from the desired value (99) and dividing it by the standard deviation of the sampling distribution (0.12). We can then use a Z-table or calculator to find the probability associated with the Z-score.
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The solution to inequality is,
⇒ y ≤ - 1
We have to give that,
An inequality to solve,
5y + 9 ≤ 4
Now, Simplify the inequality as,
⇒ 5y + 9 ≤ 4
Subtract 9 on both sides,
⇒ 5y + 9 - 9 ≤ 4 - 9
⇒ 5y ≤ - 5
⇒ y ≤ - 5/5
⇒ y ≤ - 1
Therefore, The solution is,
⇒ y ≤ - 1
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Step-by-step explanation:
The probability that the dealer will be fined is 0.0948
To find p(a <= Z <= b) = F(b) - F(a)
P(X < 20) = (20 - 30.5)/3.4489
= -10.5/3.4489
= -3.0444
= P(Z < -3.0444) from standard normal table
= 0.00117
P(X < 26) = (26 - 30.5)/3.4489
= -4.5/3.4489 = -1.3048
= P(Z < -1.3048) From standard normal table
= 0.09599
P(20 < x < 26) = 0.09599 - 0.00117 = 0.0948
The answer in this question is 0.0948
To determine the probabilities requested, the normal distribution model is employed. The number of favorable reports follows a normal distribution with mean μ = 0.73 * 69 and standard deviation σ. The probabilities are then calculated from the z-scores corresponding to the given ranges, using standard normal distribution tables or calculators.
To calculate the probability that the dealership will be fined or dissolved, we use the normal distribution model because the sample size is large enough, and the variable (the number of customers who report favorably) can be approximated by a normal distribution. Given that 73% of the dealer's customers report favorably, and we have a sample size of 69 customers, we can find the mean (μ) and the standard deviation (σ) of the distribution. The mean (μ) is 0.73 * 69, and the standard deviation (σ) is .
To find the z-score for the number of favorable reports between 40 and 46, we use the formula z = (x - μ) / σ. Then we find the corresponding probabilities using the standard normal distribution table or a calculator providing such functionalities. To find the probability that the dealer will be fined, we subtract the cumulative probability at the lower boundary from that at the upper boundary. Similarly, to find the probability that the dealership will be dissolved (fewer than 40 favorable reports), we find the cumulative probability at 39 (since it's fewer than 40) and use it directly because it represents all values below that number.
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