If the mean of a poisson variable X is 1, what is P(x = at least one) ?
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![If the mean of a poisson variable X is 1, what is P(x = at least one)?
[a] 0.456
[b] 0.821
[c] 0.632
[d] 0.254](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fefd61fce-ffcb-4548-8256-1a303637797b%2F4c414c69-26b9-4aa4-9e0f-c55b6430e31d%2Fzhctu9_processed.png&w=3840&q=75)
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- Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.P(z<2.25)=P(z < 2.56) =
- Assume x is exponentially distributed with a mean of 4. Find: a.P(X=2) b.P(X<2) c.P(X>=2) d.P(2 < X < 4)An interpolation function, P(x), for e 2 x between x=0 and x=.5 was found using the following data points (0, 1), (0.1, 1.2214), (0.2, 1.4918), (0.3, 1.8221), (0.4, 2.2255), and (0.5, 2.7183). What is the upper bound of the approximation at P(0.25)? a) ( 0.25 ) ( 0.25 – 0.1) ( 0.25 – 0.2 ) ( 0.25 – 0.3 )( 0.25 – 0.4 ) (0.25 – 0.5 ) 6 ! 2 6 e 0.5 b) ( 0.25 ) ( 0.25 - 0.1) (0.25 – 0.2 ) ( 0.25 - 0.3 ) ( 0.25 – 0.4 ) ( 0.25 – 0.5 ) 5!25 e 0.5 c) ( 0.25 ) ( 0.25 – 0.1) ( 0.25 – 0.2 ) ( 0.25 – 0.3 ) (0.25 – 0.4 ) ( 0.25 – 0.5 ) 6 ! 2 6 e d) ( 0.25 ) ( 0.25 – 0.1) ( 0.25 – 0.2) ( 0.25 – 0.3 ) ( 0.25 – 0.4)( 0.25 – 0.5 ) 5 ! 25 e - - (0.25)(0.25-0.1)(0.25-0.2)(0.25-0.3)(0.25–0.4)(0.25–0.5) ,6 ,0.5 6! (0.25)(0.25–0.1)(0.25–0.2)(0.25–0.3)(0.25,0.4)(0.25–0.5) 25 0.5 5! O (0.25)(0.25–0.1)(0.25–0.2)(0.25-0.3)(0.25-0.4)(0.25–0.5) -26e 6! (0.25)(0.25–0.1)(0.25–0.2)(0.25–0.3)(0.25–0.4)(0.25–0.5) ,5. 5!A company claims that the number of defective items manufactured during each run of making 100 of their products is independent of the number from other runs and that the proportion of defectives is not more than 3%. Assuming that the defective rate for each run is 3% Which of the following can be used to determine whether x = 8 is unusually a high number of defective items on the next run of 100 of their products?
