Answer:
5
Step-by-step explanation:
rate of change = slope = 5
Answer:
1) 5.44, 2) 3.9
Step-by-step explanation:
1) a/b + 2b - a^2 when a = 1.4 and b = 0.2
plug in the values:
1.4/0.2 + 2(0.2) - (1.4)^2 = 7 + 0.4 - 1.96 = 5.44
2) a[b-2c]^3 - d/e when a = 2, b = -0.75, c = -1, d = 0, e = -12 5/7 (rewritten to -89/7 = 12.71)
again, plug in the values:
2[-0.75-2(-1)]^3 - 0/12.71 = 2[1.25]^3 - 0 = 2[1.95] = 3.9
Answer:
Therefore, the probability that at least half of them need to wait more than 10 minutes is <em>0.0031</em>.
Step-by-step explanation:
The formula for the probability of an exponential distribution is:
P(x < b) = 1 - e^(b/3)
Using the complement rule, we can determine the probability of a customer having to wait more than 10 minutes, by:
p = P(x > 10)
= 1 - P(x < 10)
= 1 - (1 - e^(-10/10) )
= e⁻¹
= 0.3679
The z-score is the difference in sample size and the population mean, divided by the standard deviation:
z = (p' - p) / √[p(1 - p) / n]
= (0.5 - 0.3679) / √[0.3679(1 - 0.3679) / 100)]
= 2.7393
Therefore, using the probability table, you find that the corresponding probability is:
P(p' ≥ 0.5) = P(z > 2.7393)
<em>P(p' ≥ 0.5) = 0.0031</em>
<em></em>
Therefore, the probability that at least half of them need to wait more than 10 minutes is <em>0.0031</em>.
Answer:
Step-by-step explanation:
Give the rate of change of sales revenue of a store modeled by the equation 
. The Total sales revenue function S(t) can be gotten by integrating the function given as shown;
a) The total sales for the first week after the campaign ends (t = 0 to t = 7) is expressed as shown;
Total sales = S(7) - S(0)
= 6,860 - 0
Total sales for the first week = $6,860
b) The total sales for the secondweek after the campaign ends (t = 7 to t = 14) is expressed as shown;
Total sales for the second week = S(14)-S(7)
Given S(7) = 6,860
To get S(14);
The total sales for the second week after campaign ends = 13,720 - 6,860
= $6,860
Answer:
i think it's 37.7
Step-by-step explanation:
