Answer:
47.8
Step-by-step explanation:
Answer:
the answer is D
Step-by-step explanation:
dram is 40 film is 24 40 divided by 8 is 5 and 24 divided by 8 is 3 so it equals 5:3
Answer:
y'(t) = k(700,000-y(t)) k>0 is the constant of proportionality
y(0) =0
Step-by-step explanation:
(a.) Formulate a differential equation and initial condition for y(t) = the number of people who have heard the news t days after it has happened.
If we suppose that news spreads through a city of fixed size of 700,000 people at a time rate proportional to the number of people who have not heard the news that means
<em>dy/dt = k(700,000-y(t)) </em>where k is some constant of proportionality.
Since no one has heard the news at first, we have
<em>y(0) = 0 (initial condition)
</em>
We can then state the initial value problem as
y'(t) = k(700,000-y(t))
y(0) =0
Answer:
-3 is just the answer of the equation.....you must solve x so turn it into 1x and solve it.....plz mark me brainliest
Step-by-step explanation:
Answer:
The probability that a household in Maryland has an annual income of X or more is 1 subtracted by the p-value of 
, in which 
is the mean income and 
is the standard deviation of incomes.
Step-by-step explanation:
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation , the z-score of a measure X is given by:
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.
In this question:
Mean , standard deviation
What is the probability that a household in Maryland has an annual income of X or more?
The probability that a household in Maryland has an annual income of X or more is 1 subtracted by the p-value of , in which is the mean income and is the standard deviation of incomes.
