X/13 2/7
X=2/7*(13)
X=26/7 Final Answer
P(t) = P₀ e^(kt)
<span>Where P₀ is the initial population, </span>
<span>P(t) is the population after "t" time. </span>
<span>t is your rate (can be hours, days, years, etc. in this case, hours) </span>
<span>k is the growth constant for this particular problem. </span>
<span>So using the information given, solve for k: </span>
<span>P₀ = 2000 </span>
<span>P(4) = 2600 </span>
<span>P(t) = P₀ e^(kt) </span>
<span>2600 = 2000e^(k * 4) </span>
<span>1.3 = e^(4k) </span>
<span>Natural log of both sides: </span>
<span>ln(1.3) = 4k </span>
<span>k = ln(1.3) / 4 </span>
<span>Now that we have a value for "k", use that, the same P₀, then solve for P(17): </span>
<span>P(t) = P₀ e^(kt) </span>
<span>P(17) = 2000 e^(17ln(1.3) / 4) </span>
<span>Using a calculator to get ln(1.3) then to simplify from there, we get: </span>
<span>P(17) ≈ 2000 e^(17 * 0.262364 / 4) </span>
<span>P(17) ≈ 2000 e^(4.460188 / 4) </span>
<span>P(17) ≈ 2000 e^(1.115047) </span>
<span>P(17) ≈ 2000 * 3.0497 </span>
<span>P(17) ≈ 6099.4 </span>
<span>Rounded to the nearest unit: </span>
<span>P(17) ≈ 6099 bacteria hope i could help =)))</span>
Answer:
g(f(0)) = 5
Step-by-step explanation:
To evaluate g(f(0)), evaluate f(0) then substitute this value into g(x)
From the table
when x = 0, then f(0) = 1
Then
g(1)
when x = 1 , then g(x) = 5
Thus
g(f(0)) = 5
Part a)
It was given that 3% of patients gained weight as a side effect.
This means
The mean is
The standard deviation is
We want to find the probability that exactly 24 patients will gain weight as side effect.
P(X=24)
We apply the Continuity Correction Factor(CCF)
P(24-0.5<X<24+0.5)=P(23.5<X<24.5)
We convert to z-scores.
Part b) We want to find the probability that 24 or fewer patients will gain weight as a side effect.
P(X≤24)
We apply the continuity correction factor to get;
P(X<24+0.5)=P(X<24.5)
We convert to z-scores to get:
Part c)
We want to find the probability that
11 or more patients will gain weight as a side effect.
P(X≥11)
Apply correction factor to get:
P(X>11-0.5)=P(X>10.5)
We convert to z-scores:
Part d)
We want to find the probability that:
between 24 and 28, inclusive, will gain weight as a side effect.
P(24≤X≤28)=
P(23.5≤X≤28.5)
Convert to z-scores:
