We have to find 100% of the number. We can use proportion to get it
3% -----------1.5m
100% -------- x
crossmultiply now
3*x=1.5*100
3x=150 /:3 divide both sides by 3
x=50m
2. Similar situation
40% ------------1000
100% -----------x
crossmultiply
40*x=100*1000
40x=100000 /:40
x=2500 - its the answer
Answer:
1
Step-by-step explanation:
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Given:
Initial number of bacteria = 3000
With a growth constant (k) of 2.8 per hour.
To find:
The number of hours it will take to be 15,000 bacteria.
Solution:
Let P(t) be the number of bacteria after t number of hours.
The exponential growth model (continuously) is:

Where,
is the initial value, k is the growth constant and t is the number of years.
Putting
in the above formula, we get



Taking ln on both sides, we get

![[\because \ln e^x=x]](https://tex.z-dn.net/?f=%5B%5Cbecause%20%5Cln%20e%5Ex%3Dx%5D)



Therefore, the number of bacteria will be 15,000 after 0.575 hours.
Answer:
Step-by-step explanation:
World population distribution is uneven because of the different measures of the factors affecting population, such as life expectancy, economic development etc