The growth of a population of bacteria can be modeled by an exponential function. The graph models the population of the bacteri
1 answer:
Answer:
t ≥0
Step-by-step explanation:
Given the information:
The initial population: 500
The graph models the population of the bacteria colony P(t) as a function of the time t, in weeks,
=> our function is: P(t) =500* where b is the base number and it is ≥0
- What is the domain of the function?
The domain of exponential functions is all real numbers greater than zero
<=> t ≥0 (because t present for the time and time can not have negative value)
- What does the domain represent in this context?
t is the independent variable is this exponential function and the population of bacteria depends on the change of t.
Because it is the growth function so the range (the population of bacteria) increase over its domain (the time)
Hope it will find you well.
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Answer:
a)
And we can find this probability with this difference and with the normal standard table or excel:
b)
And we can use the z score defined by:
And using the limits we got:
And we want to find this probability:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Part a
Let X the random variable that represent the resitances of a population, and for this case we know the distribution for X is given by:
Where and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability with this difference and with the normal standard table or excel:
Part b
We select a sample size of n =4. And since the distribution for X is normal then we know that the distribution for the sample mean is given by:
And we want this probability:
And we can use the z score defined by:
And using the limits we got:
And we want to find this probability: