Answer:
Step-by-step explanation:
We have to find out which two events are disjoint.
Two events are disjoint if both cannot happen simultaneously or Probability of both occurring is strictly 0.
a) Choose a student at random from a statistics class. Event A is that the student is a junior. Event B is that the student is a senior.
These are disjoint because a student cannot be a senior and junior both.
b) Choose a student at random from a statistics class. Event A is that the student is a psychology major. Event B is that the student is a statistics major.
Disjoint because same student cannot have psychology as well as statistics as major
c. Choose a student at random from a statistics class. Event A is that the student is at least 5'8" tall. Event B is that the student weighs at least 160 pounds.
These cannot be disjoint because there are chances for some students to be taller than 5 feet 8 inches and also having weight more than 160 lbs.
Answer:
Step-by-step explanation:
We want to find the fraction that is equivalent to the fraction below:
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Let us put the fraction above in a simpler form:
We can factorise the numerator with 3c and the denominator with -2.
Therefore, we see that is equivalent to
Answer:
Given the initial population of termites = 60
After 7 days the population of termites = 225
Step-by-step explanation:
We have given the initial termites and the population of termites after 7 days. Now we are required to find the exponential growth model that will help to predict the future population of termites.
We have, Y = Ca^x
When the value of x is zero then population (Y) is 60 termites.
Y = Ca^x
60 = Ca^x
Now, Y = 60a^x
At x = 7 days
Y = 225
225 = 60 a^7
a^7 = 225/60
a = 1.2078
Thus, final population will be, Y = 60(1.2078)^x
Pn(Z>zp)=1−p%
Given a variable X following a normal distribution with mean μ and standard deviation σ, the area below the curve that corresponds to all values that are less than a that is, X<a
is the probability P(X<a). This probability is usually calculated by converting the variable X to a standard normal variable Z (forming z scores) defined by:
The variable Z follows the standard normal distribution with a mean of 0 and a standard deviation of 1.
The standard normal probabilities are typically found by using the standard normal tables or other computational means such as calculators or software.
Pn(Z>zp)=1−p%
Here Pn is the probability for the standard normal variable.
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