Answer:
Step-by-step explanation:
Let X denote the amount of time spending exercise in a given week
Given that X normal (3.8, (0.8)²)
Thus we know that
i)P [ amount of time less than two hour ]
= P[x < 2]
ii)
= P[z > 2.25] ∴ symmetric
= P[0 ≤ z ≤ ∞] - P[0 ≤ z ≤ 2.25]
= 0.5 - 0.48778
= 0.0122
iii)
P[2 < x < 4]
Answer:
i) Check attached image.
ii) P(x < 2) = 0.0122
iii) Check attached image.
iv) P(2 < x < 4) = 0.5865
Step-by-step explanation:
This is a normal distribution problem with
Mean = μ = 3.8 hours per week
Standard deviation = σ = 0.8 hours per week
i) The probability that a person picked at random exercises less than 2 hours per week on a shaded graph?
P(x < 2)
First of, we normalize/standardize the 2 hours per week
The standardized score for any value is the value minus the mean then divided by the standard deviation.
z = (x - μ)/σ = (2.0 - 3.8)/0.80 = -2.25
The probability that someone picked at random exercises less than 2 hours weekly is shown in the attached image to this question.
P(x < 2) = P(z < -2.25)
ii) To determine the probability that someone picked at random exercises less than 2 hours weekly numerically
P(x < 2) = P(z < -2.25)
We'll use data from the normal probability table for these probabilities
P(x < 2) = P(z < -2.25) = 0.01222 = 0.0122 to 4 d.p
iii) The probability that a person picked at random exercises between 2 and 4 hours per week on a shaded graph?
P(2 < x < 4)
We then normalize or standardize 2 hours and 4 hours.
For 2 hours weekly,
z = -2.25
For 4 hours weekly,
z = (x - μ)/σ = (4.0 - 3.8)/0.80 = 0.25
The probability that someone picked at random exercises between 2 and 4 hours weekly is shown in the attached image to this question.
P(2 < x < 4) = P(-2.25 < z < 0.25)
iv) To determine the probability that a person picked at random exercises between 2 and 4 hours per week numerically
P(2 < x < 4) = P(-2.25 < z < 0.25)
We'll use data from the normal probability table for these probabilities
P(2 < x < 4) = P(-2.25 < z < 0.25)
= P(z < 0.25) - P(z < -2.25)
= 0.59871 - 0.01222 = 0.58649 = 0.5865
Hope this Helps!!!
A right triangle with legs measuring 3 units and 4 units has a hypotenuse measuring 5 units.
You need to find a point which has a difference in x and y of 3 and 4 or 4 and 3 from the point A(2, 6).
Look at (5, 2) and compare with A(2, 6).
Difference in x: 5 - 2 = 3
Difference in y: 6 - 2 = 4
Since the differences in x and y are 3 and 4, the hypotenuse will measure 5.
Answer: (5, 2)
b. P(A) = 2P(B)
c. P(A) = 1 - P(B)
d. P(A) + P(B) > 1
e. P(A) - P(B) < 0
f. P(A) - P(B) > 1
Answer:
a. P(A) = P(B)
c. P(A) = 1 - P(B)
a and c are true . The rest are false.
Step-by-step explanation:
Two events A and B are said to be equally likely when one event is as likely to occur as the other. In other words each event should occur in equal number in repeated trials. For example when a fair coin is tossed the head is likely to appear as the tail, and the proportion of times each side is expected to appear is 1/2.
So when the events A= {1,3,4} B = {2,4,5} are equally likely then suppose their probability is 1/2.
a. P(A) = P(B) True
1/2= 1/2
b. P(A) = 2P(B) False
1/2 is not equal to 1
c. P(A) = 1 - P(B) True
1/2= 1-1/2= 1/2
d. P(A) + P(B) > 1 False
1/2 + 1/2 is not greater than 1
e. P(A) - P(B) < 0 False
1/2-1/2= 0 is not less than 0
f. P(A) - P(B) > 1 False
1/2-1/2= 0 is not greater than 1
The relationships between the probabilities are evaluated and explained.
a. P(A) = P(B) could possibly hold if P(A) = 1/3 and P(B) = 1/3.
b. P(A) = 2P(B) could not hold, as probabilities cannot exceed 1.
c. P(A) = 1 - P(B) could possibly hold if P(A) = 2/3 and P(B) = 1/3.
d. P(A) + P(B) > 1 could possibly hold if P(A) = 1/3 and P(B) = 1/2.
e. P(A) - P(B) < 0 could not hold, as the difference between probabilities cannot be negative.
f. P(A) - P(B) > 1 could not hold, as the difference between probabilities cannot exceed 1.
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Answer:A=100 , b=25
Step-by-step explanation:
Let sales of A be x and sales of B be y
Thus
Also maximum A available is
We have find the optimal solution for
z=40x+90y
Optimal solution points
(100,25) z
(110,20) z
(110,0) z
Thus for A=100 and B=25 Optimal solution is obtained
The optimal product mix problem involves maximizing profit given certain constraints. The constraints can be expressed in terms of inequalities which can be solved using linear programming techniques such as the corner point theorem or the simplex method.
The subject of this problem is to determine the optimal product mix of two products, A and B, produced by a company. This is guided by several constraints including sales volumes, maximum output, raw material availability, and profit units.
From the problem, we have two constraints. Firstly, sales of A must be at least 80% of the total sales of A and B, and no more than 110 units of A can be sold per day. Secondly, the company cannot use more than 300 lbs of the raw material per day with usage rates of 2 lbs per unit of A and 4 lbs per unit of B.
Let the quantity of A and B sold per day be x and y respectively. The profit is given by the expression 40x + 90y. We need to maximize this expression based on the constraints. The constraints can be expressed as follows:
These constraints form a linear programming problem. By plotting these inequalities on a graph and finding the feasible region, we can use the corner point theorem or simplex method to find the optimal solution.
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Answer: She will have 1.75 pounds of clay left
Step-by-step explanation: you need to divide 51/4 and it is 12.75 and then you subtract 14-12.75 and get = 1.25
Answer:
She will have 8 and 3/4 | 8.75
Step-by-step explanation:
First you subtract the whole numbers,
14 - 5 = 9
Then because you have no fraction you take a whole number and split it into 4/4 or = 1 whole
4/4 - 1/4 = 3/4
She will have 8 and 3/4 or 8.75
Answer:
D. 7017
Step-by-step explanation:
if 24 is the first term, find 7x999, or 7x1000-7 and add 24
however a better way would be to use the formula
value=a+(n-1)d
a = the first term in the sequence (24)
n = the amount of terms you need (1000)
d = the common difference between terms (7)