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Damm [24]
2 years ago
10

(x+2) (x-2)=? (n+m) (n-m)=? (r+9) ( r-9)=?

Mathematics
1 answer:
asambeis [7]2 years ago
8 0

Answer:

  1. (x+2) (x-2)=x^{2}-4

(n+m) (n-m)=n^{2} -m^{2}

  • (r+9) ( r-9)=r^{2}-81

Step-by-step explanation:

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2 years ago
In October of 2012, Apple introduced a much smaller variant of the Apple iPad, known at the iPad Mini. Weighing less than 11 oun
sveticcg [70]

Answer:

a. f_X(x) = \dfrac{1}{3.5}8.5

b. the probability that the battery life for an iPad Mini will be 10 hours or less is 0.4286 which is about 42.86%

c.  the probability that the battery life for an iPad Mini will be at least 11 hours is 0.2857 which is about 28.57 %

d. the probability that the battery life for an iPad Mini will be between 9.5 and 11.5 hours is 0.5714 which is about 57.14%

e.  86 should have a battery life of at least 9 hours

Step-by-step explanation:

From the given information;

Let  X represent the continuous random variable with uniform distribution U (A, B) . Therefore the probability  density function can now be determined as :

f_X(x) = \dfrac{1}{B-A}A

where A and B  are the two parameters of the uniform distribution

From the question;

Assume that battery life of the iPad Mini is uniformly distributed between 8.5 and 12 hours

So; Let A = 8,5 and B = 12

Therefore; the mathematical expression for the probability density function of battery life is :

f_X(x) = \dfrac{1}{12-8.5}8.5

f_X(x) = \dfrac{1}{3.5}8.5

b. What is the probability that the battery life for an iPad Mini will be 10 hours or less (to 4 decimals)?

The  probability that the battery life for an iPad Mini will be 10 hours or less can be calculated as:

F(x) = P(X ≤x)

F(x) = \dfrac{x-A}{B-A}

F(10) = \dfrac{10-8.5}{12-8.5}

F(10) = 0.4286

the probability that the battery life for an iPad Mini will be 10 hours or less is 0.4286 which is about 42.86%

c. What is the probability that the battery life for an iPad Mini will be at least 11 hours (to 4 decimals)?

The battery life for an iPad Mini will be at least 11 hours is calculated as follows:

P(X\geq11) = \int\limits^{12}_{11} {\dfrac{1}{3.5}} \, dx

P(X\geq11) =  {\dfrac{1}{3.5}} (x)^{12}_{11}

P(X\geq11) =  {\dfrac{1}{3.5}} (12-11)

P(X\geq11) =  {\dfrac{1}{3.5}} (1)

P(X\geq11) = 0.2857

the probability that the battery life for an iPad Mini will be at least 11 hours is 0.2857 which is about 28.57 %

d. What is the probability that the battery life for an iPad Mini will be between 9.5 and 11.5 hours (to 4 decimals)?

P(9.5 \leq X\leq11.5) =\int\limits^{11.5}_{9.5} {\dfrac{1}{3.5}} \, dx

P(9.5 \leq X\leq11.5) ={\dfrac{1}{3.5}} \, (x)^{11.5}_{9.5}

P(9.5 \leq X\leq11.5) ={\dfrac{1}{3.5}} (11.5-9.5)

P(9.5 \leq X\leq11.5) ={\dfrac{1}{3.5}} (2)

P(9.5 \leq X\leq11.5) =0.2857* (2)

P(9.5 \leq X\leq11.5) =0.5714

Hence; the probability that the battery life for an iPad Mini will be between 9.5 and 11.5 hours is 0.5714 which is about 57.14%

e. In a shipment of 100 iPad Minis, how many should have a battery life of at least 9 hours (to nearest whole value)?

The probability that battery life of at least 9 hours is calculated as:

P(X \geq 9) = \int\limits^{12}_{9} {\dfrac{1}{3.5}} \, dx

P(X \geq 9) =  {\dfrac{1}{3.5}}(x)^{12}_{9}

P(X \geq 9) =  {\dfrac{1}{3.5}}(12-9)

P(X \geq 9) =  {\dfrac{1}{3.5}}(3)

P(X \geq 9) =  0.2857*}(3)

P(X \geq 9) =  0.8571

NOW; The Number of iPad  that should have a battery life of at least 9 hours is calculated as:

n = 100(0.8571)

n = 85.71

n ≅ 86

Thus , 86 should have a battery life of at least 9 hours

3 0
3 years ago
Researchers have discovered a new genetic marker for a form of cancer. Twelve percent of the overall population carry this marke
In-s [12.5K]

Answer:

The probability that a person with the marker develops cancer is 0.0725.

Step-by-step explanation:

Let's denote the events as follows:

<em>A</em> = a person has cancer

<em>B</em> = a person carries the marker.

<u>Given:</u>

P (A) = 0.03

P (B) = 0.12

P (B|A) = 0.29

The conditional probability of an event <em>X</em> provided that another event <em>Y</em> has already occurred is:

P(X|Y)=\frac{P(Y|X)P(X)}{P(Y)}

Use the conditional probability formula to compute the probability that a person with the marker develops cancer.

P(A|B)=\frac{P(B|A)P(A)}{P(B)} =\frac{0.29\times0.03}{0.12}=0.0725

Thus, the probability that a person with the marker develops cancer is 0.0725.

3 0
3 years ago
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