Answer:
see explanation
Step-by-step explanation:
In 13 - 17
Consider the factors of the constant term which sum to give the coefficient of the x- term
13
x² - x - 42 = (x - 7)(x + 6)
15
x² + x - 6 = (x + 3)(x - 2)
17
x² - 27x + 50 = (x - 25)(x - 2)
19
r² - 25 ← is a difference of squares and factors in general as
a² - b² = (a - b)(a + b) , thus
r² - 25
= r² - 5² = (r - 5)(r + 5)
Answer:
$45 with 20% markup = $45 + $9 for a new total = $54
$7.60 with a 50% markup = $7.60 + $3.80 for new total = $11.40
Step-by-step explanation:
Answer:
a² + b²
Step-by-step explanation:
(a + b)² - 2ab ← expand parenthesis using FOIL
= a² + 2ab + b² - 2ab ← collect like terms
= a² + b²
A. 7.5 pages per hour B. $2.66 for one page
Given that X <span>be the number of subjects who test positive for the disease out of the 30 healthy subjects used for the test.
The probability of success, i.e. the probability that a healthy subject tests positive is given as 2% = 0.02
Part A:
</span><span>The probability that all 30 subjects will appropriately test as not being infected, that is the probability that none of the healthy subjects will test positive is given by:
</span>

<span>
Part B:
The mean of a binomial distribution is given by
</span>

<span>
The standard deviation is given by:
</span>

<span>
Part C:
This test will not be a trusted test in the field of medicine as it has a standard deviation higher than the mean. The testing method will not be consistent in determining the infection of hepatitis.</span>