Answer:
<h2>21/32</h2>
Step-by-step explanation:
-7/8 × -3/4 = 21/32
-7 × -3 = 21
-8 × -4 = 32
21/32
<u><em>IMPORTANT: This number is not negative, because a negative times a negative is a positive.</em></u>
By the way, if you didn't know how to arrive at the fraction here's how.
First, Address input parameters & values.
Input parameters & values: The decimal number = 0.65625. Then, write it as a fraction
0.65625/1
Multiply by 100000 both the numerator & denominator
(0.65625 x 100000)/(1 x 100000) = 65625/100000
65.625% = 65.625/100 or 65625/100000
Find LCM (Least Common Multiple) for 65625 & 100000.
3125 is the LCM for 65625 & 100000
Divide by 3125
65625/100000 = (65625 / 3125) / (100000 / 3125)
= 21/32
I'm always happy to help :)
because its isosceles so 9+9=x²
and x equal
2√3
Answer:
<u>R8000</u>.
Step-by-step explanation:
First, let's calculate the amount they are going to have to pay the bank after 1 year. It is given by the following expression:
R5 000 * 1.28= R6400
Therefore, they have to pay R6400/12 monthly.
Now, in fifteen months the total amount to pay should be (R6400/12) * 15= <u>R8000</u>.
Answer:
y value
Step-by-step explanation:
when you write an ordered pair the first number is your x and the second number is your y. these make a point on a graph.
(x,y)
Answer:
The probability that the sample proportion will differ from the population proportion by less than 6% is 0.992.
Step-by-step explanation:
According to the Central limit theorem, if from an unknown population large samples of sizes n > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.
The mean of this sampling distribution of sample proportion is:
The standard deviation of this sampling distribution of sample proportion is:
The information provided is:
As the sample size is large, i.e. <em>n</em> = 276 > 30, the Central limit theorem can be used to approximate the sampling distribution of sample proportion.
Compute the value of 
as follows:
Thus, the probability that the sample proportion will differ from the population proportion by less than 6% is 0.992.
