So it wants you to write two equations, one for the number of fruit and another for the money spent. gather your important information first:
20 fruits for $11.50
apples cost $0.50
bananas cost $0.75
let's do the cost equation first. it's $0.50 per apple, so 0.50a, and $0.75 per banana, so 0.75b. the total cost is $11.50. put all of this information together:
0.50a + 0.75b = 11.50 ... so, the cost of apples bought plus the cost of bananas bought equals 11.50
note what your variables stand for. a represents the number of apples, b represents the number of bananas. to write an equation for how many fruits bought, you simply have to add these two and set them equal to 20 (the total number of fruits bought).
a + b = 20
and your other equation
0.50a + 0.75b = 11.50
these are your two equations. to solve the system of equations, you first want to get one variable alone; the first equation will be easier.
a + b = 20
a = 20 - b
now take this equation and plug it into the second equation.
0.50(20 - b) + 0.75b = 11.50 ... you'll notice that you only have one variable left: b. solve for it. the first step is to distribute 0.50 to the parentheses
10 - 0.50b + 0.75b = 11.50 ... combine like terms
10 + 0.25b = 11.50 ... subtract 10
0.25b = 1.5 ... divide by 0.25
b = 6
6 bananas were purchased. plug this back into an equation to find out how many apples were purchased.
a + 6 = 20 ... subtract 6
a = 14
14 apples and 6 bananas were bought.
Mean diameter = 25 mm
Standard deviation = 0.2 mm
25.6 mm - 25 mm = 0.6 mm
0.6 mm : 0.2 mm = 3
Answer:
A ball bearing with a diameter 25.6 mm differs from the mean
D ) 3 standard deviations.
Answer:
i think its a yes
Step-by-step explanation:
Answer:
72.00
Step-by-step explanation:
umm cant really explain
Answer with explanation:
Coefficient of determination(r²), is defined as, how well the data values are associated with each other when Regression line is drawn. In regression analysis, the coefficient of determination measures , how well the regression predictions approximate the real data points, means it measures the closeness between two variables.The Value of r², lies between 0 to 1. If value of r²=1, it shows ,regression line that is data values are Perfectly associated with each other.
If ,r²=0, it means there is no variation between two variables.There is 0% variation between two variables.
→Coefficient of Variation=[Correlation coefficient]²
=r²
=(0.854)²
=0.854 × 0.854
=0.729316
=0.730(Approx)
