If he bikes for 10 miles per hour and 8 miles per hour for the same distance x miles, he went 10 miles per hour for x/10 hours, as Distance = Rate*Time and on the way back he would go for x/8 hours. So then he went 2x distance, in x/8 + x/10 hours. Since x/8 + x/10 = 10x/80 + 8x/80 = 18x/80 = 9x/40, he went 2x miles in 9x/40 hours. this can be converted into a rate with the above equation Distance = Rate*Time, so 2x=(9x/40) * Rate, thus we divide by 9x/40 on both sides to get 80x/9x = Rate, the x cancels out, and we get 80/9 Miles per hour.
Answer:
v(m) = 8 + 48m+ 180m² +216m³
Step-by-step explanation:
Let's first of all represent the edge of the the cube as a function of minutes.
Initially the egde= 2feet
As times elapsed , it increases at the rate of 6 feet per min, that is, for every minute ,there is a 6 feet increase.
Let the the egde be x
X = 2 + 6(m)
Where m represent the minutes elapsed.
So we Al know that the volume of an edge = edge³
but egde = x
V(m) = x³
but x= 2+6(m)
V(m) = (2+6m)³
v(m) = 8 + 48m+ 180m² +216m³
we will find number of non-zero elements on each rows
and then we add them
First row:
we can see that non-zero elements are
2 , 3.1 , 22 , 9
so, number of non-zero elements in first row =4
Second row:
we can see that non-zero elements are
21 , 3.2 , 6
so, number of non-zero elements in first row =3
Third row:
we can see that non-zero elements are
1 , 42 , 8
so, number of non-zero elements in first row =3
Fourth row:
we can see that non-zero elements are
40 ,4 , 6,14
so, number of non-zero elements in first row =4
Fifth row:
we can see that non-zero elements are
10 , 20 , 13 , 5 , 6.3
so, number of non-zero elements in first row =5
now, we can add them
so,
total number of non-zero elements = 4 +3+3+4+5
so,
total number of non-zero elements is 19...........Answer
Answer:
3.84% probability that it has a low birth weight
Step-by-step explanation:
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean 
and standard deviation 
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
In this problem, we have that:
If we randomly select a baby, what is the probability that it has a low birth weight?
This is the pvalue of Z when X = 2500. So
has a pvalue of 0.0384
3.84% probability that it has a low birth weight
