Answer: x > 2
Step-by-step explanation: PLEASE GIVE BRAINLIEST HELPS A LOT
Answer:
19.9 miles
Step-by-step explanation:
In this problem we have:
is the distance travelled during the 1st day
is the distance travelled during the 2nd day
is the distance travelled during the 3rd day
is the distance travelled during the 4th day
We notice that the difference between the distance travelled on the (n+1)-th day and the distance travelled on the n-th day doubles every day. In fact:

Which can be rewritten using the general formula:

This means that

By applying this formula recursively, we can find the 7th term, which is the distance travelled on the 7th day:

So, the distance travelled on the 7th day is 19.9 miles.
Answer:
3(4)+g=28
Step-by-step explanation:
3 is the cost of one pair of shoes and 4 is how many shoes were rented. you multiple the 3 times 4 and get 12 and to get the amount of one game you have to subtract the total amount. the equation I came up with might not be what your teacher wants but thats a start. hope it helped!
This is going to be 4 remainders one.
Answer:
a) y = 0.74x + 18.99; b) 80; c) r = 0.92, r² = 0.85; r² tells us that 85% of the variance in the dependent variable, the final average, is predictable from the independent variable, the first test score.
Step-by-step explanation:
For part a,
We first plot the data using a graphing calculator. We then run a linear regression on the data.
In the form y = ax + b, we get an a value that rounds to 0.74 and a b value that rounds to 18.99. This gives us the equation
y = 0.74x + 18.99.
For part b,
To find the final average of a student who made an 83 on the first test, we substitute 83 in place of x in our regression equation:
y = 0.74(83) + 18.99
y = 61.42 + 18.99 = 80.41
Rounded to the nearest percent, this is 80.
For part c,
The value of r is 0.92. This tells us that the line is a 92% fit for the data.
The value of r² is 0.85. This is the coefficient of determination; it tells us how much of the dependent variable can be predicted from the independent variable.