Answer: 
Step-by-step explanation:
This car follows a line, hence its motion can be modeled by the Line equation.
In fact, we already have two points of the line, if we call 
the time in hours and 
the traveled distance in miles:
Point 1: 
Since we are told the car's initial position is 300 miles in the time 0 h
Point 2: 
Since we are told the car's final position is 180 miles after 3h
<u />
<u>Let's find the Slope 
:
</u>
This is the slope of the line
Now, the equation of the line is:
We already know the slope, now we have to find the intersection point with the y-axis (
) with any of the given points. Let's choose Point 1:
Isolating :
Then, the equation of the line is:
Answer: D. 0.981
Step-by-step explanation:
Step 1: For the given data table on x^2
We square all values given to us
Step 2: we repeat Same for Y^2 table too.
Step 3: XY table we multiply x and y
Step 4: we make a summation of them all
Step 5: we input our summer value into our formula.
Step 6 : we arrive at our answer which is 0.981
Answer:
3,406.5 litres/hr
Step-by-step explanation:
The liquid is being poured at a rate of 15 gallons per minute.
1 minute = 1/60 hour
Thus, the rate can be written as:
15 gallons pet 1/60 hour
We are told that one gallon is approximately 3.785 liters.
Thus;
15 gallons = 15 × 3.785 litres = 56.775 litres.
Thus, the rate is;
56.775 litres per 1/60 hour
We want to find in litres/hr.
By proportion, we have it as;
(56.775 ÷ 1/60)/1 = 56.775 × 60 = 3,406.5 litres/hr
Answer:
16
Step-by-step explanation:
This problem requires PEMDAS
Parentheses ( )
Exponents ^
Multiplication
Division
Add
Subtract
Start by solving anything in parentheses. There's an exponent within the parentheses, so we change that 2^2 into 4 and also make sure to multiply 5 x 2 before subtracting.
-4 - (2 + -24 - 4 - (4-10))
-4 - (2 + -24 - 4 - (-6))
Again, solve parentheses first.
-4 - (-22 - 4 - (-6))
-4 - (-26 + 6)
-4 - (-20)
-4 + 20
Answer is 16
Answer: C. there is still not enough evidence to conclude that the time series is stationary.
Step-by-step explanation: First thing to note for a time series plot is that it is required to select a suitable forecast method for the data set being considered.
A stationary time series means that the process generating the data set has a constant mean and the variations are constant over time. This means all evidence is present leading to the conclusion that the entire time series is stationary. A stationary time series thus exhibits an horizontal pattern which enables an appropriate forecast method to be selected for this type of pattern.
A horizontal pattern of a time series plot indicates that a data set fluctuates around a constant mean for a period of time. This period of time may however not be the entire time of the time series or take the entire data set into consideration and might just be a reflection of a portion of the time series hence why it can not be explicitly considered to be stationary. This means that a horizontal pattern can change into a seasonal or trending pattern if more variables/data are added over time.
For instance, a manufacturer sells a certain amount of products over a 10 week period and the resulting pattern of a time series plot is horizontal, then from the 11th week to the 15th week he gets a sharp and continuous increase in sales. This change in level will therefore change the time series plot from horizontal to trending making it more difficult to select a suitable forecast method.
