Answer:
When dealing with VOLUME, an increase in a linear quantity, produces a third power result in the volume.
Increase the sides of a cube by 2 produces an 8 times effect in the volume.
Increasing each side of a cube by 4 produces a chnage of 4 * 4 * 4 or
64 times in the volume.
Step-by-step explanation:
b is the awnser
Step-by-step explanation:
Answer:
B
Step-by-step explanation:
There are 96 squares in total. Yard is 3 feet, so you would divide the total by 3.
Answer:
33 in
Step-by-step explanation:
The Pythagorean theorem tells you ...
diagonal² = length² +width²
diagonal² = (16 in)² +(28.5 in)² = 1068.25 in²
diagonal = √(1068.25 in²) ≈ 32.684 in
The diagonal of the television is about 33 inches.
kyle regalara 16 figuras y le quedara 3/4 de ellas
Step-by-step explanation:
cmon man its a blank screen
y-intercept, b0 = 4.7.17
Slope, b1 = 1.46
MSE = ???????? NEED THIS
What is the forecast for year 10? 19.283
Round your interim computations and final answer to two decimal places.
Answer:
a) find the attached graph
b) find the attachment no 4 and 5
c)
Step-by-step explanation:
a) A trend pattern exist if the time series plot gradually shifts to higher or lower values over a long period of time
find the attached graph
b) Liner Trend Equation
Where is the linear trend forecast in period t , is the intercept of the linear trend time, is the slope of the linear trend line, t is the time period
now computing the slope and intercept
formula is attached ( 3 no attachment)
is the value of the time series in period t, n is the number of time periods
Y(bar) is the average value and t(bar) is the average value of t
due to unavailability of equation in math-script i attached the calculation part of this question( 4th and 5th no attachment)
thus the linear trend equation is (1)
To find the Mean Squared Error (MSE), you can calculate the difference between the actual and predicted values, square these differences, and find their average. To forecast for a specific year, you can insert the year as the 'x' value into the simple linear regression equation.
The question is asking for the Mean Squared Error (MSE) for a simple linear regression model based on the enrollment data of Jefferson Community College. This involves using the y-intercept (b0) and slope (b1) values provided, and the given data points. You can calculate the MSE by taking the difference between the actual and predicted values (errors), squaring these differences, and then finding the average of these squared differences for the entire dataset.
Then, to forecast for year 10, you use the simple linear regression model equation, y = b0 + b1*x, where y represents the predicted enrollment. So, for year 10, you would insert 10 as your 'x' value into the equation, which results in the forecast value provided which is 19.283.
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