The recursive formula for the given sequence as required in the task content is; f(n) = f (n - 1) - 50.
It follows from the task content that the recursive formula for the given sequence is to be determined.
By observation, the sequence is an arithmetic progression and the common difference, d can be evaluated as;
d = 750 - 800 = 800 - 850 = 850 - 900 = -50
Also, since the recursive formula for an arithmetic sequence takes the form;
f(n) = f (n - 1) + d.
Hence, since the recursive formula as required is;
f(n) = f (n - 1) - 50.
Read more on recursive formula;
#SPJ1
Answer:
f(1)=900
f(n)=f(n-1)-50if n>1
Step-by-step explanation:
this is the correct
How do I prove this with the double angle law
Answer:
20.875
Step-by-step explanation:
47.678-(15.463+11.34) =20.875
A. (2x2 + 1)(3x2 + 1)
+
B. (5x + 1)(x+1)
C. (2x + 1)(3x + 1)
O D. (3x + 1)(2x+2)
Answer:
C
Step-by-step explanation:
The top is 2x + 1 and the left is 3x + 1
Answer:
C
The top is 2x + 1 and the left is 3x + 1
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.
#SPJ12
Answer:
I = 1.47001
Step-by-step explanation:
we have the function
In polar coordinates we have
and dA is given by
Hence, the integral that we have to solve is
This integral can be solved in a convenient program of your choice (it is very difficult to solve in an analytical way, I use Wolfram Alpha on line)
I = 1.47001
Hope this helps!!!
Answer:
-1/4 , -1
Step-by-step explanation:
I solved it using Factorization method and Quadratic Equation .
Factorization Method
Quadratic Equation