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.
Answer:
-2x + 6
Step-by-step explanation:
Step 1: Define
f(x) = 3x + 2
g(x) = 4 - 5x
Step 2: Find f(x) + g(x)
3x + 2 + 4 - 5x
-2x + 6
Step-by-step explanation:
∫ dt / (cos²(t) ⁹√(1 + tan(t)))
If u = 1 + tan(t), then du = sec²(t) dt.
∫ du / ⁹√u
∫ u^(-1/9) du
9/8 u^(8/9) + C
9/8 (1 + tan(t))^(8/9) + C
Answer:
650
Step-by-step explanation:
