Answer: an average resulting from the multiplication of each component by a factor reflecting its importance.
Step-by-step explanation:
Ralphs is 7.5x+10
frank’s is 10x
<span>1) if 2 times the wind speed is increased by 2, the wind speed is still less
than 46 km/h.
=> 2x + 2 < 46
2) Twice the wind speed minus 27 is greater than 11 km/h.
=> 2x - 27 > 11
Part A: Create a compound inequality to represent the wind speed range.
(3 points)
from 2x + 2 < 46
=> 2x < 44
=> x < 22
from 2x - 27 > 11
=> 2x > 11 + 27
=> 2x > 38
=> x > 19
The set of inequalities is
2x + 2 <46
2x - 27 > 11
The solution is x < 22 and x > 19, which is:
19 < x < 22 <----- answer
Part B: Can the wind speed in this town be 20 km/h? Justify
your answer by solving the inequalities in Part A. (3 points)
Yes, the wind speed can be 20 km/h, because the solution of the inequality is the range (19,22).
Part C:
The average wind speed in another town is 23 km/h, but the actual wind
speed is within 4 km/h of the average. Write and solve an inequality to
find the range of wind speed in this town.
x ≥ 23 - 4 => x ≥ 19
x ≤ 23 + 4=> x ≤ 27
=> 19 ≤ x ≤ 27
=> [19,27]
</span>
If data for a time series analysis are collected on an annual basis only, then the option(b) seasonal pattern can be ignored
Time series analysis is a specific way of analyzing a sequence of data points collected over an interval of time
The seasonal pattern is refers to the seasonal characteristics of the time series data. It is the predictable pattern that repeats at a certain frequency within one year, such as weekly, monthly, quarterly, etc.
A horizontal pattern exists when the data fluctuate randomly around a constant mean over time.
A trend pattern exists when there is a long-term increase or decrease in the series.
The cyclical component of a time series refers to fluctuations around the trend, excluding the irregular component, revealing a succession of phases of expansion and contraction
Here, the data for a time series analysis are collected on an annual basis, so the seasonal pattern can be ignored
Learn more about Time series analysis here
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