Answer:
Option A
f(x) = 12.5(1.6)^x
Step-by-step explanation:
The number of gnats the scientists have gathered
At 0 hours, they gathered 12 gnats.
Checking all the options, applying x = 0 makes the index part become 1 (Anything raised to the power zero is 1).
So, we have the following functions
f(x) = 12.5
f(x) = 12.6
f(x) = 6.2
f(x) = 1.6
This has reduced our work, as we can screen out options C and D, they are too far from 12. This leaves us with option A and B.
At 1 hour, they gathered 20 gnats.
Checking options A and B
A. f(x) = 12.5(1.6)
= 20
B. f(x) = 12.6(6.2)
By inspection, 12 × 6 is already 72,
12.6 × 6.2 will be more.
By these, we can conclude that f(x) = 12.5(1.6)^x has the best models the number of gnats the scientists have gathered after the number of hours listed in the given table.
Answer:
183.92 inch²
Step-by-step explanation:
To find the total amount of wrapping paper needed, you must find the Surface Area of the box.
Surface area of a rectangular prism is: A = 2(<em>wl</em> + <em>hl</em> + <em>hw</em>)
w = width = 3.8
h = height = 9.5
l = length = 4.2
Plug in the corresponding numbers to the corresponding variables.
A = 2(<em>wl</em> + <em>hl </em>+ <em>hw</em>)
A = 2((3.8 * 4.2) + (9.5 * 4.2) + (9.5 * 3.8))
Simplify.
A = 2((15.96) + (39.9) + (36.1))
A = 2(15.96 + 39.9 + 36.1)
A = 2(91.96)
Multiply.
A = 183.92
183.92 inch² is your answer.
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Answer:
Step 1: Put the numbers in order. ...
Step 2: Find the median. ...
Step 3: Place parentheses around the numbers above and below the median. Not necessary statistically, but it makes Q1 and Q3 easier to spot. ...
Step 4: Find Q1 and Q3. ...
Step 5: Subtract Q1 from Q3 to find the interquartile range.
Step-by-step explanation:
u should do those step and i think u will find the answer
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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