Answer:
The gambler's fallacy, also known as the Monte Carlo fallacy or the fallacy of the maturity of chances, is the erroneous belief that if a particular event occurs more frequently than normal during the past it is less likely to happen in the future (or vice versa), when it has otherwise been established that the probability of such events does not depend on what has happened in the past. Such events, having the quality of historical independence, are referred to as statistically independent. The fallacy is commonly associated with gambling, where it may be believed, for example, that the next dice roll is more than usually likely to be six because there have recently been fewer than the usual number of sixes.
The term "Monte Carlo fallacy" originates from the best known example of the phenomenon, which occurred in the Monte Carlo Casino in 1913.[1]
Length (L): 2w + 6
width (w): w
Perimeter (P) = 2L + 2w
240 = 2(2w + 6) + 2(w)
240 = 4w + 12 + 2w
240 = 6w + 12
228 = 6w
38 = w
Length (L): 2w + 6 = 2(38) + 6 = 76 + 6 = 82
Answer: width = 38 ft, length = 82 ft
Answer:

Step-by-step explanation:
Slope-intercept form of a <u>linear equation</u>:

where:
- m is the slope.
- b is the y-intercept (where the line crosses the y-axis).
<u>Slope formula</u>

<u>Equation 1</u>
<u />
Define two points on the line:
<u>Substitute</u> the defined points into the slope formula:

From inspection of the graph, the line crosses the y-axis at y = 1 and so the y-intercept is 1.
Substitute the found slope and y-intercept into the slope-intercept formula to create an equation for the line:

<u>Equation 2</u>
<u />
Define two points on the line:
<u>Substitute</u> the defined points into the slope formula:

From inspection of the graph, the line crosses the y-axis at y = -4 and so the y-intercept is -4.
Substitute the found slope and y-intercept into the slope-intercept formula to create an equation for the line:

<u>Conclusion</u>
Therefore, the system of linear equations shown by the graph is:

Learn more about systems of linear equations here:
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