y = mx + b
"m" is the slope, "b" is the y-intercept (the y value when x = 0)
To find the slope, you can use the slope formula and plug in the two points:
(3,63) = (x₁ , y₁)
(5,107) = (x₂, y₂)
m = 22
Now that you know m = 22, plug it into the equation:
y = mx + b
y = 22x + b
To find "b", plug in one of the points into the equation (I will do both points)
(3,63)
y = 22x + b
63 = 22(3) + b
63 = 66 + b Subtract 66 on both sides
-3 = b
(5,107)
y = 22x + b
107 = 22(5) + b
107 = 110 + b Subtract 110 on both sides
-3 = b
y = 22x - 3
answer: 1 over 165 step by step: #1 Evaluate the power 5 to the power of 1= 5 because any expression raised to the power of 1 if u asking what's is an expression the expression is five and together is 5 to the power of 1) #2 if a term like five doesn't have a exponent the exponent is 1) #3 remove the parathesis ) #4 subtract 1 and -2 u get 1 over 5 to the power of -4 and 5 to the power of negative four is 1 over 165) the second I don't know
Answer:
(a) The probability that the store’s revenues were at least $9,000 is 0.0233.
(b) The revenue of the store on the worst 1% of such days is $7,631.57.
Step-by-step explanation:
According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and we take appropriately huge random samples (n ≥ 30) from the population with replacement, then the distribution of the sum of values of X, i.e ∑X, will be approximately normally distributed.
Then, the mean of the distribution of the sum of values of X is given by,
And the standard deviation of the distribution of the sum of values of X is given by,
It is provided that:
As the sample size is quite large, i.e. <em>n</em> = 310 > 30, the central limit theorem can be applied to approximate the sampling distribution of the store’s revenues for Sundays by a normal distribution.
(a)
Compute the probability that the store’s revenues were at least $9,000 as follows:
Thus, the probability that the store’s revenues were at least $9,000 is 0.0233.
(b)
Let <em>s</em> denote the revenue of the store on the worst 1% of such days.
Then, P (S < s) = 0.01.
The corresponding <em>z-</em>value is, -2.33.
Compute the value of <em>s</em> as follows:
Thus, the revenue of the store on the worst 1% of such days is $7,631.57.