Events
• A: an even number is rolled in the first time
,
• B: a number greater than 3 is rolled the second time
The probability of rolling an even number is:
The probability of rolling a number greater than 3 is:
Events A and B are independent, then the probability of one happening after the other is:
Answer:
(5, - 4 )
Step-by-step explanation:
Given the 2 equations
2x + 3y = - 2 → (1)
3x - y = 19 → (2)
Multiplying (2) by 3 and adding to (1) will eliminate the y- term
9x - 3y = 57 → (3)
Add (1) and (3) term by term to eliminate y
(2x + 9x) + (3y - 3y) = (- 2 + 57), that is
11x = 55 ( divide both sides by 5 )
x = 5
Substitute x = 5 into either of the 2 equations and solve for y
Substituting into (1)
2(5) + 3y = - 2
10 + 3y = - 2 ( subtract 10 from both sides )
3y = - 12 ( divide both sides by 3 )
y = - 4
Solution is (5, - 4 )
We need to perform multiplication and addition property for this problem to represent the final result in decimal form. So, the expression is,
9x100+2x10+3x0.1+7x0.001 .
Now 9 x 100= 900
2 x= 10= 20
3x0.1= 0.3
7x 0.001=0.007
Now we can all the numbers. Hence,
900+20+0.3+0.007=920.307
So, the decimal number is 930.307.
The answer is 6. You can find slope by using the slope formula: M= y1 - y2 / x1 - x2. In this case you can choose any two points from the table. I chose the second two points. the equation would then be (7-1) / (2-1). It would then be 6/1 or 6.
Hope this helped(:
Question:
A solar power company is trying to correlate the total possible hours of daylight (simply the time from sunrise to sunset) on a given day to the production from solar panels on a residential unit. They created a scatter plot for one such unit over the span of five months. The scatter plot is shown below. The equation line of best fit for this bivariate data set was: y = 2.26x + 20.01
How many kilowatt hours would the model predict on a day that has 14 hours of possible daylight?
Answer:
51.65 kilowatt hours
Step-by-step explanation:
We are given the equation line of best fit for this data as:
y = 2.26x + 20.01
On a day that has 14 hours of possible daylight, the model prediction will be calculated as follow:
Let x = 14 in the equation.
Therefore,
y = 2.26x + 20.01
y = 2.26(14) + 20.01
y = 31.64 + 20.01
y = 51.65
On a day that has 14 hours of daylight, the model would predict 51.65 kilowatt hours
