Answer:
x = 34
Step-by-step explanation:
4x - 10 + x + 20 = 180
5x + 10 = 180
5x = 170
x = 34
Answer:
For this case a parameter represent the population data and for this case the parameter would be the true mean
who represent the amount of gasoline they used in the previous week

And the sample mean is an unbiased estimator of the true mean.
Step-by-step explanation:
For this case a parameter represent the population data and for this case the parameter would be the true mean
who represent the amount of gasoline they used in the previous week
And in order to estimate the parameter of interest we use a survey of n =3800 and the sample mean who represent an statistic is given by:

And we got:

And the sample mean is an unbiased estimator of the true mean.
Profit for August: x
Profit for September: x - 22%x
Total Profit for August & September: $689,000
x + x - 22% x = 689,000
2x - .22x = 689,000
1.78x = 689,000
x = 689,000/1.78
x = 387,078.65
August Profits: $387,078.65
September Profits: 387,078.65 - (22%)(387,078.65) = 387,078.65 - 85,157.30 = 301,921.35
August Profits: $387,078.65
September Profits
$301,921.35
Answer:
- The solution that optimizes the profit is producing 0 small lifts and 50 large lifts.
- Below are all the steps explained in detail.
Explanation:
<u />
<u>1. Name the variables:</u>
- x: number of smaller lifts
- y: number of larger lifts
<u></u>
<u>2. Build a table to determine the number of hours each lift requires from each department:</u>
<u></u>
Number of hours
small lift large lift total per department
Welding department 1x 3y x + 3y
Packaging department 2x 1y 2x + y
<u></u>
<u>3. Constraints</u>
- 150 hours available in welding: x + 3y ≤ 150
- 120 hours available in packaging: 2x + y ≤ 120
- The variables cannot be negative: x ≥ 0, and y ≥ 0
Then you must:
- draw the lines and regions defined by each constraint
- determine the region of solution that satisfies all the constraints
- determine the vertices of the solution region
- test the profit function for each of the vertices. The vertex that gives the greatest profit is the solution (the number of each tupe that should be produced to maximize profits)
<u></u>
<u>4. Graph</u>
See the graph attached.
Here is how you draw it.
- x + 3y ≤ 150
- draw the line x + 3y = 150 (a solid line because it is included in the solution set)
- shade the region below and to the left of the line
- 2x + y ≤ 120
- draw the line 2x + y ≤ 120 (a solid line because it is included in the solution set)
- shade the region below and to the left of the line
- x ≥ 0 and y ≥ 0: means that only the first quadrant is considered
- the solution region is the intersection of the regions described above.
- take the points that are vertices inside the solutoin region.
<u>5. Test the profit function for each vertex</u>
The profit function is P(x,y) = 25x + 90y
The vertices shown in the graph are:
The profits with the vertices are:
- P(0,0) = 0
- P(0,50) = 25(0) + 90(50) = 4,500
- P(42,36) = 25(42) + 90(36) = 4,290
- P(60,0) = 25(60) + 90(0) = 1,500
Thus, the solution that optimizes the profit is producing 0 smaller lifts and 90 larger lifts.
Probability is calculated by comparing the odds to a certain event occurring to the number of possible events.
P=

For example, take a six-sided dice number 1-6 on each side. The probability of rolling a 4 would be1 in 6 or 1/6. This is because of the six possible outcomes, rolling a 4 is only one of them.
P(4)=1/6
Now take the same dice. The probability of rolling an even number is 3/6. To see why, lets look at the total possible outcomes:
1
23
45
6
Of the 6 possibilities, 3 are even numbers.
P(even)=3/6 or 1/2