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shusha [124]
3 years ago
10

A small office supply store sells paper clips in packs of 100 and packs of 250. If the store has 84 packs of paper clips in stoc

k totaling 12,300 paper clips, how many paper clips would a customer buy if he buys half of the packs of 250 that the store has in stock?
SAT
1 answer:
sveta [45]3 years ago
3 0
Let x and y be the number of packs with 100 and 250 paper clips, respectively. The system of linear equations that would best represent the given is
                                     x + y = 84
                                    100x + 250y = 12,300

The values of x and y from the equations are 58 and 26, respectively. If a person buys half of the packs of 250 paper clips,
                              n = (0.5)(250)(26) = 3250

Thus, a person bought 3250 paper clips. 
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suppose labor productivity in the united states was $100,000 per worker in 2015. calculate the value of labor productivity in 20
sukhopar [10]

a. U.S labor productivity in 2035 would be $206,800 per worker.

b.  U.S labor productivity in 2035 would be $68,100 per worker.

c. Labor productivity per worker in 2035 with the higher growth rate is 3.04

a. Calculation to determine  what the U.S labor productivity in 2035 would be $ per worker assuming productivity grows by 3.7 percent per year

Given:

Labor Productivity in 2015 = $100,000

Growth rate = 3.7%pa or  0.037

Using this formula

Future value = Present value*(1+Growth rate)^Number of years

Let plug in the formula

2035 labor productivity per worker=100,000(1 + 0.037)^20

2035 labor productivity per worker= $206,811.71

2035 labor productivity per worker= $206,800

( rounded to nearest $100)

b.Calculation to determine  what the U.S labor productivity in 2035 would be $ per worker assuming productivity falls to 1.9 percent per year

Given:

Labor Productivity in 2015 = $100,000

Growth rate = -1.9%pa or -0.019

Using this formula

Future value = Present value*(1+Growth rate)^Number of years

Let plug in the formula

2035 labor productivity per worker= 100,000(1-0.019)^20

2035 labor productivity per worker= $68,136.55

2035 labor productivity per worker= $ 68,100

( rounded to nearest $100)

c. Calculation to determine How much larger would labor productivity per worker be in 2035 with the higher growth rate

2035 labor productivity per worker=($206,811.711/$68,136.55121)

2035 labor productivity per worker= 3.04 times

Inconclusion:

a. U.S labor productivity in 2035 would be $206,800 per worker.

b.  U.S labor productivity in 2035 would be $68,100 per worker.

c. Labor productivity per worker in 2035 with the higher growth rate is 3.04

Learn more here:

brainly.com/question/14174963

6 0
2 years ago
A 8-acre piece of land is subdivided into 4/7-acre lots. How many lots are there?
Katen [24]
14.

8 / (4/7) = 14 lots
3 0
3 years ago
Find the residual values, and use the graphing calculator tool to make a residual plot.
finlep [7]

Answer:

  • No, the points are evenly distributed about the x-axis.

Explanation:

<u>1. Write the table with the data:</u>

  x      given     predicted       residual

  1       - 3.5         - 1.1

  2      - 2.9           2

  3       - 1.1            5.1

  4        2.2           8.2

  5        3.4           1.3

<u>2. Complete the column of residuals</u>

The residual is the observed (given) value - the predicted value.

  • residual = given - predicted.

Thus, the complete table, with the residual values are:

  x      given     predicted       residual

  1       - 3.5         - 1.1                 - 2.4

  2      - 2.9           2                  - 4.9

  3       - 1.1            5.1                - 6.2

  4        2.2           8.2               - 6.0

  5        3.4           1.3                   2.1

<u>3. Residual plot</u>

You must plot the last column:

  x      residual

  1       - 2.4

  2      - 4.9

  3       - 6.2

  4       - 6.0

  5        2.1

See the plot attached.

<em>Does the residual plot show that the line of best fit is appropriate for the data?</em>

Ideally, a residual plot for a line of best fit that is appropiate for the data must not show any pattern; the points should be randomly distributed about the x-axis.

But the points of the plot are not randomly distributed about the x-axis:  there are 4 points below the x-axis and 1 point over the x-axis: there are more negative residuals than positive residuals.  This is a pattern. Also, you could say that they show a curve pattern, which drives to the same conclusion: the residual plot shows that the line of best fit is not appropiate for the data.

Thus, the conclusion should be: No, the points have a pattern.

  • 1. "<em>Yes, the points have no pattern</em>": false, because as shown, the points do have a pattern, which makes the residual plots does not show that the line of best fit is appropiate for the data.

  • 2. "<em>No, the points are evenly distributed about the x-axis</em>": true. As already said the points have a pattern. It is a curved pattern, and this <em>shows the line of best fit is not appropiate for the data.</em>

  • 3. "<em>No, the points are in a linear pattern</em>": false. The points are not in a linear pattern.

  • 4. "<em>Yes, the points are in a curved pattern</em>": false. Because the points are in a curved pattern, the residual plot shows that the line of best fit is not appropiate for the data.

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