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laiz [17]
3 years ago
10

Ms. Ford's kitchen is in the shape of a rectangle with a width of 12.25 feet. She is buying a wallpaper border to go on all of h

er kitchen walls. She wants to buy 5 extra feet of the border to be sure she has enough. She buys 62.5 feet of the border.
What is the length of Ms. Ford's kitchen? Explain how you can find your answer.
Mathematics
1 answer:
qaws [65]3 years ago
4 0

Answer:

57.5 feet

Step-by-step explanation:

The kitchen is a rectangle and she wants to buy 5 feet of wallpaper. And she buys 62.5 feet of wallpaper border. Just subtract 62.5 and 5 and you get 57.5 feet.


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What type of line is y = x?
Troyanec [42]

Answer:

A slanted line slanting right on the graph

Step-by-step explanation:

It’s c

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3 years ago
The home run percentage is the number of home runs per 100 times at bat. A random sample of 43 professional baseball players gav
Andru [333]

Step-by-step explanation:

(a) Yes, if you enter all 43 values into your calculator, you calculator should report:

xbar = 2.293

s = 1.401

(b)

Note: Most professors say that is sigma = the population standard deviation is unknown (as it is unknown here), you should construct a t-confidence interval.

xbar +/- t * s / sqrt(n)

2.293 - 1.684 * 1.401 / sqrt(43) = 1.933

2.293 - 1.684 * 1.401 / sqrt(43) = 2.653

Answer: (1.933, 2.653)

Note: To find the t-value that allows us to be 90% confident, go across from df = 43-1 = 42 (round down to 40 to be conservative since 42 in not in the table) and down from (1-.90)/2 = .05 or up from 90% depending on your t-table. So, the t-critical value is 1.684.

Note: If you can use the TI-83/84, it will construct the following CI using df = 42 (ie t = 1.681).

2.293 +/- 1.681 * 1.401 / sqrt(43)

(1.934, 2.652)

Note: Some professors want you to construct a z-CI when the sample size is large. If your professor says this, the correct 90% CI is:

2.293 +/- 1.645 * 1.401 / sqrt(43)

(1.942, 2.644)

Note: To find the z-value that allows us to be 90% confident, (1) using the z-table, look up (1-.90)/2 = .05 inside the z-table, or (2) using the t-table, go across from infinity df (= z-values) and down from .05 or up from 90% depending on your t-table. Either way, the z-critical value is 1.645.

(c)

Note: Again, most professors say that is sigma = the population standard deviation is unknown (as it is unknown here), you should construct a t-confidence interval.

xbar +/- t * s / sqrt(n)

2.293 - 2.704 * 1.401 / sqrt(43) = 1.715

2.293 - 2.704 * 1.401 / sqrt(43) = 2.871

Answer: (1.715, 2.871)

Note: To find the t-value that allows us to be 99% confident, go across from df = 43-1 = 42 (round down to 40 to be conservative since 42 in not in the table) and down from (1-.99)/2 = .005 or up from 99% depending on your t-table. So, the t-critical value is 2.704.

Note: If you can use the TI-83/84, it will construct the following CI using df = 42 (ie t = 2.698).

2.293 +/- 2.698 * 1.401 / sqrt(43)

(1.717, 2.869)

Note: Again, some professors want you to construct a z-CI when the sample size is large. If your professor says this, the correct 99% CI is:

2.293 +/- 2.576 * 1.401 / sqrt(43)

(1.742, 2.843)

Note: To find the z-value that allows us to be 99% confident, (1) using the z-table, look up (1-.99)/2 = .005 inside the z-table, or (2) using the t-table, go across from infinity df (= z-values) and down from .005 or up from 99% depending on your t-table. Either way, the z-critical value is 2.576.

(d)

Tim Huelett 2.5

Since 2.5 falls between (1.715, 2.871), we see that Tim Huelett falls in the 99% CI range. So, his home run percentage is NOT significantly different than the population average.

Herb Hunter 2.0

Since 2.0 falls between (1.715, 2.871), we see that Herb Hunter falls in the 99% CI range. So, his home run percentage is NOT significantly different than the population average.

Jackie Jensen 3.8.

Since 3.8 falls above (1.715, 2.871), we see that Jackie Jensen falls in the 99% CI range. So, his home run percentage IS significantly GREATER than the population average.

(e)

Because of the Central Limit Theorem (CLT), since our sample size is large, we do NOT have to make the normality assumption since the CLT tells us that the sampling distribution of xbar will be approximatley normal even if the underlying population distribution is not.

6 0
3 years ago
The data and summary given in the represents a random sample of twelfth-grade girls and bots in a school district. Is there an o
zhenek [66]

Answer:

it is A) No, there is not an overlap between the two data setsStep-by-step explanation:

i did it on usatestprep

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Ilia_Sergeevich [38]

Answer:

a. 90 pack

b. $0.27

c. $0.18

d. $0.21

e. 60 pack

Step-by-step explanation:

a. i think  the 90 pack container should be having least unit rate per pack,as purchasing in bulk amount the cost of a unit should be reduced to some amount which is must to lure the customer to purchase in bulk amounts.

b. unit price = total cost of container ÷ number of individual units inside it

for 20 pack, unit rate = 5.49÷20 = $0.27

c. for 60 pack, unit rate = 10.97÷60 =$0.18

d. for 90 pack, unit rate = 18.95÷90 =$0.21

e. ∴ the 60 pack container has the least unit rate per pack which is in contrary with our expectation of 90 pack to be lowest expecting bulk order.

5 0
3 years ago
Not sure how to do these. i need help with 13! needing it to be reduced just like y should be 8
Delicious77 [7]

Answer:

I'm not sure 710

Step-by-step explanation:

I'm not sure

8 0
3 years ago
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