Answer:
1 hour
Step-by-step explanation:
25min=1 poster for the shop owner
25×4=100
100×8=800
800÷25=32 posters in 8hrs for the shop owner
1hr×8=8 posters for the apprentice
thus 40 in total
7We can see that line NM = JK so NM also equals 10.
We know NL = 23 and NM = 10 therefore, ML = NL -NM ML = 23 -13
ML = 10
The last thing to solve is the length of KL
KL = ML / sine 34
KL = 10 / 0.55919
KL = 17.9
Total fence length required = JK + KL + NL =
13 + 17.9 + 23
= 53.9 yards
Cost of Fencing = $3.50 * 53.9 =
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$188.65
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Answer:
1. 8/$12=21/$x then cross multiply.
2. 1/$1.5, we're looking for cost so $1 is more reasonable
3. $31.5
Step-by-step explanation:
12x 21/ 8 = 31.5
<h3>
Answer: 95 degrees</h3>
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Explanation:
I recommend drawing it out to see what's going on. See the drawing below.
In the diagram, both angles are in the northeast corner of their four-corner configurations. They are both congruent corresponding angles. So that's why the second angle is also 95 degrees.
Side note: we could replace "northeast" with any of the other directions on the compass (such as southwest). All that matters is that they are in the same configuration.
Suppose you performed a regression analysis. The mse for this scenario is 0.105
Regression is a statistical method used in finance, making an investment, and different disciplines that attempt to determine the electricity and man or woman of the relationship between one established variable (commonly denoted through Y) and a sequence of different variables (called independent variables).
We are able to say that age and peak can be described through the usage of a linear regression version. because someone's peak will increase as age will increase, they have got a linear courting. Regression fashions are commonly used as statistical proof of claims regarding regular statistics.
"Regression" comes from "regress" which in turn comes from Latin "regresses" - to head returned (to something). In that feel, regression is the approach that permits "to head again" from messy, hard-to-interpret data, to a clearer and more significant version.
y ypred (y-ypred)^2
1 1.1 0.01
1.5 1.3 0.04
2.8 3.2 0.16
3.7 3.7 0
The error sum of the square is given by
ESS = (y- )
ESS=0.21
The mean square error is given by
ESS MSE = ESS/dfe
MSE = \frac{0.21}{2}
MSE = 0.105
Learn more about regression here brainly.com/question/26755306
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