The first piece is 5 inches long, the second piece is 10 inches long, and the third piece is 31 inches long.
The problem involves a piece of steel that is 46 inches long and it is cut into three pieces. The wording of the problem gives us equations we can use to solve for lengths of the pieces. We're told:
We can let x represent the length of the first piece. Then the length of the second piece is 2x, and the length of the third piece is 6x+1.
Because the three pieces together form the original 46-inch piece, we can set up this equation: x + 2x + 6x + 1 = 46, which simplify to 9x +1 = 46. Solving for x gives x = 5. Therefore, the lengths of the pieces are 5 inches, 10 inches (2 * 5), and 31 inches (6 * 5 + 1).
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Answer:
63 ft
Step-by-step explanation:
Multiply your scale factor by 7.
1 in : 9 ft . . . . . . . . . . your scale factor
7·(1 in) : 7·(9 ft) . . . . . indicate the multiplication
7 in : 63 ft . . . . . . . . do the multiplication
Answer:
u mStep-by-step explanation:
g
Answer:
13 miles
Step-by-step explanation:
Add all of the number of miles you ran from each day to get your total mileage.
2+2+3+2+4
Answer:
17y^2+19
Step-by-step explanation:
sum means add
Answer:
19+ 17y²
Step-by-step explanation:
Answer:
p = 0.48
Step-by-step explanation:
A binomial experiment is and experiment with n trials, every trial is identical and independent and every trial has the same probability p of success and 1-p of fail.
Then, we have a binomial experiment of 16 trials. it means that every trial has the same conditions. So, if the probability of success on trial 9 is 0.48, the probability of success on trial 13 is also 0.48.
Step-by-step explanation:
What are the options to choose from?
Answer:
Sample size should be atleast 625
Step-by-step explanation:
Given that the Labor Bureau wants to estimate, at a 90% confidence level, the proportion of all households that receive welfare
Sample proportion = 17.5%
Let n be the sample size
Standard error of sample proportion=
Z critical for 90% = 1.645
Margin of error = 1.645 * std error
Since margin of error<0.025 we have
The sample size that would limit the margin of error to be within 0.025 of the population proportion is approximately 185.
To estimate the sample size needed to limit the margin of error within 0.025, we can use the formula for sample size in proportion estimation. The formula is:
n = (Z^2 * p * (1-p)) / (E^2)
Where:
n = sample size
Z = Z-score corresponding to the desired confidence level
p = preliminary sample proportion
E = margin of error
Given that the confidence level is 90%, the Z-score for a 90% confidence level is approximately 1.645. The preliminary sample proportion is 17.5% (or 0.175) and the margin of error is 0.025.
Substituting these values into the formula:
n = (1.645^2 * 0.175 * (1 - 0.175)) / (0.025^2)
Simplifying the equation:
n = 1.645^2 * 0.175 * 0.825 / 0.025^2
n ≈ 185.16
So, the sample size that would limit the margin of error to be within 0.025 of the population proportion is approximately 185, rounded up to the nearest whole number.
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