Three small airplanes flight a 1000-mile route. Write a program
that inputs the airplane make,
model, and the number of gallons of fuel used by each airplane.
After calling a calcMPG()
function once for each airplane have main determine and display
which airplane is the most
fuel-efficient, and how many miles per gallon it got. The calcMPG()
function should be passed
the distance flew and the gallons of gas consumed as arguments and
should return the miles
per gallon obtained. Code must be written in C++
In: Computer Science
A four-lane urban freeway is rolling on rolling terrain with 12-ft lanes, obstructions 2-ft from the right edge of the traveled pavement, and nine ramps within three miles upstream and three miles downstream of the midpoint of the analysis segment. The traffic stream consists primarily of commuters. A directional weekday peak-hour volume of 2400 vehicles is observed with 800 vehicles arriving in the most congested 15-min period. If the traffic stream has 10% large trucks and buses and recreational vehicles, determine the level of service.
In: Civil Engineering
A six-lane freeway with three lanes in each direction has regular weekday users. The
lanes are 12 feet wide, the right-side shoulder is 2 ft wide, and there are two ramps
within 3 miles upstream and two ramps within 3 miles downstream of the segment
midpoint. The highway is on rolling terrain with 12% large trucks and buses and 2%
recreational vehicles. The peak hour factor is 0.85. Determine the maximum hourly
volumes that can be sustained at LOS C and LOS D densities.
In: Civil Engineering
Regarding the notion of organizational culture, structure and styles of management from the perspectives of Handy’s (1976) and Miles & Snow (1978). These authors provided their frameworks that are different from each other’s. What you have to do:
Take an organization with which you are familiar or imaginary organization and evaluate & relate or apply Handy’s and Miles & Snow’s typologies (scientific/logical classification/steps of organizational culture, structure and styles) that they provided in their approaches or framework.
Note: Your conversation must have to reflect your critical thinking and analytical skills.
In: Operations Management
all python
Question One [2 * 2.5]
•The sum
•The difference
•The product
•The average
•The distance (absolute value of the difference)
•The maximum (the larger of the two)
•The minimum (the smaller of the two)
Hint: Python defines max and min functions that accept a sequence of values, each separated with a comma.
Example:
Enter a letter grade: B-
The numeric value is 2.7.
Grade = 99
if Grade>= 90:
print("A")
if Grade >=80 :
print("B")
if Grade >=70 :
print("C")
if Grade >=60:
print("D")
else:
print("Failed")
In: Computer Science
The accompanying table shows a portion of data consisting of the selling price, the age, and the mileage for 20 used sedans. PictureClick here for the Excel Data File Selling Price Age Miles 13,554 7 61,477 13,713 8 54,368 22,970 2 8,242 15,260 2 24,882 16,386 1 22,126 16,639 7 23,654 16,902 2 47,397 18,485 3 16,820 18,830 7 35,376 19,828 3 29,634 11,896 8 55,775 14,937 6 46,198 15,879 3 37,035 16,467 7 45,548 9,478 8 86,924 12,994 6 77,257 15,710 7 59,600 10,517 9 93,215 8,940 10 48,217 11,953 10 42,411 a. Determine the sample regression equation that enables us to predict the price of a sedan on the basis of its age and mileage. (Negative values should be indicated by a minus sign. Round your answer to 2 decimal places.) Priceˆ = + Age + Miles. b. Interpret the slope coefficient of Age. The slope coefficient of Age is −487.30, which suggests that for every additional year of age, the predicted price of car decreases by $487.30. The slope coefficient of Age is −0.08, which suggests that for every additional year of age, the predicted price of car decreases by $0.08. The slope coefficient of Age is −487.30, which suggests that for every additional year of age, the predicted price of car decreases by $487.30, holding number of miles constant. The slope coefficient of Age is −0.08, which suggests that for every additional year of age, the predicted price of car decreases by $0.08, holding number of miles constant. c. Predict the selling price of a eight-year-old sedan with 68,000 miles. (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) Priceˆ = $
In: Math
What Influences the Sample Size? We examine the effect of different inputs on determining the sample size needed to obtain a specific margin of error when finding a confidence interval for a proportion. Find the sample size needed to give, with 95% confidence, a margin of error within plus-or-minus 2% when estimating a proportion. First, find the sample size needed if we have no prior knowledge about the population proportion p. Then find the sample size needed if we have reason to believe that p almost-equals 0.7. Finally, find the sample size needed if we assume p almost-equals 0.8. Round your answers up to the nearest integer.
Population proportion Sample Size
No knowledge:
0.7:
0.8:
In: Math
Ben would like to invest in gold and is aware that the returns
on such an investment can be quite volatile.
Use the following table of states, probabilities, and returns and
calculate the coefficient of variation for the investment?
(Round intermediate calculations and answer to 5
decimal places, e.g. 0.07680.)
| Probability | Return |
| Boom | 0.1 | 39 % |
| Good | 0.2 | 25 % |
| Ok | 0.3 | 10 % |
| Level | 0.2 | 7 % |
| Slump | 0.2 | -10 % |
| Coefficient of variation |
In: Finance
On each bet, a gambler loses $2 with probability 0.2, loses $1 with probability 0.7, or wins $10 with probability 0.1.
After 100 of these bets, what is the approximate probability that the gambler's total is negative?
Show your work below.
In: Statistics and Probability
The maintenance manager at a trucking company wants to build a regression model to forecast the time until the first engine overhaul based on four explanatory variables: (1) annual miles driven, (2) average load weight, (3) average driving speed, and (4) oil change interval. Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks.
| Time Until First Engine Overhaul (Yrs) | Annual Miles Driven (000) | Average Load Weight (tons) | Average Driving Speed (mph) | Oil Change Interval (000 miles) |
| 7.9 | 42.8 | 19 | 46 | 15 |
| 0.9 | 98.5 | 25 | 46 | 29 |
| 8.5 | 43.4 | 21 | 64 | 14 |
| 1.3 | 110.7 | 27 | 60 | 26 |
| 1.4 | 102.3 | 28 | 51 | 17 |
| 2.1 | 97.1 | 24 | 63 | 20 |
| 2.5 | 92.8 | 23 | 55 | 15 |
| 7.4 | 53.9 | 20 | 65 | 13 |
| 8.2 | 51.4 | 22 | 52 | 17 |
| 4.1 | 84.9 | 25 | 56 | 28 |
| 0.5 | 120.4 | 29 | 52 | 23 |
| 5.1 | 77.5 | 25 | 48 | 27 |
| 5.2 | 68.6 | 21 | 48 | 25 |
| 5.3 | 54.9 | 24 | 58 | 23 |
| 5.7 | 66.7 | 20 | 58 | 26 |
| 8.5 | 39.4 | 20 | 50 | 16 |
| 5.8 | 52.7 | 21 | 56 | 25 |
| 5.9 | 54.2 | 19 | 48 | 17 |
| 4.4 | 74.8 | 22 | 65 | 25 |
| 6.3 | 58.7 | 20 | 54 | 16 |
| 6.7 | 52.3 | 22 | 53 | 19 |
| 7.0 | 68.6 | 18 | 51 | 19 |
| 3.9 | 94.6 | 23 | 54 | 23 |
| 7.2 | 45.7 | 17 | 58 | 15 |
| 6.1 | 61.2 | 24 | 58 | 19 |
a. Estimate the regression model to predict the time before the first engine overhaul for a truck driven 60,000 miles per year with an average load of 22 tons, an average driving speed of 57 mph, and 18,000 miles between oil changes. (Note that both annual miles driven and oil change interval are measured in 1,000s.)
b. Use the above prediction to calculate and interpret the 90% confidence interval for the mean time before the first engine overhaul.
c. Calculate and interpret the corresponding 90% prediction interval for the time before the first
In: Statistics and Probability