Collect Customer Data - Part 2

1. Collect Mileage information:

   Prompt: "Starting Odometer Reading:\n"

   Variable: odoStart = ?

   Prompt: "Ending Odometer Reading:\n"

   Variable: odoEnd = ?

   Add code to PRINT odoStart and odoEnd variables as well as the totalMiles to check your work.

   The following data will be used as input in the test:

   1. Prompt the user to input the starting odometer reading (expect type int from the user)
   2. Prompt the user to input the ending odometer reading (expect type int from the user)
   3. Test your code.

import sys
'''
Section 1: Collect customer input
'''
#Add customer input 1 here, rentalCode = ?

#Collect Customer Data - Part 2

#4)Collect Mileage information:
#a)   Prompt the user to input the starting odometer reading and store it as the variable odoStart

#Prompt -->"Starting Odometer Reading:\n"
# odoStart = ?

#b)   Prompt the user to input the ending odometer reading and store it as the variable odoEnd

#Prompt -->"Ending Odometer Reading:"
# odoEnd = ?

#c) Calculate total miles

#Print odoStart, odoEnd and totalMiles

# Calculate Charges 2

##   Calculate the mileage charge and store it as
# the variable mileCharge:

#a)   Code 'B' (budget) mileage charge: $0.25 for each mile driven

#b)   Code 'D' (daily) mileage charge: no charge if the average
# number of miles driven per day is 100 miles or less;
# i)   Calculate the averageDayMiles (totalMiles/rentalPeriod)

# ii)   If averageDayMiles is above the 100 mile per day
# limit:
# (1)   calculate extraMiles (averageDayMiles - 100)
# (2)   mileCharge is the charge for extraMiles,
# $0.25 for each mile

#c)   Code 'W' (weekly) mileage charge: no charge if the
# average number of miles driven per week is
# 900 miles or less;

# i)   Calculate the averageWeekMiles (totalMiles/ rentalPeriod)

# ii)   mileCharge is $100.00 per week if the average number of miles driven per week exceeds 900 miles

Im getting a Error on my Script at line 55:

LAST RUN on 9/14/2019, 8:44:31 AM

Check 1 failed

Output:

File "rental_car-customer-data-2.py", line 55 elif rentalCode == 'W' or rentalCode=='w': ^ SyntaxError: invalid syntax

Expected:

Starting Odometer Reading: Ending Odometer Reading: 1234 2222 988

My Script:

import sys
'''
Section 1: Collect customer input
'''
#Add customer input 1 here, rentalCode = ?
rentalCode = input("(B)udget, (D)aily, or (W)eekly rental?\n")
print (rentalCode)
#Collect Customer Data - Part 2

#4)Collect Mileage information:
#a)   Prompt the user to input the starting odometer reading and store it as the variable odoStart

#Prompt -->"Starting Odometer Reading:\n"
# odoStart = ?
odoStart = input('Starting Odometer Reading: ')
#b)   Prompt the user to input the ending odometer reading and store it as the variable odoEnd

#Prompt -->"Ending Odometer Reading:"
# odoEnd = ?
odoEnd = input('Ending Odometer Reading: ')
#c) Calculate total miles
totalMiles = int(odoEnd) - int(odoStart)
#Print odoStart, odoEnd and totalMiles
print (odoStart)
print (odoEnd)
print (totalMiles)

# Calculate Charges 2

##   Calculate the mileage charge and store it as
# the variable mileCharge:

#a)   Code 'B' (budget) mileage charge: $0.25 for each mile driven
if rentalCode == "B" or rentalCode=='b':
mileCharge = totalMiles * 0.25
#b)   Code 'D' (daily) mileage charge: no charge if the average
# number of miles driven per day is 100 miles or less;
# i)   Calculate the averageDayMiles (totalMiles/rentalPeriod)
elif rentalCode == "D" or rentalCode=='d':
rentalPeriod = int(input('Enter days rented: '))
averageDayMiles = totalMiles/rentalPeriod
if averageDayMiles <= 100:
mileCharge=0
# ii)   If averageDayMiles is above the 100 mile per day
# limit:
# (1)   calculate extraMiles (averageDayMiles - 100)
else:
# (2)   mileCharge is the charge for extraMiles,
# $0.25 for each mile
mileCharge = (averageDayMiles-100) *0.25

#c)   Code 'W' (weekly) mileage charge: no charge if the
# average number of miles driven per week is
# 900 miles or less;
elif rentalCode == 'W' or rentalCode=='w':
rentalWeek = int(input('Enter rental week: '))
averageWeekMiles = totalMiles / rentalWeek
if averageWeekMiles<=900:
mileCharge=0
else:
mileCharge=100*rentalWeek
print('Charges : ${}'.format(mileCharge))
# i)   Calculate the averageWeekMiles (totalMiles/ rentalPeriod)

# ii)   mileCharge is $100.00 per week if the average number of miles driven per week exceeds 900 miles

ONLY ANSWER PART C, D AND E

1A. Suppose The lifetime for a competing brands of tires are independent of each other and approximately normal with unknown means but known variances

σ^2= 975 miles^2 and σ^2= 965 miles^2. We gather did some testing under controlled conditions and have the following summary statistics:

n1= 75

̄x1= 3251.4

n2= 60

̄x2= 3274.7

Construct a 80% confidence interval for the difference in population means,μ1−μ2.

B.Using the same setup as part A, conduct a hypothesis test to check if the means are equal. Use α= 0.2.

C.Using the same setup as part A, but now assuming we do not know the variances but assume they are equal. Construct a 99% confidence interval for the difference in means using the same sample data as before. We now know that the sample variances are s^2= 982.2 and s^2= 967.4.

D.Using the same setup as part C, construct a 90% confidence interval for the ratio of variances σ^2/ σ^2.

E. Using the same setup as part C, conduct a hypothesis test to test whether population 1 has a smaller variance than population 2 using α= 0.1.

There are 750,000 residents in a city. Based on a government poll, they fall within three groups regarding their willingness to pay for the construction of a park.

- 200,000 of the residents are not willing to pay for the park at all,

- 250,000 residents are willing to pay $12,

- 300,000 are willing to pay $100.

The cost of the park will be $15 million. Should it be built? Why or why not?

Would this answer change if the only way to pay for it is to divide the cost equally across each of the 750,000 residents? Why or why not?

SUBJECT: AUDIT & ASSURANCE

Forecast Financial Statements

On your second day at AA’s head office, you have been given the forecast financial statements for the full year to 30 June 2020, as well as the previous two years’ audited results.

Aussie Airlines: Consolidated Income Statement (Selected) Year Ended 30th June
Currency AUD Millions (figures are rounded)

Aussie Airlines: Consolidated Balance Sheet (Selected) As at 30th June
Currency AUD Millions (figures are rounded)

QUESTION: After discovering that Aussie Airlines is a going concern, select one material account from AA’s Balance Sheet and one material account from the Income Statement and prepare a brief plan for auditing each account. Give particular attention to the following:

1. An assessment of the audit risk for the account, given the information in this case study and your assumptions.

2. The relevant/significant audit assertions for this account.

3. Name two controls that you would expect management to implement for this account. How would you test these controls.

4. Describe two substantive testing procedures that you would perform in relation to this account to address the relevant/significant assertions.

1. In general, the marginal cost curve is U-shaped as you learned in lectures and the textbook. However, exception exists. Please provide one particular industry as an example to illustrate that MC is not U-shaped. Explain briefly the shape of MC in the industry. 2. Engineers at a national research laboratory built a prototype automobile that could be driven 180 miles on a single gallon of gasoline. They estimated that in mass production the car would cost $40,000 per unit to build. The engineers argued that Congress should force U.S. automakers to build this energy-efficient car. In your opinion, is energy efficiency the same thing as economic efficiency? Please explain your opinion and state whether you support it or not.

A fire insurance company thought that the mean distance from a home to the nearest fire department in a suburb of Chicago was at least 4.7 miles. It set its fire insurance rates accordingly. Members of the community set out to show that the mean distance was less than 4.7 miles. This, they thought, would convince the insurance company to lower its rates. They randomly identified 64 homes and measured the distance to the nearest fire department from each. The resulting sample mean was 4.4. If σ = 2.4 miles, does the sample show sufficient evidence to support the community's claim at the α = 0.05 level of significance?

A.) Conduct a hypothesis test using the classical approach.

B.) Conduct a hypothesis test using the p-value approach.

1. You live 20 miles away from your job, where you work five days per week (except for a two-week vacation every year). Your car gets 35 miles per gallon, on average.
   1. If the average price per gallon of gas is $2.50, how much should you budget for gas for your commute in your annual budget?
   2. You are considering a new job that is 30 miles from where you live. How much more will your commute cost you each year?
   3. If you take the new job and the price of gas rises to $3.00 per gallon, how much more will your commute cost you each year?

A fire insurance company thought that the mean distance from a home to the nearest fire department in a suburb of Chicago was at least 4.7 miles. It set its fire insurance rates accordingly. Members of the community set out to show that the mean distance was less than 4.7 miles. This, they thought, would convince the insurance company to lower its rates. They randomly identified 64 homes and measured the distance to the nearest fire department from each. The resulting sample mean was 4.4. If σ = 2.4 miles, does the sample show sufficient evidence to support the community's claim at the α = 0.05 level of significance?

A.) Conduct a hypothesis test using the classical approach.

B.) Conduct a hypothesis test using the p-value approach.

Continental Railroad decided to use the high-low method and operating data from the past six months to estimate the fixed and variable components of transportation costs. The activity base used by Continental Railroad is a measure of railroad operating activity, termed "gross-ton miles," which is the total number of tons multiplied by the miles moved.

Determine the variable cost per gross-ton mile and the total fixed cost.