In: Operations Management
discuss any four challenges that students who have just started tertiary education are faced with and that you think are most likely to contribute to the below average marks that the students are acquiring in the module and solutions to the challenges
In: Psychology
The North Central Water Company has finalized its financial statements for the 2019 financial year. The Company's board of directors has asked you, their cost accountant, to look at the financial results and to compare the financial performance for the 2019 fiscal year to the results of the 2018 financial year. The board would also like you to project the revenues and expenses for the 2020 financial year based on several key assumptions. They have asked you to submit an excel file containing the financial results and budget projections as well as a one page memorandum of your findings.
Financial Results:
Total Number of Customers 26,000 25,000
2019 % of Total Revenues 2018 % of Total Revenues
Revenues:
Water Sales $1,162,000 ? $1,200,000 ?
Late Fees 87,000 ? 68,000 ?
Fire Hydrant Fees 114,500 ? 122,000 ?
Total Revenues $1,363,500 100% $1,390,000 100%
Expenses:
Cost of Water Sold $512,000 ? $278,000 ?
Payroll Expense 608,000 ? 450,000 ?
Overhead Expense 292,050 ? 200,000 ?
Miscellaneous Expenses 64,075. ? 78,000 ?
Total Expenses $1,476,125 ? $1,006,000 ?
Net Income (Loss) <$112,625> ? $ 384,000 ?
I. Excel Analysis (Please submit your answers with the excel file provided for you in Ilearn entitled "North Central Financial Results- Student Copy".
Based on the financial results provided above, complete the excel spreadsheet file provided to you and submit your file in Ilearn. Please include include your name in the filename.
.
Required:
1. Calculate each revenue and expense item as a percentage of total revenues in 2019 and 2018 (show percentages out to TWO decimal places for all revenues and expenses, but round total revenue's percentage to ZERO decimal places- see examples in spreadsheet).
2. Calculate the water sales per customer for 2019 and 2018 (show number out to TWO decimal places- see example in spreadsheet).
3. Calculate the company's budgeted financial performance for 2020 based on the assumptions listed below for each revenue and expense item. Then calculate each item as a percentage of total revenues just like you did for 2019 and 2018. Then calculate the water sales per customer for 2020 just as you did for 2019 and 2018- see examples in spreadsheet.
4. Finally, calculate the differences in each revenue and expense item between 2020 and 2019, and 2019 and 2018- see example in spreadsheet. This will provide you with some insight about the year-to-year changes and help you with your business memo which is the second part of this project.
You must use formulas in the excel spreadsheet rather typing-in calculated numbers to get
full credit. You will also run into rounding errors unless you use formulas. Some formulas
and calculated numbers have already been included in the spreadsheet to help you. YOU
SHOULD HAVE AN ANSWER WHEREVER YOU SEE A QUESTION MARK (?)
ASSUMPTIONS:
Assume that the water company expects that in 2020:
a. The number of customers will increase by 5%.
b. Water sales will increase by 4% and late fees will increase by 1% due to increased customer demand.
c. Hydrant fees will decrease by 1% because several older hydrants will be taken out of service.
d. The cost of water sales will increase by 8% because of higher chemical costs.
e. Payroll expenses will increase by 5.5% due to wage increases and higher medical
insurance expenses.
f. Overhead expense will decrease by 4% because of efforts to reduce costs.
g. Miscellaneous expenses are expected to double because of the purchase of building supplies in anticipation of a major waterline project in 2020.
Here are some check figures to help you out:
2020 Total Revenue=1,409,705
2020 Total Expense=1,602,918
2020 Water Sales per customer= $44.27
Total Income<loss> 2020 vs 2019= <$80,588>
Total Income<loss> 2019 vs 2018=<$496,625>
Total Income <loss> as a percentage of total revenue in 2020=-13.71% Total Income <loss> as a percentage of total revenue in 2019=-8.26%
In: Finance
The data in TECHPRO.sav, obtained from Business Week’s (June 22, 2006) technology section, represents typical salaries of technology professionals in 13 metropolitan areas for 2003 and 2005. Suppose you want to determine if the mean salary of technology professionals at all US. Metropolitan areas have increased between 2003 and 2005.
(a) Set up the null and alternative hypothesis for the test.
(f) Conduct the appropriate test and provide your conclusion. More specifically, I want you to examine whether the null hypothesis should be rejected by analyzing the data with SPSS. alpha=0.05
DATA SET:
|
AREA |
SAL 2003 |
Sal 2005 |
|
Silicon Valley |
87.7 |
85.9 |
|
New York |
78.6 |
80.3 |
|
Washington, D.C. |
71.4 |
77.4 |
|
Los Angeles |
70.8 |
77.1 |
|
Denver |
73.0 |
77.1 |
|
Boston |
76.3 |
80.1 |
|
Atlanta |
73.6 |
73.2 |
|
Chicago |
71.1 |
73.0 |
|
Philadelphia |
69.5 |
69.8 |
|
San Diego |
69.0 |
77.1 |
|
Seattle |
71.0 |
66.9 |
|
Dallas-Ft. Worth |
73.0 |
71.0 |
|
Detroit |
62.3 |
64.1 |
In: Statistics and Probability
The data in TECHPRO.sav, obtained from Business Week’s (June 22, 2006) technology section, represents typical salaries of technology professionals in 13 metropolitan areas for 2003 and 2005. Suppose you want to determine if the mean salary of technology professionals at all US. Metropolitan areas have increased between 2003 and 2005.
(a) Set up the null and alternative hypothesis for the test.
(f) Conduct the appropriate test and provide your conclusion. More specifically, I want you to examine whether the null hypothesis should be rejected by analyzing the data with SPSS. alpha=0.05
DATA SET:
|
AREA |
SAL 2003 |
Sal 2005 |
|
Silicon Valley |
87.7 |
85.9 |
|
New York |
78.6 |
80.3 |
|
Washington, D.C. |
71.4 |
77.4 |
|
Los Angeles |
70.8 |
77.1 |
|
Denver |
73.0 |
77.1 |
|
Boston |
76.3 |
80.1 |
|
Atlanta |
73.6 |
73.2 |
|
Chicago |
71.1 |
73.0 |
|
Philadelphia |
69.5 |
69.8 |
|
San Diego |
69.0 |
77.1 |
|
Seattle |
71.0 |
66.9 |
|
Dallas-Ft. Worth |
73.0 |
71.0 |
|
Detroit |
62.3 |
64.1 |
In: Statistics and Probability
1. The owner of a popular chicken restaurant,
Chicken-For-Me, with many branches wanted to know if the quality of
customer service at a new restaurant was acceptable. One aspect of
service that was examined was the length of time that customers had
to wait in line before ordering their food. The restaurant decided
on acceptable probabilities for the waiting-time categories, and
these are given below.
Waiting-time Category
Probability
No more than 1 minute
0.15
More than 1 minute but no more than 3 mins
0.30
More than 3 minutes but no more than 5 mins
0.24
More than 5 minutes but no more than 10 minutes
0.25
More than 10 minutes
0.06
To investigate whether the quality of customer service was
acceptable, waiting times were recorded for a random sample of 100
customers at the new Chicken-for-Me. The table below shows the
number of customers observed in the five waiting-time
categories.
Waiting-time Category
Number of Customers
No more than 1 minute
20
More than 1 minute but no more than 3 mins
31
More than 3 minutes but no more than 5 mins
31
More than 5 minutes but no more than 10 minutes
15
More than 10 minutes
3
Total
100
Use the sample data for the 100 customers to conduct a statistical
test to determine if the waiting times at the new Chicken-For-Me
are inconsistent with the acceptable probabilities for the waiting-
time categories.
2.
A randomly selected group of men and women were surveyed to
investigate the association between gender and the amount of money
spent at a local store, Bullseye. Results are shown in the table
below:
Dollars Spent @ “Bullseye”
$0 to $50
$51 to $100
$101 to $200
more than $201
Total
Men
18
85
71
90
264
Women
35
72
98
142
347
Total
53
157
169
232
611
Is there convincing evidence that there is an association between
gender and the amount of money spent at “Bullseye”?
In: Statistics and Probability
The owner of a popular chicken restaurant, Chicken-For-Me, with
many branches wanted to know if the quality of customer service at
a new restaurant was acceptable. One aspect of service that was
examined was the length of time that customers had to wait in line
before ordering their food. The restaurant decided on acceptable
probabilities for the waiting-time categories, and these are given
below.
Waiting-time Category
Probability
No more than 1 minute
0.15
More than 1 minute but no more than 3 mins
0.30
More than 3 minutes but no more than 5 mins
0.24
More than 5 minutes but no more than 10 minutes
0.25
More than 10 minutes
0.06
To investigate whether the quality of customer service was
acceptable, waiting times were recorded for a random sample of 100
customers at the new Chicken-for-Me. The table below shows the
number of customers observed in the five waiting-time
categories.
Waiting-time Category
Number of Customers
No more than 1 minute
20
More than 1 minute but no more than 3 mins
31
More than 3 minutes but no more than 5 mins
31
More than 5 minutes but no more than 10 minutes
15
More than 10 minutes
3
Total
100
Use the sample data for the 100 customers to conduct a statistical
test to determine if the waiting times at the new Chicken-For-Me
are inconsistent with the acceptable probabilities for the waiting-
time categories.
Question #2
A randomly selected group of men and women were surveyed to
investigate the association between gender and the amount of money
spent at a local store, Bullseye. Results are shown in the table
below:
Dollars Spent @ “Bullseye”
$0 to $50
$51 to $100
$101 to $200
more than $201
Total
Men
18
85
71
90
264
Women
35
72
98
142
347
Total
53
157
169
232
611
Is there convincing evidence that there is an association between
gender and the amount of money spent at “Bullseye”?
In: Math