1 2 Insert Title Here Insert Your Name Here Insert University Here Course Name Here Instructor Name Date Data Analysis: Hypothesis Testing Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations if the models are statistically significant. Delete instructions and examples highlighted in yellow before submitting this assignment. Correlation: Hypothesis Testing Restate the hypotheses from Unit II here. Example: Ho1: There is no statistically significant relationship between height and weight. Ha1:There is a statistically significant relationship between height and weight. Enter data output results from Excel Toolpak here. Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis. Example: The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables. Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight. Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function. Simple Regression: Hypothesis Testing Restate the hypotheses from Unit II here. Ho2: Ha2: Enter data output results from Excel Toolpak here. Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation. Multiple Regression: Hypothesis Testing Restate the hypotheses from Unit II here. Ho3: Ha3: Enter data output results from Excel Toolpak here. Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, ...

1. 1
2
Insert Title Here
Insert Your Name Here
Insert University Here
Course Name Here
Instructor Name
Date
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation
analysis, simple regression analysis, and multiple regression
analysis using the correlation tab, simple regression tab, and
multiple regression tab respectively. The statistical output
tables should be cut and pasted from Excel directly into the
final project document. For the regression hypotheses, display
and discuss the predictive regression equations if the models are
statistically significant. Delete instructions and examples
highlighted in yellow before submitting this assignment.
Correlation: Hypothesis Testing
Restate the hypotheses from Unit II here.
Example:
Ho1: There is no statistically significant relationship between
height and weight.
Ha1:There is a statistically significant relationship between
height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below
the Excel output. Your explanation should include: r, r2, alpha

2. level, p value, and rejection or acceptance of the null hypothesis
and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a
moderately strong positive correlation. This equates to an r2 of
.36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 <
.05. Therefore, the null hypothesis is rejected, and the
alternative hypothesis is accepted that there is a statistically
significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically
calculate the p value when using the correlation function. As a
workaround, the data should also be run using the regression
function. The Multiple R is identical to the Pearson r in simple
regression, R Square is shown, and the p value is generated. Be
sure to show your results using both the correlation function
and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results
below the Excel output. Your explanation should include:
multiple R, R squared, alpha level, ANOVA F value, accept or
reject the null and alternative hypotheses for the model,
statistical significance of the x variable coefficient, and the
regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results
below the Excel output. Your explanation should include
multiple R, R squared, alpha level, ANOVA F value, accept or

3. reject the null and alternative hypotheses for the model,
statistical significance of the x variable coefficients, and the
regression model as an equation with explanation.
References
Include references here using hanging indentations. Remember
to remove this example.
Creswell, J. W., & Creswell, J. D. (2018). Research design:
Qualitative, quantitative, and mixed methods approaches (5th
ed.). SAGE.
2
Formative process
The first step in budgeting is creating the goals for the school.
This entail establishing the number of students admitted,
facilities needed and the number of workers (skilled and
unskilled) needed in the institution. This is a very important
step. The second step is to determine how much the institution
has in the bank account. This is meant to help establish how
much will be needed (Borough of Staten Island, 2019).
The third step is projecting the expected income or revenue.
This could be obtained from tuition fees, or from the
government grants. The fourth step is to categorize spending.

4. This where the priorities are made on what is needed and what
can wait. The last step is to create the budget spread sheet.
Challenges
There are many challenges that are encounter when making
budgets for any company, small or large. First, there is the
change in prices of items because of many forces in the market.
It has been known that minimum wages keep on changing from
one state to another for one reason or another.
Price of items can change because of forces of supply and
demand. This is true especially where the trade wars are
common. For instance, in the past administration, there was
heavy levies on all goods imported from certain countries. This
increases the cost of stationary and other learning materials.
Changes in prices and cost of operation requires the
management to draw supplementary budget which increases the
cost incurred.
Inflation is hard to account for when drawing the budget. While
the government makes effort to keep the inflation rate very low,
there are things that causes the inflation increase significantly.
Things affect by inflation is the cost of utilities such as the
water, fuel, and electricity ( Potter,Barry, H., & Diamond,
2014).
Assumptions
The assumptions are important when making budgets. The first
assumption is that the prices of the items in the budget
including the labor will not change. This will help setting prices
for all the items needed. The other assumption is that there will
be no interruption during the scheduled learning time table.
Disruption could be due natural disasters or pandemic such as
the COVID-19. Disruption fatally affects the anticipated
sources of income even when the recurrent costs are incurred.
For instance, during the pandemic, some workers had to be paid
even when there were no schools.
The other assumption is that there will be no policy changes
from the government that will affect tuition fees or how the
government grants are to be spend.

5. A statement of budgetary priorities.
1. The general reserve for the school should always be
maintained at 12%
2. The activities that are supported by the student should be
fully recoverable.
3. The budget development should be support by long term
budget plan.
4. The ongoing expenditures in school should be supported by
the income revenues from tuition fees and government grants.
5. Once a budget is adopted, it should be amended only when
there are emergencies.
The first basic principle of the school budgeting framework is
very important in funding the school priorities.
The funding formula and its purpose
The main source of the revenue is the tuition fees from the
students. The high tuition fees charged the students when used
well can fundamentally support all ongoing school operations.
From the tuition fees, the board can pay the teachers, buy
learning materials pay utilities and pay for the field trips and
studies. Also, the equipment needed for technical courses and
sciences can be bought using this money ( Potter,Barry, H., &
Diamond, 2014).
The second source of funds is the government grants. The good
thing is that there is annual state budget allocation to support
learning in various institutions. While the grants may have
limited uses according the federal and state laws, they help ease
the burden of the operation costs.
Lastly there is the money from non-government organizations
and donors. This money is not limited like the government
grants are. However, it is a requirement by the law for the
institutions to report whatever amount of money they receive
from donors. Most of the time, this money is used to buy
equipment, and sometimes hire teachers and technicians.
Expenditures and bonds
When the expenditures are more than what the revenue can

6. provide, the bonds can be used to fund the operations. Such
bonds can be issued public. They could have coupon or can be
zero coupon depending on what the board determines (Borough
of Staten Island, 2019).
Long range planning
The goal of every school is to make enough revenue to support
its operation. To achieve this, most of the money is spend on
the education related things such as hiring teachers, buying
equipment among others. Highly performing school gets better
chances of having more students and receiving more grants from
the government. Therefore, the goal should be to get more
students through high performance in classes and in the fields.
Prediction of responses
Since the worst case scenario is occurrence of activities that can
paralyze learning operation, the school ought to have good
credit scores so it can borrow from the financial institutions and
from the public.
References
Borough of Staten Island. (2019). Statement of budget
priorities: Fiscal year 1992. New York, NY.
In Potter,Barry, H., & In Diamond,A, J. (2014). Guidelines for
Public Expenditure Management. Washington: International
Monetary Fund.

7. Budget Worksheet and Template
Use this sheet to calculate prior year (PY) and current year
(CY) revenue, expenditures, fund balances, operational
balances, and budget balance. You may move or add items as
necessary.
No. of students (_20_) x ($_45000______ / student) = State
foundation funding = _$ 900000_______
Local Taxes
Amount
Quantity of maintenance and operation mills
$ 20,778.74
Quantity of debt service mills
$ 18,344.71
Quantity of capital outlay mills
$ 48,364.81
Total millage
$ 87,488.27
Assessed valuation
$ 4,374.41
Bonded debt
$ 874.88
Fund 1: Salary
Category
PY Actual
CY Budget
Beginning balance

8. $ -
$ -
Total revenue
$ -
$ -
Total expenditure
$ 36,682.57
$ 10,465.40
Total transfers
$ 45,729.69
$ 20,203.05
Ending balance
$ 26.42
$ 33,856.61
Full-time equivalents
$ 1,815.00
$ 1,815.00
Average teacher salary
$ 45,897.00
$ 45,897.00
Fund 2: Operating
Category
PY Actual
CY Budget
Beginning balance
$ 20,778.74
$ 37,001.63
Total revenue
$ 18,344.71
$ 10,361.74
Total expenditure
$ 43,691.04
$ 36,409.40
Total transfers
$ 1,675.48
$ 14,741.61

9. Ending balance
$ 20,778.74
$ 37,001.63
Fund 3: Building and Construction
Category
PY Actual
CY Budget
Beginning balance
$ 15,798.48
$ 52,327.39
Total revenue
$ 56,530.37
$ 32,367.10
Total expenditure
$ 18,393.87
$ 48,364.81
Total transfers
$ 14,450.37
$ 66,172.57
Ending balance—building and construction is part of capital
outlay
$ 24,704.53
$ 63,831.32
Fund 4: Debt Service
Category
PY Actual
CY Budget
Beginning balance
$ 6,727.40
$ 6,338.98
Total revenue
$ 7,725.85
$ 2,698.38
Total expenditure
$ 8,072.47
$ 8,902.07

10. Total transfers
$ 5,094.65
$ 3,179.96
Ending balance
$ 1,264.44
$ 7,767.23
Fund 5: Capital Outlay
Category
PY Actual
CY Budget
Beginning balance
$ 38,566.77
$ 14,388.16
Total revenue
$ 68,906.19
$ 72,184.90
Total expenditure
$ 11,742.63
$ 84,269.62
Total transfers
$ 70,837.26
$ 35,172.75
Ending balance
$ 3,529.52
$ 3,192.50
Fund 6: Federal Grants
Category
PY Actual
CY Budget
Beginning balance
$ 3,683.89
$ 1,008.64
Total revenue
$ 2,183.23
$ 4,100.90
Total expenditure

11. $ 6,744.33
$ 8,934.86
Total transfers
$ 132.39
$ 8,834.16
Ending balance
$ 5,241.74
$ 6,929.77
Fund 7: Activity
Category
PY Actual
CY Budget
Beginning balance
$ 748.12
$ 4,552.27
Total revenue
$ 3,823.13
$ 1,330.13
Total expenditure
$ 2,651.41
$ 1,196.18
Total transfers
$ 3,951.42
$ 2,917.25
Ending balance
$ 4,527.15
$ 2,584.81
Fund 8: Food Service
Category
PY Actual
CY Budget
Beginning balance
$ 161.72
$ 151.77
Total revenue
$ 345.33

12. $ 793.15
Total expenditure
$ 626.58
$ 968.87
Total transfers
$ 714.94
$ 500.02
Ending balance
$ 63.07
$ 242.82
Fund 9: Fixed Assets
Category
PY Actual
CY Budget
Beginning balance
$295,159.70
$499,715.25
Total revenue
$203,680.95
$197,467.44
Total expenditure
$338,885.52
$402,676.46
Total transfers
$135,092.53
$239,172.85
Ending balance
$120,076.41
$342,940.95
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
Remodeling
Category

13. PY Actual
CY Budget
Beginning balance
$3,472.03
$4,651.52
Total revenue
$0.00
$0.00
Total expenditure
$3,534.00
$691.64
Total transfers
$3,116.25
$514.36
Ending balance
$1,109.81
$4,089.91
Renovations
Category
PY Actual
CY Budget
Beginning balance
$371.64
$174.68
Total revenue
$0.00
$0.00
Total expenditure
$1,642.54
$3,975.96
Total transfers
$3,772.39
$2,259.04
Ending balance
$4,728.80

14. $4,161.72
Installation of service system
Category
PY Actual
CY Budget
Beginning balance
$621.18
$1,345.02
Total revenue
$0.00
$194.41
Total expenditure
$341.08
$265.70
Total transfers
$357.41
$470.52
Ending balance
$1,319.02
$466.21
Land and building improvement
Category
PY Actual
CY Budget
Beginning balance
$1,159.45
$14,449.95
Total revenue
$0.00
$0.00
Total expenditure
$13,777.05
$1,835.24
Total transfers

15. $11,369.13
$148.64
Ending balance
$10,440.75
$1,266.49
Purchasing buildings, vehicles, lawnmower and furniture
Category
PY Actual
CY Budget
Beginning balance
$25,868.36
$25,258.21
Total revenue
$0.00
$0.00
Total expenditure
$22,838.84
$4,416.45
Total transfers
$12,187.97
$38,841.99
Ending balance
$20,086.22
$38,594.93