My professor is looking for a simple data analysis demonstration from a statistics standpoint. Please choose a simple subject as I will be conducting a short oral presentation on the subject. I will need a Power Point Presentation and a written project report following the APA guidelines. I have attached a sample power point and a sample word document that were previously used for this project by another student for reference. Choose a subject along the lines of consumers and marketing please 🙂 let me know if you have any questions. I will be connected to my computer waiting for the work. Please refer to the work attached and follow the same guidelines.
Project
BUSN 5760
Anonymous
Anonymous
Webster University
BUSN 5760 – Applied Business Statistics
Fall 1 – AY 2007
Project Paper:
A Study on the Impact of Gender, Age, and
Ethnicity on Military Recruitment
1
Project
BUSN 5760
Anonymous
There has always been a correlation between age and military recruitment. The
recruitment of youth was taken for granted in the past. As a result of the recent downturn
in military recruitment, new initiatives are being launched to attempt to bolster
recruitment among the youth. The body of knowledge addressing the correlation
between military recruitment and age has progressed to capture these changes.
Physical requirements of military service necessitate that youth make up the rank and
file of the Services. Military tasks, including combat, demand stamina that is not
available to persons past their forties.1 A General Accounting Office (GAO) study done
in September of 2005 showed that sixty-nine percent of active service members are
between the ages of twenty and thirty-four, and outlined the profile of the military by age.
Please see bar graph excerpted below for further detail.2
The youth of the contemporary era, though, find military service a distasteful option.
Perceptions of the dangers of military service are recognized to be inhibiting recruiting
2
Project
BUSN 5760
Anonymous
efforts.3 College students are less likely to enlist in the military, and college enrollment
of African-Americans and Latinos, who are traditionally the bulk of military enlistees, is
rising.4
This shrinking pool of potential enlistees is causing the military to rethink its
strategies for recruiting youths. Military marketing campaigns have the stated objective
of increasing interest in young adults. In order to do this they have employed
nontraditional advertising methods, including web sites targeted to young adults, such as
the “El Navy” site intended for the young Latino audience. All the Services are moving
toward on-line recruitment, including using “chat rooms” to enlist new recruits.5 Special
events were also used to draw the attention of the youth. These measures of exotic
advertising increased the recruiting expense. The Services almost doubled their FY 2003
advertising budget versus the FY 1998 budget, and as of May, 2004, per-recruit
advertising expense had almost tripled over FY 1990 spending.6
The body of knowledge capturing and describing changes in the relationship
between age and military recruitment is comprehensive. Each study reviewed has shown
how compiled data reveals a trend in recruitment by age and then discusses the
organizational response to the trend. It is expected that the trends described above will
also be observed in the collected data for the project undertaken here. It is postulated that
the trend in recruitment of youths between ages eighteen and twenty-four will remain
constant as countervailing measures are employed to offset the diminishing voluntary
enlistments.
3
Project
BUSN 5760
Anonymous
Bibliography (May not be correct APA style!)
1
Quester, George H.. Parameters: US Army War College, Spring2005, Vol. 35 Issue 1,
p27-40, 14p; (AN 16345902)
2
Reporting Additional Service Member Demographics Could Enhance
Congressional Oversight, GAO-05-952, a report to Congress Requesters, September 2005
3
Moskos, Charles, Reviving the citizen-soldier, Public Interest, 00333557, Spring2002,
Issue 147
4
General Accounting Office report on military recruiting advertising released on
September 19, 2003, published in Congressional Digest in May of 2004.
5
Kimball P. Marshall and Ulysses J. Brown III: International Journal of Nonprofit and
Voluntary Sector Marketing, College of Business Administration, Loyola University
New Orleans
6
General Accounting Office report on military recruiting advertising released on
September 19, 2003, published in Congressional Digest in May of 2004.
4
Data Analysis Project
Anonymous Student
BUSN 5760
Professor Noffsinger
Synopsis
• The purpose of this data analysis
project was to determine the average
participation and lunches serviced
through the National School Lunch
Program for grades PK-12.
Hypothesis
• H10: There is no significant difference between the schools that participate
and the number of lunches serviced.
• H1A: There is a significant difference between the schools that participate
and the number of lunches serviced.
Data
• The data reflects from 2010-2017
the average participation and the
total lunches serviced. Participation
data are averaged over 9 months
since the summer months are
excluded.
NATIONAL SCHOOL LUNCH PROGRAM: PARTICIPATION AND LUNCHES
SERVED
(Data as of October 05, 2018)
——-Average Participation——Fiscal
Year
Free
Reduced
Full
Price
Price
Total
Total
Lunches
Percent
Free/RP
Served
of Total
———-Millions———-
%
2010
17.6
3.0
11.1
31.8
5,278.4
65.3
2011
18.4
2.7
10.8
31.8
5,274.5
66.6
2012
18.7
2.7
10.2
31.7
5,214.8
68.2
2013
18.9
2.6
9.2
30.7
5,097.6
70.5
2014
19.2
2.5
8.8
30.5
5,020.4
71.6
2015
19.8
2.2
8.5
30.5
5,005.4
72.6
2016
20.1
2.0
8.2
30.4
5,052.9
73.3
2017
20.0
2.0
8.0
30.0
4,891.4
73.6
Descriptive Summary
Mean
Median
Mode
1033.24825
19.05
31.8
Minimum
2
Maximum
5278.39
Range
5276.39
Variance
4253438.2587
Standard Deviation
2062.3865
Coeff. of Variation
199.60%
Skewness
1.5622
Kurtosis
0.4670
Count
Standard Error
40
326.0919
National School Lunch Program
25.0
20.0
15.0
Free
Reduced Price
Full Price
10.0
5.0
0.0
2010
2011
2012
2013
2014
2015
2016
2017
Regression Analysis
Simple Linear Regression Analysis
Calculations
b1, b0 Coefficients
b1, b0 Standard Error
R Square, Standard Error
F, Residual df
Regression Statistics
Multiple R
0.8517
R Square
0.7254
Adjusted R Square
Standard Error
Observations
0.6705
0.3865
8
Regression SS, Residual SS
ANOVA
df
Regression
Residual
Total
SS
1
5
6
MS
F
Significance F
1.9731 1.9731 13.2088
0.0150
0.7469 0.1494
2.7200
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95%
Upper 95%
Intercept
41.6712
6.1572 6.7679 0.0011
25.8437
57.4988
25.8437
57.49876
5278.39
-0.0044
0.0012 -3.6344 0.0150
-0.0075
-0.0013
-0.0075
-0.00129
Confidence level
t Critical Value
Half Width b0
Half Width b1
-0.0044
0.0012
0.7254
13.2088
41.6712
6.1572
0.3865
5.0000
1.9731
0.7469
95%
2.5706
15.8275
0.0031
Conclusion
• The results concluded that there is
a significant difference between the
schools that participate and the
number of lunches serviced.
Therefore, the null hypothesis that
there is a difference in the number
of schools participating cannot be
rejected.
References
• Education. (n.d.). Retrieved October 14, 18, from
https://www.data.gov/education/national-school-lunch-assistance-program
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