1
8
Human Trafficking
Maria Fernanda Granadillo
SYG2323.0M1
Santa Fe College
Abstract
Human trafficking has been a global crisis existing since the 13th century. However, the action violates human rights and the mission to end modern-day slavery. Human trafficking can actively be done where people are forced to work, enslaved people, or commercial sexual exploitation; otherwise, passive human traffic exists in cases of forced marriage. The research needs to identify the source of the million cases of human trafficking as a gazette in the California charter. There is an urgent need to end modern-day slavery, promote equality consciousness, and promote humanity.
Introduction
Criminology relates to different topics. The research focuses on human trafficking as a discipline of criminology. The study incorporates various data collection methods such as observation and internet exploration. This article integrates knowledge from all sources to find out more about human trafficking, the possible reasons for the recent increase of related cases, and provide possible solutions as suggested.
Methodology: Secondary Data
Human trafficking has existed for centuries, and the misled culture continues today. According to (Adler, Mueller, and Laufer,2007), the slave trade still exists between developing and affluential countries. During the research, secondary methods of data collection used include; government publications, public records, documents, and internet exploration (Adler, Mueller, and Laufer,2007).
According to government publications on global human trafficking analysis, 70 percent of developing countries experience the challenge directly or indirectly (Cockbain & Bowers, 2019). The number of trafficking victims is estimated to be 27 million globally, with between one and two million trafficked each year internationally (Cockbain & Bowers, 2019). The clear case is in Pakistan, where sex trafficking is often seen as a regular activity to sustain basic needs.
The problem has become a global crisis in which fewer efforts to provide a long-lasting solution have entirely failed. (Cockbain & Bowers, 2019) says a common factor of human trafficking is sex trafficking across the borders between developing countries and affluent nations. Many victims of the immoral and violated actions are youths, majorly young women, and underage children trying to secure peanut earnings through sexual acts (Adler, Mueller, & Laufer,2007). Instead of helping the low-income families make a living, the affluents take advantage to harass them sexually and encourage sexual trafficking.
However, distinguished human trafficking, where low-income earners are forced labor is evident in the United States (Adler, Mueller, & Laufer,2007). Domestic trafficking and illegal labor mobility are apparent from state to state without the consent and agreement of the servant. In a case documented in the California gazette, a domestic lady worker from Pakistan working in ...
1 8Human Trafficking Maria Fernanda GranadilloSYG23
1. 1
8
Human Trafficking
Maria Fernanda Granadillo
SYG2323.0M1
Santa Fe College
Abstract
Human trafficking has been a global crisis existing since the
13th century. However, the action violates human rights and the
mission to end modern-day slavery. Human trafficking can
actively be done where people are forced to work, enslaved
people, or commercial sexual exploitation; otherwise, passive
human traffic exists in cases of forced marriage. The research
needs to identify the source of the million cases of human
trafficking as a gazette in the California charter. There is an
urgent need to end modern-day slavery, promote equality
consciousness, and promote humanity.
2. Introduction
Criminology relates to different topics. The research focuses on
human trafficking as a discipline of criminology. The study
incorporates various data collection methods such as
observation and internet exploration. This article integrates
knowledge from all sources to find out more about human
trafficking, the possible reasons for the recent increase of
related cases, and provide possible solutions as suggested.
Methodology: Secondary Data
Human trafficking has existed for centuries, and the misled
culture continues today. According to (Adler, Mueller, and
Laufer,2007), the slave trade still exists between developing
and affluential countries. During the research, secondary
methods of data collection used include; government
publications, public records, documents, and internet
exploration (Adler, Mueller, and Laufer,2007).
According to government publications on global human
trafficking analysis, 70 percent of developing countries
experience the challenge directly or indirectly (Cockbain &
Bowers, 2019). The number of trafficking victims is estimated
to be 27 million globally, with between one and two million
trafficked each year internationally (Cockbain & Bowers, 2019).
The clear case is in Pakistan, where sex trafficking is often seen
as a regular activity to sustain basic needs.
The problem has become a global crisis in which fewer efforts
to provide a long-lasting solution have entirely failed.
(Cockbain & Bowers, 2019) says a common factor of human
trafficking is sex trafficking across the borders between
developing countries and affluent nations. Many victims of the
immoral and violated actions are youths, majorly young women,
and underage children trying to secure peanut earnings through
sexual acts (Adler, Mueller, & Laufer,2007). Instead of helping
the low-income families make a living, the affluents take
advantage to harass them sexually and encourage sexual
trafficking.
However, distinguished human trafficking, where low-income
3. earners are forced labor is evident in the United States (Adler,
Mueller, & Laufer,2007). Domestic trafficking and illegal labor
mobility are apparent from state to state without the consent and
agreement of the servant. In a case documented in the California
gazette, a domestic lady worker from Pakistan working in a
household in Chicago and signed for the household servant was
transferred to Minnesota to work in a relative house without her
consent or agreement with the same compensation (Cockbain &
Bowers, 2019). This is a precise instance of direct violation of
human rights and modern-day slavery.
Cockbainand Bowers (2019) state that since 2009, Canada has
recorded a 29 percent instance of human trafficking affecting
about 39 percent of her population. However, the citizen is
aware it is prohibited by the legislation and a criminal offense
(Cockbain & Bowers, 2019). This indicates apparent gross
misconduct calling for law enforcement and severe punishment
for the offenders. According to statists, nova scotia is an
established corridor used to transport victims of domestic
trafficking to Atlantic Canada. It indicates a failed government
dealing with this inhumane action (Adler, Mueller, &
Laufer,2007).
In another instance from global news and peace documentation,
Africa has the most significant percentage of human trafficking
activities Regarding forced labor, slavery, sex trafficking, and
forced marriages and relationships. According to Cockbain &
Bowers, (2019) statistics on criminology, Africans working in
European, American, and Gulf countries are engaged in forced
labor, contract agreement violations, extra uncompensated
working hours, and even sexual engagement without their
consent (Cockbain and Bowers, 2019). Alternatively, due to
denominational and cultural concepts, young people are engaged
with each other without their determination, yielding picked
culture such as Karo Kari referring to women who refuse false
engagement in Arabic culture (Cockbain and Bowers, 2019).
Human trafficking has been identified as a global crisis
addressed by international tribunals, social service agencies,
4. ambassadors, and media outlets. It has resulted in international
and federal laws changing, attracting criminal investigations
internationally ((Cockbain & Bowers, 2019). To fight sex
trafficking, the global response needs a concurrent address,
local lovers. The international court of criminals summons any
nation that fails to implement human trafficking rules.
Human beings violate laws. Thus, implementing the law is not
enough to combat the action entirely. Local levels of education
and law interpretation on any attempt of human trafficking will
work along. This requires educating victims on vulnerabilities,
respect for humanity and human rights, freedom to work, and
slavery response.
Theory
The social control theory focuses on techniques and strategies
that regulate human behavior leading to conformity and
obedience to society’s rules. The theory governs individual
coordination in society and ensures it’s according to societal
control (Adler, Mueller, and Laufer, (2007). It governs human
actions from the individual level to the entire society. The
theory applies to regulating human trafficking which is
inhumane and wrong regarding all beliefs (Franchino-Olsen et
al.,2022). Societal has a role to condemn evil acts and regulate
human behavior in distinguishing what is right and wrong.
Methodology: Primary Data
Primary data collection methods are surveys, interviews,
experiments, and questionnaires in the research. Interviews
refer to interrogating an individual on how well they are
conversant with the topic. Surveys refer to critical observation
of the subject matter, in this case, human trafficking.
Using questionnaires, out of ten participants, at least six have
directly or indirectly been a victim, most of them being African
American citizens. From personal interviews, engaging a
domestic manager locked in her boss's house and trying to reach
out for government agencies' aid in vain is a factual existence
of slavery and forced labor (Adler, Mueller, and Laufer,2007).
5. Taking samples of the population, at least 20 percent have been
victims of human trafficking.
Cockbain and Bowers, (2019), Federal and international law
have failed to control the action. It calls for a new strategy to
extinct the bypassed behavior promotes equality and humanity
globally.
Given a chance to conduct research, I will engage the
government, mainly the African American ambassadors, on
federal law and their concern to ensure their workers in foreign
nations are safe from human trafficking. Additionally, I will
consider the origin of the issue through interviews and propose
possible solutions (Franchino-Olsen et al.,2022). For instance,
research needs vie from victims of the vulnerability of
trafficking, possibly victims who engage in this illegal business,
and the government to act on the set regulations.
Questions to be used in the questionnaires include;
· What is the experience of human trafficking as a victim?
· Did you seek any help from government offices, if yes, details
about it.
· Have you witnessed any case of human trafficking from close
contact?
· What should the federal government do to deal with human
trafficking
Human trafficking is a global crisis involving all capitalist and
communist nations. This shows the importance of a worldwide
solution; however, the government might have failed due to a
lack of valuable and informative sources on the ongoing crisis.
Given a chance to do primary research, I will ensure
informative research paper drafting to deliver this concurrent
old narrative.
Findings
Considering the secondary data analysis, human trafficking is
continuously growing up to date. The issue has been addressed
by media such as the California gazette and government
statistics. It is evident that malpractice mainly involving
developing countries is still thriving regardless of global rules
6. on the protection of human rights (Franchino-Olsen et al.,2022).
The main reason could be the lack of enough education on the
protection of human rights and poverty in developing countries.
Conclusion
Human trafficking is a global crisis involving all capitalist and
communist nations. This shows the importance of a worldwide
solution; however, the government might have failed due to a
lack of valuable and informative sources on the ongoing crisis.
Given a chance to do primary research, I will ensure
informative research paper drafting to deliver this concurrent
old narrative.
References
Adler, F., G. Mueller, & W. Laufer. (2007). Criminology and
the Criminal Justice System (6th edition). New York, NY.
McGraw Hill
Cockbain, E., & Bowers, K. (2019). Human trafficking for sex,
labor, and domestic servitude: how do key trafficking types
compare and their predictors? Crime, Law and Social
Change, 72(1), 9-34.
[email protected](#) IBM SPSS STATISTICS 64-bit MS
Windows 28.0.0.0
����������������i���������[email protected]
Feb 2213:29:37
���������������������������ID ����
������������
���
��LASTNAME������������������������
����
������������
���
9. )/review:[email protected]('0'
)/extcr:[email protected]('0'
)/quiz2:[email protected]('0'
)/quiz4:[email protected]('0'
)/quiz5:[email protected]('0'
)/percent:[email protected]('0'
)/grade:[email protected]('0'
)/passfail:[email protected]('0'
)/gender:[email protected]('0'
)/ethnicity:[email protected]('0'
)/year:[email protected]('0'
)
���������������UTF-
8�������������e��������@VALAZQUEZ
SCOTT ���(��@kfn�efnjm���fhg�C P
�����:�A����e��jOSBORNE ANN {��G�z
@fk�eelkj���egf��[email protected] P
����`��ATOMOSAWA���e��ngDANIEL
�Q�����@l�efmnn�[email protected]��ffg���B P
�����w�ASWARM ��e��nglMARK
�������@�fennm��������[email protected]
�fhg����P ������
AMISCHKE ELAINE �e��kfg�)���(
10. @eeljl���D P ehe���������8� AAUSTIN
DERRICK e��lgi�fףp=
� @eijh���fD P
hg�����e�������ACARPIO MARY ��len�feffffff
@nnm���[email protected] P
f�����e�����8��ASAUNDERSTAMARA
�hfi�fej�������@hi���[email protected] P
�����e������x��ADEVERS GAIL
����Q��@lek�eejkm���egg�[email protected] P
����r� A����e��mJONES LISA ������
@gk�eelmj���egg��������[email protected] P
����dd%AWEBSTER ���e��ngDEANNA
�������@l�femnn�������[email protected]��egf��
�A P �����'&ABATILLER��e��kfjFRED
R����Q�?�fekki��[email protected] �fff����P
������'ALANGFORDTREVOR �e��kfm
̮ G�z��
@femml���������[email protected] P
fhg�����������'AKURSEE JACKIE e��jfm�f
=pף
@ejkn���eB P gg�����e�����C'AGOUW
BONNIE
��lgl�fe333333�@knl���eh������[email protected]
P f�����e�����6�(ALEWIS CARL
�kel�efi�������@hk���[email protected] P
�����e������
{+ACOCHRAN STACY
)���(�@lfn�ffmnm���fhg�[email protected] P
������+A����e��jMARQUEZ
CHYRELLE�������?fk�felkm���ehe��[email protected
11. ] P ������+ALESKO ���e��hgLETICIA
�Q����
@n�femnl�������[email protected]��egf���A P
������,ALIAO ��e��nfnMICHELLE=
=pף
@�ffmnm��A �eff����P ������,AYEO
DENISE �e��kgk�=
=pף
@fenlm���[email protected] P eeg���������`?-
ARONCO SHERRY
e��ken�f�������@emnk���e������[email protecte
d] P hf�����f����@��@VILLARRUZ
ALFRED
��mfi�fe�������@ijg���ff������[email protected]
P f�����f�����P��@GALVEZ JACKIE
�lfn�ffk�G�z���@mk���[email protected] P
�����f���������AGUADIZ VALERIE
����Q��@lek�eelln���efh�[email protected] P
����0i�A����f��nRANGIFO TANIECE ������
@gn�fenmm���ehg��[email protected] P
����H��ALIAN ���f��leJENNY ���(�
@l�femnn�������[email protected]��eif���A P
�����.�ABAKKEN ��f��nenKREG
�������@�ffnnm��������[email protected]
�fhg����P �������ALANGFORDDAWN
�f��mfh��Q����
@efnnn���A P
egg���������P�AVALENZUELA NANCY
12. f��ifk�e���(��@elkn���[email protected] P
eh�����f�����f�AKHOURY DENNIS
��kel�ee�������@lnj���fh������[email protected]
P g�����f�����H�
APOTTER MICKEY �ngi�felR����Q
@hn���[email protected] P �����f�������
ALEE JONATHAN333333
@lfi�ffkkj���ffh�[email protected] P ������
A����f��lDAYES ROBERT
)���(�@el�eemkn���fhg��C P �����w
ASTOLL ���f��hfGLENDON
H�z��G�@i�eemjn�[email protected]��fhg���C P
�������ACUSTER ��f��lehJAMES
�������@�eemnk��������[email protected]
�fhh����P ����,��AWU VIDYUTH
�f��jfn�������
@fejjj���[email protected] P
eff������������ACHANG RENE
f��ifn�f������
@elnl���e������[email protected] P
fg�����f�������ACUMMINGSDAVENA
��mgm�fe�G�z���@nmm���ei������[email protecte
d] P g�����f������ABRADLEY SHANNON
�ken�fem�G�z���@mm���ehg������[email protecte
d] P �����f�������u�AJONES ROBERT =
13. =p@�ףjgf�feiij���fgh�������[email protected] F
�������A����f�fjTORRENCEGWEN
fj�ffikj���egf��[email protected] P
�����AUYEYAMA ���f��jfVICTORINE
����Q��@n�eflnk�������[email protected]��eeg��
�B P �����3�ALUTZ ��f�gifhWILLIAM
�ffmnl��������[email protected] �fhg����P
�������ASHIMA MIHAELA �f��kfj�=
=p@�ףfekjl���C P
efg���������@��ADOMINGO MONIKA
f��ngn�e�p=
ף
@fnmm���e������[email protected] P
hg�����f�����P�ARATANA JASON ��lel�fe=
=p@�ףmnm���ff������[email protected] P
g�����f������s�AEVANGELIST NIKKI
�lfg�felH�z��G
@nj���efgB P �����f������̠�ADE
CANIOPAULA =
=pף
@jfk�fekmm���ehg�[email protected] P
�������A����f��iBADGER SUZANNA
�z��G��@gn�fennn���ehg��B P
����,��ASURI ���f��ifMATHEW
ffffff�@k�eejll�������[email protected]��ffg���C
P ������APANG ��f��kelSUZANNE H�z��G
@�fejlk��[email protected] �efg����P
�����R�AGALANVILLE DANA
�f��hgj�)���(�@eelil���������[email protected]
14. P eih����������F�AHANSEN TIM
f��mel�f����Q�
@fnmn���fA P
hg�����f�����w�APICKERING HEIDI ��igh�ee
=pף
�@khk���egC P g�����f�������APARK
SANDRA
�jfl�fel�z��G��@nm���egh������[email protected]
P �����f�������D�ALANGFORDBLAIR ���(
@len�ffnmn���fgg�[email protected] P
�������A����f��lSTEPHEN LIZA
�������@fl�femln���eig��[email protected] P
����Ps�AHUANG ���f�gjgJOE
d�eeifi�[email protected]��fig���F F
�������ASCARBROUGH ��f��kflCYNTHE
�������@�feihk��������[email protected]
�ehg����P �����xAFIALLOS LAUREL
�f��kfk�333333�@eeljj���[email protected] P
ehf���������P�ARATHBUN DAWNE
f��mfn�e)���(
@emnl���eA P hh�����f����̩ AHAMIDI
KIMBERLY��jek�ee�G�z��
@kml���ei������[email protected] P
g�����f�����~� AKWON SHELLY
�hen�ffn333333�@nl���[email protected] P
�����f��������!AHURRIA WAYNE ����Q�
@jfh�eeijj���fef�D P
������!A����f��lBULMERKAHUSIBA ������
@gn�eflmk���ehh��B P
15. ������!AMISHALAN���f��keY LUCY
�������@d�fegff�������[email protected]��ehg��
�F F ����>$"ACRUZADO
��f��lfmMARITESSffffff�@�felll��[email protected]
�ehh����P �����)"AWILLIAMSOLIMPIA
�f��ngk�=pף
��?eejni���[email protected] P
egg�����������"AVASENIUSRUSS f��igj�f)���(
@eklj���[email protected] P
gg�����f����>�"ASPRINGERANNELIES��nen�fe��
Q��
@nnn���[email protected] P g�����f������
#ACORTEZ VIKKI �mgi�fek{��G�z�@ij���eghC
P �����f�������H$AKHAN JOHN
�������?lgi�felfk���fhg�[email protected] P
������$A����f��jGRISWOLDTAMMY
�������?fi�fekil���ehg��������[email protected]
P �����y%ASUNYA ���f�gngDALE
n�femnk�������[email protected]��fig���B P
����>�&ASONG ��f��jgjLOIS
��(���?�eemkn��[email protected] �ffg����P
������&ABELTRAN JIM
�f��kej��(��@eelik���C P
fgg���������zG'ADAEL IVAN f��nen�fףp=
��@fmnn���f������[email protected] P
gf�����f����`['AROBINSONERIC ��ifl�feq=
p@�ףlln���[email protected] P
g�����f������w'ADUMITRESCU STACY
�ifk�een
=pף
16. @mn���fhh������[email protected] P
�����f��������'AANDERSONERIC
333333�@jgg�eejfj���fih�[email protected] F
������'A����f��lAHGHEL BRENDA ������
@eg�feifh���eig��������[email protected] F
������'AROBINSON���f��neCLAYTON
�������@n�fenmn���fhg���A P
������'AWATKINS ��f�hlemYVONNE �femnm��A
�egh����P �����a(AZUILL RENAE
�f��ieh���(���@ffmnl���[email protected] P
ehg�����������(ACARRINGTON JYLL
f��kem�f333333�?enll���eC P
hg�����f������)AVALENZUELA KATHRYN
��lel�fe333333�@mnl���eh������[email protected]
P e�����f�������)APRADO DON
�mgn�femR����Q
@lm���[email protected] P
�����f������4�*AREYNO NICHOLASq=
pף
@ngn�eflnn���fhg�33[email protected] P
�����_+A����f�fiHUANG MIRNA
ek�eejlk���efg��[email protected] P
�����d+AGENOBAGA���f��jgJACQUELINE
���(
@l�femlk�[email protected]��efg���B P
�����m+ARAO ��f��kelDAWN ������
@�fenlm��A �efg����P
�����s+AHAWKINS CARHERIN�f��ifn�E
{��G�z�@eelnk���[email protected] P
egh���������*�+AJENKINS ERIC
f��jgj�e����Q��@eljn���fB P
17. gf�����f������+ASHEARER LUCIO
��jen�fe��(���@nml���[email protected] P
g�����f�������,AKINZER RICHARD �lfk�femףp=
��@kl���[email protected] P
�����f������T�,ASUAREZ-TAN KHANH
)���(�@ngk�fflnk���efg�[email protected] P
����|�,A����f��kLEDESMA MARTINE
�������@fj�fekim���ehg��B P ����
�-AKAHRS ���f��nfJANN
�(����@n�fennn�������[email protected]��ehh���
C P �����-AROSS ��f��iemMARIA
��Q��� @�fekmk��[email protected]
�ehh����P ������-AZIMCHEK ARMANDO
�f��jeh�333333�@feljm���[email protected] P
fhh�����������-ANEUHARTHJIM
f��igh�f�������?ejhi���fD P
hg�����f������.ASLOAT AARON
��ngh�ee�z��G��@ijj���[email protected] P
g�����f�������.ACHA LILY �ien�ffmq=
p@�ףnk���ehf������[email protected] P
�����f�������-.AMCCONAHACORA
333333�@lgk�fellk���ehg�[email protected] P
Remove or Replace: Header Is Not Doc Title
[Type here]
Data Set Instructions
The grades.sav file is a sample SPSS data set. The fictional data
represent a teacher’s recording of student demographics and
performance on quizzes and a final exam across three sections
of the course. Each section consists of about 35 students (N =
105).
18. Last week, you converted grades2.dat to grades.sav. There are
21 variables in grades.sav. Open your grades.sav file and go to
the Variable View tab. Make sure you have the following values
and scales of measurement assigned.
SPSS variable
Definition
Values
Scale of measurement
id
Student identification number
Nominal
lastname
Student last name
Nominal
firstname
Student first name
Nominal
gender
Student gender
1 = female; 2 = male
Nominal
ethnicity
Student ethnicity
1 = Native; 2 = Asian; 3 = Black;
4 = White; 5 = Hispanic
Nominal
year
Class rank
1 = freshman; 2 = sophomore;
3 = junior; 4 = senior
Scale
lowup
Lower or upper division
19. 1 = lower; 2 = upper
Ordinal
section
Class section
Nominal
gpa
Previous grade point average
Scale
extcr
Did extra credit project?
1 = no; 2 = yes
Nominal
review
Attended review sessions?
1 = no; 2 = yes
Nominal
quiz1
Quiz 1: number of correct answers
Scale
quiz2
Quiz 2: number of correct answers
Scale
quiz3
Quiz 3: number of correct answers
Scale
quiz4
Quiz 4: number of correct answers
Scale
quiz5
Quiz 5: number of correct answers
20. Scale
final
Final exam: number of correct answers
Scale
total
Total number of points earned
Scale
percent
Final percent
Scale
grade
Final grade
Nominal
passfail
Passed or failed the course?
Nominal
1
1
TOPIC: Descriptive Statistics
Your first IBM SPSS assignment includes two sections in which
you will do the following:
· Create two histograms.
· Calculate measures of central tendency and dispersion.
·
· As you work on this assignment, you may find the Data Set
Instructions [DOCX] helpful.
· Provide a title for your document
21. The grades.sav file is a sample SPSS data set. The data
represent a teacher's recording of student demographics and
performance on quizzes and a final exam. you will create and
describe two histograms and a descriptives table using these
data.
Part 1
Create two histograms for visual interpretation using the
following variables:
SPSS Variable
Definition
Lowup
Lower division =1; Upper division =2
Final
Final exam: number of correct answers
Create two histograms and paste them into your Word
document:
· A histogram for lower division students.
· A histogram for upper division students.
Briefly describe what a visual inspection of this output tells you
about the nature of the curves.
Part 2
Create a descriptives table to assess measures of central
tendency and dispersion using the following variables:
SPSS Variable
Definition
GPA
Previous grade point average
Quiz3
Quiz 3: number of correct answers
Create a descriptives table and paste it into your Word
document.
Under the table:
· Report the mean, standard deviation, skewness, and kurtosis
for GPA and quiz3.
22. · Briefly describe what skewness and kurtosis tell you about
these data with regard to normality.
Submit both sections of your assignment as an attached Word
document.
Competencies Measured
By successfully completing this assignment, you will
demonstrate your proficiency in the following course
competencies and assignment criteria:
· Competency 1: Analyze the computation, application,
strengths, and limitations of various statistical tests.
· Below the output, provide an accurate interpretation of
histograms for lower division and upper division.
· Below the output, report descriptive statistics and interpret
skew and kurtosis values.
· Competency 5: Apply a statistical program's procedure to data.
· Provide histograms for lower division and upper division.
· Provide a descriptive statistics table.
USE THE most recent version SPSS
Include four academic references above 2017
NO CONSIDERATION FOR PLAGIARISM
APA FORMAT AND INDEX CITATION
PLEASE WRITE FROM PUBLIC HEALTH PERSPECTIVE
Due 4/20/22 at 10am
MAKE SURE TO READ ALL INSTRUCTION VERY
CAREFULLY
OTHER RESOURCES
Field, A. (2018). Discovering statistics using IBM SPSS:
North American edition (5th ed.). Sage. Chapter 5 describes
how you can explore and learn about data with graphs.
step by step: A simple guide and reference (15th ed.).
Routledge.
23. MAKE SURE TO FOLLOW ALL Descriptive Statistics Scoring
Guide TO AGAIN ALL FULL POINTS
Criteria
Non-performance
Basic
Proficient
Distinguished
Provide histograms for lower division students and upper
division students.
25%
Does not provide histograms.
Multiple errors noted in the output.
One to two errors noted in the output.
Nearly flawless output.
Below the output, provide an accurate interpretation of
histograms for lower division students and upper divi sion
students.
25%
Does not provide an interpretation.
Multiple errors noted in the interpretation.
One to two errors noted in the interpretation.
Accurately interprets the histograms.
Provide a descriptive statistics table.
25%
Does not provide a descriptive statistics table.
Multiple errors noted in the output.
One to two errors noted in the output.
Nearly flawless output.
Below the output, report descriptive statistics and interpret
skew and kurtosis values.
25%
Does not provide descriptive statistics and/or interpret skew and
kurtosis values.
Multiple errors noted in the reporting of descriptive statistics
and/or interpretation of skew and kurtosis.
24. One to two errors noted in the reporting of descriptive statistics
and/or interpretation of skew and kurtosis.
Accurately reports descriptive statistics and accurately
interprets skew and kurtosis.
_____________________________________________________
_________________________Histograms and Descriptive
Statistics
_____________________________________________________
_________________________
Part 1: Histograms
Download grades.sav from Week 2 Assignment Instructions.
Open grades.sav in SPSS.
On the Graphs menu, scroll down to Legacy Dialogs and select
Histogram…
In the Histogram box, select final. Select the arrow to move
final to the Variable box.
Select Display normal curve.
Select lowup. Select the arrow to move lowup to the Rows box.
Select OK.
Copy and paste the histogram output into a new Word
document. Below the output, briefly describe what a visual
25. inspection of this output tells you about the nature of the
curves.
_____________________________________________________
_________________________
Part 2: Descriptive Statistics
On the Analyze menu, point to Descriptive Statistics and select
Descriptives…
In the Descriptives box, select gpa. Select the arrow to move
gpa to the Variables box.
Select quiz3. Select the arrow to move quiz3 to the Variables
box.
Select the Options… button.
Select Mean, Standard Deviation, Kurtosis, and Skewness.
Select Continue.
Select OK.
Copy and paste the descriptive statistics output into the Word
document. Under the table, report the mean, standard deviation,
skewness, and kurtosis of gpa and quiz3. Briefly describe what
skewness and kurtosis tell you about these data with regard to
normality.
26. Your homework should look like the next page. Upload for
grading.
7864 u02a1
Learner Name
Briefly describe what a visual inspection of this output tells you
about the nature of the curves.
Report the mean, standard deviation, skewness, and kurtosis for
GPA and quiz3. Briefly describe what skewness and kurtosis
tell you about these data with regard to normality.
SCREENSHOTS TAKEN FROM SPSS (PC) VERSION 28.
QUESTIONS? EMAIL: [email protected]