Day: July 6, 2020

HANDS-ON ANALYSIS 1

Churn Data Set

21. Using the churn data set, develop EDA which shows that the remaining numeric variables in the data set (apart from those covered in the text above) indicate no obvious association with the target variable.

Figure1

AccountLength

Figure2

DayCalls

Figure3

EveningCalls

Figure4

NightCalls

Figure5

InternationalCalls

Figure6

VoicemailMessages

From Figure 1 to 6, the normal curves on thehistogram diagrams indicate no obvious relationship amongst thecontinuous variables and the target variable, churn.

Adult Data Set

21. Which variables are categorical and which are continuous?

The categorical variables are workclass, education, maritalstatus,occupation, relationship, race, sex, nativecountry, income. Thecontinuous variables are age, demogweight, educationnum,capitalgain, capitalloss, hoursperweek.

21. Using software, construct a table of the first 10 records of the data set, in order to get a feel for the data.&nbsp

    Table 1 First Ten Entries Statistics
    		age	demogweight	education-num	capital-gain	capital-loss	hours-per-week
    N	Valid	10	10	10	10	10	10
    	Missing	0	0	0	0	0	0
    Mean		41.90	180924.40	11.00	2143.60	.00	36.40
    Median		40.50	184914.50	13.00	.00	.00	40.00
    Std. Deviation		8.825	94190.885	3.232	4520.900	.000	12.020
    Minimum		28	45781	5	0	0	13
    Maximum		53	338409	14	14084	0	50

22. Investigate whether we have any correlated variables.

Figure7

ScatterPlot

From Figure 7, it is evident that there aren’tany mutually related variables.

21. For each of the categorical variables, construct a bar chart of the variable, with an overlay of the target variable. Normalize if necessary. Discuss the relationship, if any, each of these variables has with the target variables. Which variables would you expect to make a significant appearance in any data mining classification model we work with?

Figure8

Workclass

Figure9

Education

Figure10

Maritalstatus

Figure11

Occupation

Figure12

Relationship

Figure13

Race

Figure14

Sex

Figure15

Nativecountry

From Figure 8 to 15 we can deduce that those under private workclasscategory have the largest share in both income groups. Those atHS-grad education earn the least. Those who’ve never been marriedearn the least while those married-civ-spouse earn the most.Prof-speciality and exec-managerial occupations earn the most.Husbands have a majority share in both income groups. White race hasthe largest share in both income groups. Also, men have the largestproportions in both income groups.

21. For each pair of categorical variables, construct a crosstabulation. Discuss your salient results.

Table2

Workclass Crosstab
				income				Total
				&lt=50K.		&gt50K.
workclass	?	Count		1251		148		1399
		% within income		6.6%		2.5%		5.6%
	Federal-gov	Count		467		283		750
		% within income		2.5%		4.7%		3.0%
	Local-gov	Count		1156		468		1624
		% within income		6.1%		7.8%		6.5%
	Never-worked	Count		5		0		5
		% within income		0.0%		0.0%		0.0%
	Private	Count		13624		3761		17385
		% within income		71.6%		62.9%		69.5%
	Self-emp-inc	Count		379		478		857
		% within income		2.0%		8.0%		3.4%
	Self-emp-not-inc	Count		1411		567		1978
		% within income		7.4%		9.5%		7.9%
	State-gov	Count		714		279		993
		% within income		3.8%		4.7%		4.0%
	Without-pay	Count		9		0		9
		% within income		0.0%		0.0%		0.0%
Total			Count		19016		5984		25000
			% within income		100.0%		100.0%		100.0%

Table3

Education Crosstab
				income				Total
				&lt=50K.		&gt50K.
education	10th		Count		666		55			721
			% within income		3.5%		0.9%			2.9%
	11th		Count		858		51			909
			% within income		4.5%		0.9%			3.6%
	12th		Count		299		24			323
			% within income		1.6%		0.4%			1.3%
	1st-4th		Count		115		5			120
			% within income		0.6%		0.1%			0.5%
	5th-6th		Count		233		11			244
			% within income		1.2%		0.2%			1.0%
	7th-8th		Count		460		31			491
			% within income		2.4%		0.5%			2.0%
	9th		Count		374		20			394
			% within income		2.0%		0.3%			1.6%
	Assoc-acdm		Count		599		202			801
			% within income		3.1%		3.4%			3.2%
	Assoc-voc		Count		786		273			1059
			% within income		4.1%		4.6%			4.2%
	Bachelors		Count		2428		1712			4140
			% within income		12.8%		28.6%			16.6%
	Doctorate		Count		84		231			315
			% within income		0.4%		3.9%			1.3%
	HS-grad		Count		6826		1294			8120
			% within income		35.9%		21.6%			32.5%
	Masters		Count		569		731			1300
			% within income		3.0%		12.2%			5.2%
	Preschool		Count		36		0			36
			% within income		0.2%		0.0%			0.1%
	Prof-school		Count		114		316			430
			% within income		0.6%		5.3%			1.7%
	Some-college		Count		4569		1028			5597
			% within income		24.0%		17.2%			22.4%
Total		Count		19016		5984			25000
		% within income		100.0%		100.0%			100.0%

Table 4 Marital-Status Crosstab
					income				Total
					&lt=50K.		&gt50K.
marital-status	Divorced	Count		3085		350		3435
		% within income		16.2%		5.8%		13.7%
	Married-AF-spouse	Count		9		7		16
		% within income		0.0%		0.1%		0.1%
	Married-civ-spouse	Count		6336		5105		11441
		% within income		33.3%		85.3%		45.8%
	Married-spouse-absent	Count		301		27		328
		% within income		1.6%		0.5%		1.3%
	Never-married	Count		7840		385		8225
		% within income		41.2%		6.4%		32.9%
	Separated	Count		736		50		786
		% within income		3.9%		0.8%		3.1%
	Widowed	Count		709		60		769
		% within income		3.7%		1.0%		3.1%
Total			Count		19016		5984		25000
			% within income		100.0%		100.0%		100.0%

Table5

Occupation Crosstab
				income				Total
				&lt=50K.		&gt50K.
occupation	?		Count		1256		148		1404
			% within income		6.6%		2.5%		5.6%
	Adm-clerical		Count		2582		393		2975
			% within income		13.6%		6.6%		11.9%
	Armed-Forces		Count		7		0		7
			% within income		0.0%		0.0%		0.0%
	Craft-repair		Count		2419		703		3122
			% within income		12.7%		11.7%		12.5%
	Exec-managerial		Count		1596		1488		3084
			% within income		8.4%		24.9%		12.3%
	Farming-fishing		Count		677		90		767
			% within income		3.6%		1.5%		3.1%
	Handlers-cleaners		Count		936		64		1000
			% within income		4.9%		1.1%		4.0%
	Machine-op-inspct		Count		1348		188		1536
			% within income		7.1%		3.1%		6.1%
	Other-service		Count		2443		112		2555
			% within income		12.8%		1.9%		10.2%
	Priv-house-serv		Count		121		0		121
			% within income		0.6%		0.0%		0.5%
	Prof-specialty		Count		1758		1422		3180
			% within income		9.2%		23.8%		12.7%
	Protective-serv		Count		343		160		503
			% within income		1.8%		2.7%		2.0%
	Sales		Count		2064		751		2815
			% within income		10.9%		12.6%		11.3%
	Tech-support		Count		488		215		703
			% within income		2.6%		3.6%		2.8%
	Transport-moving		Count		978		250		1228
			% within income		5.1%		4.2%		4.9%
Total		Count		19016		5984		25000
		% within income		100.0%		100.0%		100.0%

Table6

Relationship Crosstab
			income		Total
			&lt=50K.	&gt50K.
relationship	Husband	Count	5554	4510		10064
		% within income	29.2%	75.4%		40.3%
	Not-in-family	Count	5783	660		6443
		% within income	30.4%	11.0%		25.8%
	Other-relative	Count	701	28		729
		% within income	3.7%	0.5%		2.9%
	Own-child	Count	3856	55		3911
		% within income	20.3%	0.9%		15.6%
	Unmarried	Count	2481	159		2640
		% within income	13.0%	2.7%		10.6%
	Wife	Count	641	572		1213
		% within income	3.4%	9.6%		4.9%
Total		Count	19016	5984		25000
		% within income	100.0%	100.0%		100.0%

Table 7 Race Crosstab
			income			Total
			&lt=50K.	&gt50K.
race	Amer-Indian-Eskimo	Count	214	27	241
		% within income	1.1%	0.5%	1.0%
	Asian-Pac-Islander	Count	575	200	775
		% within income	3.0%	3.3%	3.1%
	Black	Count	2081	298	2379
		% within income	10.9%	5.0%	9.5%
	Other	Count	199	15	214
		% within income	1.0%	0.3%	0.9%
	White	Count	15947	5444	21391
		% within income	83.9%	91.0%	85.6%
Total		Count	19016	5984	25000
		% within income	100.0%	100.0%	100.0%

Table 8 Sex Crosstab
				income				Total
				&lt=50K.		&gt50K.
sex	Female	Count	7395		896		8291
		% within income	38.9%		15.0%		33.2%
	Male	Count	11621		5088		16709
		% within income	61.1%		85.0%		66.8%
Total		Count	19016		5984		25000
		% within income	100.0%		100.0%		100.0%

Table 9 Native-country Crosstab
					income				Total
					&lt=50K.		&gt50K.
native-country	?	Count		337		108		445
		% within income		1.8%		1.8%		1.8%
	Cambodia	Count		12		4		16
		% within income		0.1%		0.1%		0.1%
	Canada	Count		64		35		99
		% within income		0.3%		0.6%		0.4%
	China	Count		45		15		60
		% within income		0.2%		0.3%		0.2%
	Columbia	Count		43		2		45
		% within income		0.2%		0.0%		0.2%
	Cuba	Count		57		15		72
		% within income		0.3%		0.3%		0.3%
	Dominican-Republic	Count		52		2		54
		% within income		0.3%		0.0%		0.2%
	Ecuador	Count		17		2		19
		% within income		0.1%		0.0%		0.1%
	El-Salvador	Count		65		7		72
		% within income		0.3%		0.1%		0.3%
	England	Count		46		26		72
		% within income		0.2%		0.4%		0.3%
	France	Count		12		9		21
		% within income		0.1%		0.2%		0.1%
	Germany	Count		70		32		102
		% within income		0.4%		0.5%		0.4%
	Greece	Count		16		7		23
		% within income		0.1%		0.1%		0.1%
	Guatemala	Count		49		1		50
		% within income		0.3%		0.0%		0.2%
	Haiti	Count		35		3		38
		% within income		0.2%		0.1%		0.2%
	Holand-Netherlands	Count		1		0		1
		% within income		0.0%		0.0%		0.0%
	Honduras	Count		7		1		8
		% within income		0.0%		0.0%		0.0%
	Hong	Count		7		4		11
		% within income		0.0%		0.1%		0.0%
	Hungary	Count		9		1		10
		% within income		0.0%		0.0%		0.0%
	India	Count		42		25		67
		% within income		0.2%		0.4%		0.3%
	Iran	Count		22		13		35
		% within income		0.1%		0.2%		0.1%
	Ireland	Count		14		5		19
		% within income		0.1%		0.1%		0.1%
	Italy	Count		33		22		55
		% within income		0.2%		0.4%		0.2%
	Jamaica	Count		50		8		58
		% within income		0.3%		0.1%		0.2%
	Japan	Count		28		20		48
		% within income		0.1%		0.3%		0.2%
	Laos	Count		7		1		8
		% within income		0.0%		0.0%		0.0%
	Mexico	Count		463		25		488
		% within income		2.4%		0.4%		2.0%
	Nicaragua	Count		23		2		25
		% within income		0.1%		0.0%		0.1%
	Outlying-US(Guam-USVI-etc)	Count		8		0		8
		% within income		0.0%		0.0%		0.0%
	Peru	Count		22		1		23
		% within income		0.1%		0.0%		0.1%
	Philippines	Count		110		41		151
		% within income		0.6%		0.7%		0.6%
	Poland	Count		40		9		49
		% within income		0.2%		0.2%		0.2%
Portugal	Count		25		3		28
	% within income		0.1%		0.1%		0.1%
Puerto-Rico	Count		85		11		96
	% within income		0.4%		0.2%		0.4%
Scotland	Count		8		1		9
	% within income		0.0%		0.0%		0.0%
South	Count		49		15		64
	% within income		0.3%		0.3%		0.3%
Taiwan	Count		24		18		42
	% within income		0.1%		0.3%		0.2%
Thailand	Count		12		3		15
	% within income		0.1%		0.1%		0.1%
Trinadad&ampTobago	Count		11		1		12
	% within income		0.1%		0.0%		0.0%
United-States	Count		16941		5480		22421
	% within income		89.1%		91.6%		89.7%
Vietnam	Count		48		2		50
	% within income		0.3%		0.0%		0.2%
Yugoslavia	Count		7		4		11
	% within income		0.0%		0.1%		0.0%
Total			Count		19016		5984		25000
			% within income		100.0%		100.0%		100.0%

From Table 2 to Table 9, it is evident that thesalient results are similar to those displayed in the bar charts fromquestion 26.

21. (If your software supports this.) Construct a web graph of the categorical variables. Fine tune the graph so that interesting results emerge. Discuss your findings.

The IBM SPSS Statistics 23 does notsupport the construction of web graphs.

21. Report on whether anomalous fields exist in this data set, based on your EDA, which fields these are, and what we should do about it.

Table 10 workclass
			Frequency		Percent		Valid Percent		Cumulative Percent
Valid	?	1399		5.6		5.6		5.6
	Federal-gov	750		3.0		3.0		8.6
	Local-gov	1624		6.5		6.5		15.1
	Never-worked	5		.0		.0		15.1
	Private	17385		69.5		69.5		84.7
	Self-emp-inc	857		3.4		3.4		88.1
	Self-emp-not-inc	1978		7.9		7.9		96.0
	State-gov	993		4.0		4.0		100.0
	Without-pay	9		.0		.0		100.0
	Total	25000		100.0		100.0

Table 11 race
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Amer-Indian-Eskimo	241	1.0	1.0	1.0
	Asian-Pac-Islander	775	3.1	3.1	4.1
	Black	2379	9.5	9.5	13.6
	Other	214	.9	.9	14.4
	White	21391	85.6	85.6	100.0
	Total	25000	100.0	100.0

Table 12 sex
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Female	8291	33.2	33.2	33.2
	Male	16709	66.8	66.8	100.0
	Total	25000	100.0	100.0

Table 13 native-country
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	?	445	1.8	1.8	1.8
	Cambodia	16	.1	.1	1.8
	Canada	99	.4	.4	2.2
	China	60	.2	.2	2.5
	Columbia	45	.2	.2	2.7
	Cuba	72	.3	.3	2.9
	Dominican-Republic	54	.2	.2	3.2
	Ecuador	19	.1	.1	3.2
	El-Salvador	72	.3	.3	3.5
	England	72	.3	.3	3.8
	France	21	.1	.1	3.9
	Germany	102	.4	.4	4.3
	Greece	23	.1	.1	4.4
	Guatemala	50	.2	.2	4.6
	Haiti	38	.2	.2	4.8
	Holand-Netherlands	1	.0	.0	4.8
	Honduras	8	.0	.0	4.8
	Hong	11	.0	.0	4.8
	Hungary	10	.0	.0	4.9
	India	67	.3	.3	5.1
	Iran	35	.1	.1	5.3
	Ireland	19	.1	.1	5.4
	Italy	55	.2	.2	5.6
	Jamaica	58	.2	.2	5.8
	Japan	48	.2	.2	6.0
	Laos	8	.0	.0	6.0
	Mexico	488	2.0	2.0	8.0
	Nicaragua	25	.1	.1	8.1
	Outlying-US(Guam-USVI-etc)	8	.0	.0	8.1
	Peru	23	.1	.1	8.2
	Philippines	151	.6	.6	8.8
	Poland	49	.2	.2	9.0
	Portugal	28	.1	.1	9.1
	Puerto-Rico	96	.4	.4	9.5
	Scotland	9	.0	.0	9.5
	South	64	.3	.3	9.8
	Taiwan	42	.2	.2	10.0
	Thailand	15	.1	.1	10.0
	Trinadad&ampTobago	12	.0	.0	10.1
	United-States	22421	89.7	89.7	99.8
	Vietnam	50	.2	.2	100.0
	Yugoslavia	11	.0	.0	100.0
	Total	25000	100.0	100.0

Table 14 income
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	&lt=50K.	19016	76.1	76.1	76.1
	&gt50K.	5984	23.9	23.9	100.0
	Total	25000	100.0	100.0

Figure16

Figure17

Figure18

The anomalous fields are income-gain andincome-loss. There is no evident relationship between the two fieldswith income. There is no pattern in the how the income-gain andincome-loss affect the target variable.

21. Report the mean, median, minimum, maximum, and standard deviation for each of the numerical variables.

Table 15 Statistics
		age	demogweight	education-num	capital-gain	capital-loss	hours-per-week
N	Valid	25000	25000	25000	25000	25000	25000
	Missing	0	0	0	0	0	0
Mean		38.61	189741.84	10.08	1088.58	86.50	40.41
Median		37.00	178353.00	10.00	.00	.00	40.00
Std. Deviation		13.688	105294.740	2.557	7486.621	401.254	12.299
Minimum		17	12285	1	0	0	1
Maximum		90	1484705	16	99999	4356	99

The mean, median, standard deviation, minimum andmaximum for age, demogweight, education-num, capital-gain,capital-loss, and hours-per-week are shown in Table 15.

21. Construct a histogram of each numerical variables, with an overlay of the target variable income. Normalize if necessary. Discuss the relationship, if any, each of these variables has with the target variables.

Figure19

Figure20

Figure21

Figure 22

Figure23

Figure24

From Figure 19 to 24, we can deduce that theparticipants either earn &lt=50K or &gt50K at the peak of 40 years,at around 200,000 demogweight, and at education-num of around 10.

21. For each pair of numerical variables, construct a scatter plot of the variables. Discuss your salient results.

Figure25

ScatterPlot

There does not seem to be any relationship among age, demogweight,capital-gain, capital-loss, and hours-per-week.

21. Based on your EDA so far, identify interesting sub-groups of records within the data set that would be worth further investigation.

From the EDA, private workclass,white race, male sex, and United States native-country sub groups areworth undergoing more investigation.

21. Apply binning to one of the numerical variables. Do it in such a way as to maximize the effect of the classes thus created (following the suggestions in the text). Now do it in such a way as to minimize the effect of the classes, so that the difference between the classes is diminished. Comment.

Figure26 No Binning

Figure27 Binning – Maximize Effect

Figure28 Binning – Minimize Effect

From Figure 26 to 28, performing binning ondemogweight to maximize the effect helps identify the slow reductionpattern as we move from left to right while when binning to minimizethe effect, we do not come upon a slow reduction pattern as we movefrom left to right.

21. Refer to the previous exercise. Apply the other two binning methods (equal width, and equal number of records) to this same variable. Compare the results and discuss the differences. Which method do you prefer?

After comparing Figure 29 and 30, I prefer theequal width binning method since it violates less errors although thehistograms appear to be almost similar.

Figure29 Binning – Equal Number of Records

Figure30 Binning – Equal Width

21. Summarize your salient EDA findings from the above exercises. Just as if you were writing a report.

The EDA analyzed the variables andidentified anomalous variable income whereby &lt=50K represents twopossibilities. Also, histograms were drawn from the data,distribution of categorical variables, and interrelationship betweenthe variables were explored. It was evident that the variablescapital-gain and capital-loss had no substantial relationship withthe target variable.

ComputerTechnologies

ComputerTechnologies

Informationtechnology is a vital department for an organisation hence, it isimportant for small business to get it right during the developmentprocess. The bigger picture is to use information technology in thebusiness to strategically take advantage of it and to make the staffmore productive and smarter. By doing so, business will gain anadvantage over its competitors, which is the goal of everyentrepreneur. With a budget of twenty five thousand dollars,MilleniAds needs to come up with a well-calculated budget that willensure all the IT necessities are met at a low cost.

Inorder to meet the hardware requirements, MilleniAds can seek theservices of ITC organisation, which is an IT firm dealing with theselling and installation of computer hardware and software at a lowcost. The company has only ten employees who will require tendesktops with specifications as follows: RAM – 4GB, Processor (CPU) -Intel i3, Hard Drive Disk (HDD) – 500GB, Operating System – Windows10 that will cost Investment (excluding VAT) at a cost of $4930.Additionally, two employees will need tablets to access companyinformation at a cost of $199 dollars each, which boats of 9.6&quotdisplay, 16GB storage capacity, and Wi-Fi among others. To set up anetwork, a wired router will be needed at a cost of $283 and anaccess point at a cost of $109. In terms of router choice, departmentcan either opt for the stated wired router or a wireless router, butthe best alternative is the former since it is well suited for a anenvironment the uses desktops. The best network for MilleniAdsCompany will be a peer-to-peer network since the numbers of employeesare few like the one shown in the diagram below:

For mass storage purposes, the company can use a QNAP that is attached to the network, thus facilitating safe storage of information, the device contains two hard disks and also shares data across the desktop. The data storage device is less expensive as compared to traditional ones as it goes for only $600. Other network devices will also be needed that include a universal printer and a scanner at a cost of $236 [ CITATION ITC16 l 2057 ]. In terms of software, the company will need to purchase through downloads Microsoft office at a cost of $199.99 each. A total of around twelve will cost $2388. A customer relationship management software will also be required by the organisation since the management will need to organise their client relationship at every stage and it will cost an initial price of $177.99 in addition to a monthly cost of $5. Security softwares that will be installed on the desktops, preferably Kaspersky, will also be required at a cost of $400 for twelve pieces. The labour cost for the whole process is estimated to be about $1000 dollars. XTen Desktops	$493 each	$4,930
two tablets	199 each	$398
router		$283
access points		$109
QNAP		$600
printer and scanner		$236
Microsoft office	$199.99	$2,388
CRM		$237.99
Kaspersky		$400
labor		$1,000
network cable		$1,200
		$11,782

Theabove budget shows the resources that will be needed by the companyand the functional strength of the devices is that they are durable.The choice for desktops, printer, scanners, and router is the bestsince they are less costly and are durable. However, the hard disksize of the desktop is a limitation in addition to the choice ofnetwork since it will not hold when the firm is expanding. In termsof maintainability, the devices can easily be maintained at a lowcost since the organisation will only need to carry out periodicchecks instead of hiring a fulltime IT expert.

Inconclusion, the company will need the resources mentioned in order toset up an information technology department inclusive of afunctioning network. With the budget, the organisation will be ableto save more than ten thousand dollars that can be channelled toother sections of the organisation. In the case that the firm intendsto expand, the peer-to-peer network will make it easy for additionalnodes to be added.

References

ITC. (2016). Computer Hardware and Software Sales and Installation . Retrieved from ITC: http://www.itcweb.co.uk/products/

Valuesand Ethics in Social Work

ExecutiveSummary

Thesocial work profession has become one of the most sought-aftercareers in the world today, and this is because of the role thatsocial workers play in promoting social justice and giving meaning tothe human life. Social workers are found in virtually all settings,including hospitals and correctional facilities. These professionalsusually work with disadvantaged persons and people grappling withissues such as substance addiction and domestic violence. In order toequip social workers with the skills and competencies needed toexecute this important duty, a set of standards and values has beencreated, the primary purpose being to outline the ethical principlesthat social workers should abide by. Clearly captured in a documentknown as the National Association of Social Workers Code of Ethics,the core values that guide social workers include competence respectfor human dignity and the value of interpersonal relationshipssocial justice service and integrity. However, social workersoccasionally experience conflicts between these core values and theirpersonal values. For example, individuals coming from conservativebackgrounds may initially encounter challenges when dealing withclients with rather unconventional beliefs, such as same-sexmarriages. Apart from this, ethical principles stipulated within theCode, such as confidentiality, privacy, informed consent, andself-determination usually create ethical challenges for socialworkers. This is usually experienced by social workers specializingin the field of substance abuse and addictions, where it is foundthat the reluctance of victims to disclose their problem may compelpractitioners to violate the right to self-determination.Nonetheless, social workers should strive to abide by the core valuesin order to ensure that ethical practice is upheld.

Valuesand Ethics in Social Work

Socialwork Ethics

Socialwork is one of the noblest professions today, particularlyconsidering that the primary responsibility of social workers is tohelp in making people`s lives better by acting as advocates for thedisadvantaged (Berg-Werger, 2013). Apart from this, the uniqueness ofthe profession lies in its scope of practice, which is very broad, aswell as the strong values on which it is entrenched. Moreimportantly, social workers are one among the persons that are highlycommitted to economic as well as social justice (Berg-Weger, 2013).These are the same features that make social work a sensitive,demanding profession. To be precise, social workers are prone tofacing legal charges on account of having violated ethical standards.

Thispaper explores the ethical frameworks, principles, and dilemmasinvolved in social work.

Ethicalframeworks for social work practice

Oneof the key frameworks upon which the social work profession isfounded is the Code of Ethics created by the National Association ofSocial Workers (NASW). In brief, the NASW Code recognizes socialworkers as existing to improve the well-being of human beings byempowering the poor, oppressed, and the vulnerable. The valuesoutlined in the Code include service, competence, valuing humanrelationships, social justice, integrity, and upholding everyperson`s dignity. A well-defined ethical principle supports each ofthese core values. For instance, the Code stipulates that socialworkers can only provide excellent service if they focus on the goalof helping needy persons to overcome their social problems.Similarly, the Code stipulates that social workers must exercisecompetence by continually upgrading their professional knowledge. TheNASW Code also outlines the ethical responsibilities of social toclients, colleagues, the society, and the profession (NationalAssociation of Social Workers, 2017).

Socialworkers are also bound by the 1996 Health Insurance Portability andAccountability Act (HIPAA), whose emphasis is on privacy andconfidentiality of client information, as well as social justice.Precisely, the Act recommends the use of electronic systems in datamanagement, besides prohibiting denial of service to needy persons(Krager &amp Krager, 2016). Like NASW, the Council on Social WorkEducation believes that social workers exist to promote individual aswell as community well-being. However, the central view held by theCouncil is that this mandate can only be exercised to the best extentpossible if social workers are adequately trained and educated. Thisis why the Council has established policy and accreditation standardsto ensure academic excellence for students pursuing the social workprofession. The standards emphasize a shift from content-basedcurricula to those focused on learning outcomes. To be specific, themodel favors the use of assessments to ensure that students canimplement their knowledge in a practical situation (Council on SocialWork Education, 2015).

Ethicalissues facing social workers today

Accordingto Reamer (2013), social workers dealing with small groups andindividuals often face the dilemma of maintaining confidentialitywhilst at the same honoring the need to disclose vital information tothe client’s family members. For example, it would be disastrous tomaintain confidentiality about a client who has suicidal thoughts, asthis may cause harm to the client and his/her relatives.Additionally, inasmuch as social workers play a vital role in helpingpersons struggling with difficult life situations to overcome suchsituations and maximize the quality of their lives, their professionis one of the most demanding, particularly in view of ethicalstandards that guide practice. It is worth noting that the autonomyof social workers is somewhat constrained, as suggested by theobservation that social workers must accept the way their clientsdefine life issues (Zastrow, 2013).

Thismeans that even though social workers are charged with aresponsibility of imparting vital skills in their clients, it isunethical for a social worker to try instructing a client on what heor she in a specific situation. Such a statement implies that socialworkers play a subordinate role in facilitating and guiding, and thiscould be challenging to practitioners because it implies that theirpower to make decisions is limited. Still, on the subject ofdecision-making, it should be noted that even though the NASW Code ofEthics is supposed to provide direction to social workers whendealing with elderly clients, the direction provided by the Code isnot definitive. For example, the Code does not provide a clearposition regarding the right of dying, and whether or not it isethical for practitioners to take part in assisted suicide. Becauseof this lack of definitive guidelines, social workers are oftenexpected to apply professional judgment and conduct a sober, criticalevaluation of the pros and cons of various options before coming to adecision (Green &amp Simon, 2012). Specifically, social workers mustconsider the core values guiding their work, hypothesize the outcomesof various decisions, and liaise with colleagues as well assupervisors in order to come up with the choice that is most ethical.The above example demonstrates that the Code of Ethics does notprovide a comprehensive, clear direction on the conduct of socialworkers when faced with difficult situations. For this reason, itmight rightly be said that the code of ethics guiding social work is,in itself, a source of an ethical dilemma for social workers.

Additionally,in consideration of the economic hardships facing many societiestoday, social workers often find themselves working with diminishedfinancial resources. This arises from government cuts on publicspending, to which social work belongs. The situation is worsened bythe fact that in most cases, the people who seek assistance fromsocial workers are those from the low-income category (Cowden &ampPullen-Sansfacon, 2014). The implication of this is that socialworkers are likely to lose the morale to provide excellent servicesimply because they are not being with adequate financial resources.As Cowden and Pulen-Sansfacon (2014) put it, the quality of servicerendered in times of economic hardship is likely to be compromised,thus making it difficult for practitioners to abide by the ethicalprinciple of subordinating self-interest to service to the society.Moreover, this may encourage injustice and bias in the way socialworkers provide their service (Reamer, 2013).

Socialwork and substance abuse: ethical issues

Althoughthe ethical challenges outlined in the preceding section generallyapply to the social work profession, some challenges uniquely applyto certain fields of practice. For example, social workers whospecialize in offering help to victims of substance abuse andaddictions are not necessarily confronted by the same challenges asthose dealing in corrections and criminal justice. For social workersspecializing in substance abuse, one of the ethical challenges thatabound relates to the issue of self-determination and consent. Asstipulated in the NASW Code of Ethics, it is wrong for a socialworker to obtain a client’s private information without his or herconsent (National Association of Social Workers, 2017). While this isunderstandable, it is important to bear in mind that some people areeither reluctant or shy of disclosing addiction to substances(Miller, 2017).

Ina scenario where a social worker is dealing with a client who is shyof admitting that he or she has addiction problems, it is highlylikely that an ethical dilemma will arise. Specifically, theprofessional is expected to exercise professionalism and competenceby using appropriate strategies to identify the issues underlying theproblem. In most cases, this involves a detailed assessment procedurein which the social worker assesses signs of substance addiction inthe client, regardless of whether or not the client admits havingsuch a problem (Miller, 2017). By virtue of the fact that the socialworker may not wait for the client to self-report the problem, itmight be said that the practitioner violated the principle ofinformed consent in soliciting information regarding the problem.

Accordingto the National Association of Social Workers (2017), one of the coreethical responsibilities of social workers to clients is to upholdthe client’s right to self-determination. In simple terms, thismeans that it is unethical for the professional to impose a treatmentprogram on a client. In other words, the social worker should explainall available options together with their merits and demerits to theclient, leaving the client to decide on the one he or she wants.However, social workers may find it hard to provide such freedom toclients with severe addiction problems. Precisely, social workers maybe unable to resist the urge to refer the client to a rehabilitationcenter. Although such a decision may appear helpful andwell-intentioned, the practitioner may be indicted for violating theclient’s self-determination rights.

Still,on the ethical standards that should be followed by social workers,as contained within the NASW Code of Ethics, the principle ofconfidentiality may create ethical challenges in a case involvingsubstance addiction. Essentially, confidentiality means that anysensitive information pertaining to the client must not be disclosedto a third party, unless with the client`s permission. However,supposing that the client in question is a minor whose parents havesought the assistance of a social worker to the client havingdeveloped behavioral problems, it is not realistic to expect thesocial worker to withhold details about the client’s addiction tohis or her parents. Similarly, it is assumed that spouses have aright to know about each other’s health status, and this may make asocial worker liable for violating the principle of confidentiality.

Corevalues of the social work profession

Asoutlined in the NASW Code of Ethics, the social work profession isunderpinned by six core values: integrity, social justice, a person`sdignity, competence, service, and the fact that human relationshipsare important (Segal, Gerdes &amp Steiner, 2013). In brief, serviceimplies that social workers must lay their personal interests asidewhen executing their duty and that they must utilize their skillswhilst also volunteering when necessary in order to deal with socialproblems. Concerning social justice, social workers are expected toensure that all clients obtain necessary resources and information toovercome the problems of poverty and discrimination (Ambrosino,Hefferman, Shuttlesworth &amp Ambrosino, 2015).

Withregard to dignity, social workers ought to treat all clients withcare and respect, regardless of their ethnicity. This is onlypossible where social workers engage their clients as partners, hencedemonstrating the understanding of the value of relationships betweenpeople. Integrity is measured by the degree of trustworthinessdemonstrated by a social worker, whereas competence refers to acontinuous struggle to improve one’s professional knowledge(Ambrosino et al., 2015).

Althoughall the above values appear sensible, especially in light of thenature of work that social workers do, it would be pretentious toignore the conflicts that may arise between the above values and thepractitioner’s personal values. Personally, I find the principlesof service and dignity quite hard to pursue. Specifically, I believethat it is wrong for two people of a similar sex to love one another.Accordingly, it would be hard for me to provide unbiased attention toa client with a homosexual orientation. Nevertheless, I plan to refersuch a client to a colleague who is more comfortable handling it, butin the meantime, I would enroll in a counseling class so that I learnhow to accommodate other people’s views.

Conclusion

Undoubtedly,social workers play an invaluable role in the society they promotesocial justice and strive to maximize the well-being of people. Inorder to be capable of executing this crucial role effectively, a setof standards and values have been developed to guide social work.These values and standards are contained in the National Associationof Social Work, and they include integrity, competence, respect forhuman dignity and relationships, social justice, and service. Insupport of the value of competence to social work, the Council onSocial Work Education has formulation standards that are designed toensure that social workers have sufficient theoretical and practicalexperience and knowledge. With all these guidelines, however, socialworkers frequently encounter ethical challenges, mostly related toconfidentiality, privacy, and self-determination. As such, it emergesthat social work is a vital, yet highly demanding and trickyprofession.

References

Ambrosino,R., Heffernan, J., Shuttlesworth, G. &amp Ambrosino, R. (2015).EmpowermentSeries: Social Work and Social Welfare.Cengage Learning.

Berg-Werger,M. (2013). Socialwork and social welfare: an invitation.Routledge.

Councilon Social Work Education. (2015). Educationalpolicy and accreditation standards.Retrieved from &lt&lt http://www.cswe.org/File.aspx?id=81660&gt&gton 18^thJanuary 2017.

Cowden,S. &amp Pullen-Sansfacon, A. (2014). Theethical foundations of social work.Routledge.

Green,W. &amp Simon, B. L. (2012). TheColumbia guide to social work writing.New York: Columbia University Press.

Krager,D. &amp Krager, C. (2016). HIPAAfor health care professionals.Cengage Learning.

Miller,A. (2017). Therole of social workers in the fight against drug abuse.Retrieved from &lt&lthttp://work.chron.com/role-social-workers-fight-against-drug-abuse-11513.html&gt&gton 18^thJanuary 2017.

NationalAssociation of Social Workers. (2017). Codeof Ethics of the National Association of Social Workers.Available at &lt&lthttps://www.socialworkers.org/pubs/code/code.asp&gt&gt

Reamer,F. G. (2013). Socialwork values and ethics.New York: Columbia University Press.

Segal,E. A., Gerdes, K. E. &amp Steiner, S. (2013). Anintroduction to the profession of social work: Becoming a changeagent.Belmont, Calif: Brooks/Cole, Cengage Learning.

Zastrow,C. (2013). Brooks/ColeEmpowerment Series: Introduction to Social Work and Social Welfare.Cengage Learning.