Research Report: Numeracy and ICT Skills in HIV Data Analysis
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AI Summary
This report explores the application of Information and Communication Technologies (ICT) and numeracy skills in analyzing HIV data in the UK from 2014 to 2019. The report begins with an introduction to ICT techniques, their relevance, and their role in collecting and representing data effectively. The main body details various ICT techniques, including informative and constructive approaches, and explains statistical methods such as mean, median, mode, and standard deviation. These techniques are used to analyze data related to HIV diagnoses, age at diagnosis, and probable exposure categories. The results, presented in a systematic format, include calculations of mean, standard deviation, median, and mode for different datasets. The report concludes by summarizing the findings and emphasizing the importance of ICT and numeracy skills in data analysis. The report is structured to provide insights into the use of these skills in public health research, offering valuable information for researchers and organizations involved in health data analysis. The data is presented with columns for different years, allowing for comparative analysis and highlighting trends over time.
USING NUMERACY AND ICT SKILLS IN
RESEARCH
RESEARCH
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Table of Contents
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
About ICT techniques..................................................................................................................3
Techniques used within ICT........................................................................................................4
Result of using ICT technique in systematic format....................................................................5
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
About ICT techniques..................................................................................................................3
Techniques used within ICT........................................................................................................4
Result of using ICT technique in systematic format....................................................................5
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14
INTRODUCTION
Information and communication technologies are includes those tools which help in
collecting data in effective manner by using different advance technique tool. This report is
formulated to determine use of ICT technique in order to measure HIV patients data of UK for
from 2014 to 2019. This report includes, relevance of ICT techniques, different types of theses
technique as well as use of mean, mode, median and standard deviation to measure data.
MAIN BODY
About ICT techniques
The term ICT refers as information & communication technology theses techniques are
used for the purpose of collection and representation of business data in effective and systematic
manner. With the use of tools and technique of this approach organization or researcher able to
collect reliable and accurate business information as well as theses are useful to collect and
represent primary and secondary data in effective manner.
On the bias of using ICT techniques manager able to represent relevant business
information and these data used for measuring purpose also. Data which can be collect by using
ICT technique it is known as secondary business data. By collection of this data researcher able
to find relevant information regarding particular source and on the basis of that organization able
to take relevant business decision (Falck, Heimisch-Roecker and Wiederhold, 2020).
Theses data useful in find out relevant business information as well as perspective of
target market customer and relevance of customer can be determine by using different
information & communication technique. Following technique are used by researchers in order
to gain relevant knowledge regarding Constructive techniques-ding their researching project,
these are define below:
informative techniques: There are different types of technique which is used in order to collect
business data at the time of research. Tools of informative technique are useful in order to find
different types of information With the use of internet, communication network which includes,
computer, social media, laptop, all these source are helpful in represent and or collect
information in easy manner (Kahan and et.al., 2017).
With the development of internet technology , communication regarding with particular
information become easier as well as theses technique or tools also relevant in order to find out
Information and communication technologies are includes those tools which help in
collecting data in effective manner by using different advance technique tool. This report is
formulated to determine use of ICT technique in order to measure HIV patients data of UK for
from 2014 to 2019. This report includes, relevance of ICT techniques, different types of theses
technique as well as use of mean, mode, median and standard deviation to measure data.
MAIN BODY
About ICT techniques
The term ICT refers as information & communication technology theses techniques are
used for the purpose of collection and representation of business data in effective and systematic
manner. With the use of tools and technique of this approach organization or researcher able to
collect reliable and accurate business information as well as theses are useful to collect and
represent primary and secondary data in effective manner.
On the bias of using ICT techniques manager able to represent relevant business
information and these data used for measuring purpose also. Data which can be collect by using
ICT technique it is known as secondary business data. By collection of this data researcher able
to find relevant information regarding particular source and on the basis of that organization able
to take relevant business decision (Falck, Heimisch-Roecker and Wiederhold, 2020).
Theses data useful in find out relevant business information as well as perspective of
target market customer and relevance of customer can be determine by using different
information & communication technique. Following technique are used by researchers in order
to gain relevant knowledge regarding Constructive techniques-ding their researching project,
these are define below:
informative techniques: There are different types of technique which is used in order to collect
business data at the time of research. Tools of informative technique are useful in order to find
different types of information With the use of internet, communication network which includes,
computer, social media, laptop, all these source are helpful in represent and or collect
information in easy manner (Kahan and et.al., 2017).
With the development of internet technology , communication regarding with particular
information become easier as well as theses technique or tools also relevant in order to find out
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essential business information and help in collecting secondary data regarding with particular
business research object. Researcher can be found relevant information and source of data they
collect from journals, questioners, by conducting survey all these useful in providing essential
information.
Constructive techniques- Theses are types of technique which researcher used for the
purpose of collecting and storing relevant data. Power point, MS excel, MS word are some of
the example of constructive technique. The main purpose of applying this technique is to collect
and summarised large data in systematic manner, which help to prove base for long period of
time to collection of business data (Windisch, 2016).
These data are useful and work as source of organization and most of multinational
corporation apply and use tools of ICT in order to manager their data for the purpose of saving
time and money. By implementation of these technique manager able to represent and
interpretation which useful in decision making purpose. Theses data useful in find out solution of
different types of problems.
With the changes of environment, case related with HIV in England has been raise it is consider
as one of the major issue from which people suffer . Many of researcher use or implement this
technique in order to collect data and present their data in effective manner. With the use of
these techniques essential information regarding HIV patients in London from 2014 to 2019 can
be recognized (Lane and Conlon, 2016).
Techniques used within ICT.
There are different types of technique has been used in order to collect and present data
for research project. Following are the techniques which help in determine accurate and relevant
information regarding HIV patients of UK , these are define below:
Mean: This is consider as one of the most useful method or technique which represent
the overall data series. Mean is define as value which represent overall series or data. It is
consider as the average of specific data series. By calculation of mean value , researcher able to
recognized at the rate which affect person and number of people due to this problem as well as
comparison on the basis of gender regarding with how many female or male had been died
within specific time period.
business research object. Researcher can be found relevant information and source of data they
collect from journals, questioners, by conducting survey all these useful in providing essential
information.
Constructive techniques- Theses are types of technique which researcher used for the
purpose of collecting and storing relevant data. Power point, MS excel, MS word are some of
the example of constructive technique. The main purpose of applying this technique is to collect
and summarised large data in systematic manner, which help to prove base for long period of
time to collection of business data (Windisch, 2016).
These data are useful and work as source of organization and most of multinational
corporation apply and use tools of ICT in order to manager their data for the purpose of saving
time and money. By implementation of these technique manager able to represent and
interpretation which useful in decision making purpose. Theses data useful in find out solution of
different types of problems.
With the changes of environment, case related with HIV in England has been raise it is consider
as one of the major issue from which people suffer . Many of researcher use or implement this
technique in order to collect data and present their data in effective manner. With the use of
these techniques essential information regarding HIV patients in London from 2014 to 2019 can
be recognized (Lane and Conlon, 2016).
Techniques used within ICT.
There are different types of technique has been used in order to collect and present data
for research project. Following are the techniques which help in determine accurate and relevant
information regarding HIV patients of UK , these are define below:
Mean: This is consider as one of the most useful method or technique which represent
the overall data series. Mean is define as value which represent overall series or data. It is
consider as the average of specific data series. By calculation of mean value , researcher able to
recognized at the rate which affect person and number of people due to this problem as well as
comparison on the basis of gender regarding with how many female or male had been died
within specific time period.
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There are different types of method which help in calculation of value of mean. It is
calculated on the basis of sum of value as well as number of observation define in the research
project.
Median: It is consider as technique or tool of central tendency which define middle
value of definite series. On the basis of calculation of median value research represent value or
data which useful in further process of decision making.
Mode: This is define as the tool which used to represent value which is frequency arrive
in specific data series. This technique useful in find out revenue of particular series. On the basis
of that research formulate and recommand suggestion after analysing and evaluating data series.
Standard deviation: This tool of central tendency is calculate vale of difference between mean
value with particular variable of data series (Pinto and et.al., 2016).
It is calculated by identifying square root of data series. It is useful in also determining
variances which represent or define relation and variation between different data series. On the
basis of calculating value of these measuring value of these researcher able to put value if
difference between standard deviation and mean is positive then it added up and if values
negative then it deduct and it represent negative relation between different variables (Sgobbi,
2018).
Result of using ICT technique in systematic format
Data related with HIV diagnoses in between male and female and their death ratio.
4,330 4,257 3,660 3,140 3,047 2,726
1,457 1,369 1,146 1,099 1,083 1,046
5,787 5,626 4,806 4,242 4,133 3,772
162 211 188 163 152 164
71 78 58 59 54 55
233 289 246 222 206 219
413 342 221 229 270 340
132 111 48 53 94 87
545 453 269 282 364 427
calculated on the basis of sum of value as well as number of observation define in the research
project.
Median: It is consider as technique or tool of central tendency which define middle
value of definite series. On the basis of calculation of median value research represent value or
data which useful in further process of decision making.
Mode: This is define as the tool which used to represent value which is frequency arrive
in specific data series. This technique useful in find out revenue of particular series. On the basis
of that research formulate and recommand suggestion after analysing and evaluating data series.
Standard deviation: This tool of central tendency is calculate vale of difference between mean
value with particular variable of data series (Pinto and et.al., 2016).
It is calculated by identifying square root of data series. It is useful in also determining
variances which represent or define relation and variation between different data series. On the
basis of calculating value of these measuring value of these researcher able to put value if
difference between standard deviation and mean is positive then it added up and if values
negative then it deduct and it represent negative relation between different variables (Sgobbi,
2018).
Result of using ICT technique in systematic format
Data related with HIV diagnoses in between male and female and their death ratio.
4,330 4,257 3,660 3,140 3,047 2,726
1,457 1,369 1,146 1,099 1,083 1,046
5,787 5,626 4,806 4,242 4,133 3,772
162 211 188 163 152 164
71 78 58 59 54 55
233 289 246 222 206 219
413 342 221 229 270 340
132 111 48 53 94 87
545 453 269 282 364 427
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 1458.8
88888
8889
Mean 1415.1
11111
1111
Mean 1182.4
44444
4445
Mean 1054.3
33333
3333
Mean 1044.7
77777
7778
Mean 981.77
77777
778
Standa
rd
Error
704.90
83755
363
Standa
rd
Error
688.13
20416
825
Standa
rd
Error
594.48
51673
486
Standa
rd
Error
517.35
84615
89
Standa
rd
Error
499.96
42981
081
Standa
rd
Error
448.16
86121
743
Media
n
413 Media
n
342 Media
n
246 Media
n
229 Media
n
270 Media
n
340
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
2114.7
25126
6089
Standa
rd
Deviat
ion
2064.3
96125
0475
Standa
rd
Deviat
ion
1783.4
55502
0459
Standa
rd
Deviat
ion
1552.0
75384
7671
Standa
rd
Deviat
ion
1499.8
92894
3243
Standa
rd
Deviat
ion
1344.5
05836
523
Sampl
e
Varian
ce
44720
62.361
11111
Sampl
e
Varian
ce
42617
31.361
11111
Sampl
e
Varian
ce
31807
13.527
77778
Sampl
e
Varian
ce
24089
38
Sampl
e
Varian
ce
22496
78.694
44444
Sampl
e
Varian
ce
18076
95.944
44444
Kurtos
is
1.2232
02424
7
Kurtos
is
1.2041
32305
6
Kurtos
is
1.1641
43790
3
Kurtos
is
1.2487
31613
Kurtos
is
1.2775
44487
4
Kurtos
is
1.3546
46962
5
Skewn
ess
1.5940
85223
Skewn
ess
1.6022
09892
5
Skewn
ess
1.5992
63753
Skewn
ess
1.5975
60107
1
Skewn
ess
1.5986
80989
5
Skewn
ess
1.5930
44097
2
Range 5716 Range 5548 Range 4758 Range 4189 Range 4079 Range 3717
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 1458.8
88888
8889
Mean 1415.1
11111
1111
Mean 1182.4
44444
4445
Mean 1054.3
33333
3333
Mean 1044.7
77777
7778
Mean 981.77
77777
778
Standa
rd
Error
704.90
83755
363
Standa
rd
Error
688.13
20416
825
Standa
rd
Error
594.48
51673
486
Standa
rd
Error
517.35
84615
89
Standa
rd
Error
499.96
42981
081
Standa
rd
Error
448.16
86121
743
Media
n
413 Media
n
342 Media
n
246 Media
n
229 Media
n
270 Media
n
340
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
2114.7
25126
6089
Standa
rd
Deviat
ion
2064.3
96125
0475
Standa
rd
Deviat
ion
1783.4
55502
0459
Standa
rd
Deviat
ion
1552.0
75384
7671
Standa
rd
Deviat
ion
1499.8
92894
3243
Standa
rd
Deviat
ion
1344.5
05836
523
Sampl
e
Varian
ce
44720
62.361
11111
Sampl
e
Varian
ce
42617
31.361
11111
Sampl
e
Varian
ce
31807
13.527
77778
Sampl
e
Varian
ce
24089
38
Sampl
e
Varian
ce
22496
78.694
44444
Sampl
e
Varian
ce
18076
95.944
44444
Kurtos
is
1.2232
02424
7
Kurtos
is
1.2041
32305
6
Kurtos
is
1.1641
43790
3
Kurtos
is
1.2487
31613
Kurtos
is
1.2775
44487
4
Kurtos
is
1.3546
46962
5
Skewn
ess
1.5940
85223
Skewn
ess
1.6022
09892
5
Skewn
ess
1.5992
63753
Skewn
ess
1.5975
60107
1
Skewn
ess
1.5986
80989
5
Skewn
ess
1.5930
44097
2
Range 5716 Range 5548 Range 4758 Range 4189 Range 4079 Range 3717
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Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Minim
um
71 Minim
um
78 Minim
um
48 Minim
um
53 Minim
um
54 Minim
um
55
Maxi
mum
5787 Maxi
mum
5626 Maxi
mum
4806 Maxi
mum
4242 Maxi
mum
4133 Maxi
mum
3772
Sum 13130 Sum 12736 Sum 10642 Sum 9489 Sum 9403 Sum 8836
Count 9 Count 9 Count 9 Count 9 Count 9 Count 9
2) Data regarding with age at diagnosis.
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Minim
um
71 Minim
um
78 Minim
um
48 Minim
um
53 Minim
um
54 Minim
um
55
Maxi
mum
5787 Maxi
mum
5626 Maxi
mum
4806 Maxi
mum
4242 Maxi
mum
4133 Maxi
mum
3772
Sum 13130 Sum 12736 Sum 10642 Sum 9489 Sum 9403 Sum 8836
Count 9 Count 9 Count 9 Count 9 Count 9 Count 9
2) Data regarding with age at diagnosis.
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
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Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 744.8 Mean 731.06
66666
667
Mean 621.2 Mean 549.8 Mean 533 Mean 485.06
66666
667
Standa
rd
Error
181.27
15458
458
Standa
rd
Error
179.55
98975
98
Standa
rd
Error
155.82
03238
776
Standa
rd
Error
131.34
22718
737
Standa
rd
Error
126.21
66693
391
Standa
rd
Error
114.47
21827
997
Media
n
578 Media
n
567 Media
n
484 Media
n
451 Media
n
440 Media
n
371
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
702.06
16782
021
Standa
rd
Deviat
ion
695.43
24930
437
Standa
rd
Deviat
ion
603.48
95193
788
Standa
rd
Deviat
ion
508.68
64316
2
Standa
rd
Deviat
ion
488.83
50583
64
Standa
rd
Deviat
ion
443.34
88575
871
Sampl
e
Varian
ce
49289
0.6
Sampl
e
Varian
ce
48362
6.3523
80952
Sampl
e
Varian
ce
36419
9.6
Sampl
e
Varian
ce
25876
1.8857
14286
Sampl
e
Varian
ce
23895
9.7142
85714
Sampl
e
Varian
ce
19655
8.2095
2381
Kurtos
is
-
0.4688
32916
8
Kurtos
is
-
0.4657
04111
3
Kurtos
is
-
0.1748
04343
6
Kurtos
is
-
0.2575
46722
8
Kurtos
is
-
0.4712
02153
7
Kurtos
is
-
0.5303
98939
9
Skewn
ess
0.8695
89584
9
Skewn
ess
0.8809
81217
5
Skewn
ess
0.9562
73675
4
Skewn
ess
0.8612
83892
2
Skewn
ess
0.8070
98259
Skewn
ess
0.7713
32546
5
Range 2116 Range 2081 Range 1899 Range 1612 Range 1502 Range 1368
Minim 11 Minim 14 Minim 11 Minim 6 Minim 9 Minim 6
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 744.8 Mean 731.06
66666
667
Mean 621.2 Mean 549.8 Mean 533 Mean 485.06
66666
667
Standa
rd
Error
181.27
15458
458
Standa
rd
Error
179.55
98975
98
Standa
rd
Error
155.82
03238
776
Standa
rd
Error
131.34
22718
737
Standa
rd
Error
126.21
66693
391
Standa
rd
Error
114.47
21827
997
Media
n
578 Media
n
567 Media
n
484 Media
n
451 Media
n
440 Media
n
371
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
702.06
16782
021
Standa
rd
Deviat
ion
695.43
24930
437
Standa
rd
Deviat
ion
603.48
95193
788
Standa
rd
Deviat
ion
508.68
64316
2
Standa
rd
Deviat
ion
488.83
50583
64
Standa
rd
Deviat
ion
443.34
88575
871
Sampl
e
Varian
ce
49289
0.6
Sampl
e
Varian
ce
48362
6.3523
80952
Sampl
e
Varian
ce
36419
9.6
Sampl
e
Varian
ce
25876
1.8857
14286
Sampl
e
Varian
ce
23895
9.7142
85714
Sampl
e
Varian
ce
19655
8.2095
2381
Kurtos
is
-
0.4688
32916
8
Kurtos
is
-
0.4657
04111
3
Kurtos
is
-
0.1748
04343
6
Kurtos
is
-
0.2575
46722
8
Kurtos
is
-
0.4712
02153
7
Kurtos
is
-
0.5303
98939
9
Skewn
ess
0.8695
89584
9
Skewn
ess
0.8809
81217
5
Skewn
ess
0.9562
73675
4
Skewn
ess
0.8612
83892
2
Skewn
ess
0.8070
98259
Skewn
ess
0.7713
32546
5
Range 2116 Range 2081 Range 1899 Range 1612 Range 1502 Range 1368
Minim 11 Minim 14 Minim 11 Minim 6 Minim 9 Minim 6
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
um um um um um um
Maxi
mum
2127 Maxi
mum
2095 Maxi
mum
1910 Maxi
mum
1618 Maxi
mum
1511 Maxi
mum
1374
Sum 11172 Sum 10966 Sum 9318 Sum 8247 Sum 7995 Sum 7276
Count 15 Count 15 Count 15 Count 15 Count 15 Count 15
3) Data related with probalbe exposure category.
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 36 Mean 28.666
66666
67
Mean 24 Mean 20.666
66666
67
Mean 26 Mean 22
Standa 9 Standa 7.2188 Standa 6.0277 Standa 5.7831 Standa 7.8102 Standa 5.5075
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
um um um um um um
Maxi
mum
2127 Maxi
mum
2095 Maxi
mum
1910 Maxi
mum
1618 Maxi
mum
1511 Maxi
mum
1374
Sum 11172 Sum 10966 Sum 9318 Sum 8247 Sum 7995 Sum 7276
Count 15 Count 15 Count 15 Count 15 Count 15 Count 15
3) Data related with probalbe exposure category.
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 36 Mean 28.666
66666
67
Mean 24 Mean 20.666
66666
67
Mean 26 Mean 22
Standa 9 Standa 7.2188 Standa 6.0277 Standa 5.7831 Standa 7.8102 Standa 5.5075
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Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
rd
Error
rd
Error
02609
2
rd
Error
13773
3
rd
Error
17191 rd
Error
49675
9
rd
Error
70547
3
Media
n
27 Media
n
23 Media
n
19 Media
n
20 Media
n
27 Media
n
17
Mode 27 Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
15.588
45726
81
Standa
rd
Deviat
ion
12.503
33288
9
Standa
rd
Deviat
ion
10.440
30650
89
Standa
rd
Deviat
ion
10.016
65280
09
Standa
rd
Deviat
ion
13.527
74925
85
Standa
rd
Deviat
ion
9.5393
92014
2
Sampl
e
Varian
ce
243 Sampl
e
Varian
ce
156.33
33333
333
Sampl
e
Varian
ce
109 Sampl
e
Varian
ce
100.33
33333
333
Sampl
e
Varian
ce
183 Sampl
e
Varian
ce
91
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Skewn
ess
1.7320
50807
6
Skewn
ess
1.6205
48721
5
Skewn
ess
1.6608
18054
2
Skewn
ess
0.2981
74552
2
Skewn
ess
-
0.3308
31814
7
Skewn
ess
1.7106
62618
2
Range 27 Range 23 Range 19 Range 20 Range 27 Range 17
Minim
um
27 Minim
um
20 Minim
um
17 Minim
um
11 Minim
um
12 Minim
um
16
Maxi
mum
54 Maxi
mum
43 Maxi
mum
36 Maxi
mum
31 Maxi
mum
39 Maxi
mum
33
Sum 108 Sum 86 Sum 72 Sum 62 Sum 78 Sum 66
Count 3 Count 3 Count 3 Count 3 Count 3 Count 3
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
rd
Error
rd
Error
02609
2
rd
Error
13773
3
rd
Error
17191 rd
Error
49675
9
rd
Error
70547
3
Media
n
27 Media
n
23 Media
n
19 Media
n
20 Media
n
27 Media
n
17
Mode 27 Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
15.588
45726
81
Standa
rd
Deviat
ion
12.503
33288
9
Standa
rd
Deviat
ion
10.440
30650
89
Standa
rd
Deviat
ion
10.016
65280
09
Standa
rd
Deviat
ion
13.527
74925
85
Standa
rd
Deviat
ion
9.5393
92014
2
Sampl
e
Varian
ce
243 Sampl
e
Varian
ce
156.33
33333
333
Sampl
e
Varian
ce
109 Sampl
e
Varian
ce
100.33
33333
333
Sampl
e
Varian
ce
183 Sampl
e
Varian
ce
91
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Kurtos
is
#DIV/
0!
Skewn
ess
1.7320
50807
6
Skewn
ess
1.6205
48721
5
Skewn
ess
1.6608
18054
2
Skewn
ess
0.2981
74552
2
Skewn
ess
-
0.3308
31814
7
Skewn
ess
1.7106
62618
2
Range 27 Range 23 Range 19 Range 20 Range 27 Range 17
Minim
um
27 Minim
um
20 Minim
um
17 Minim
um
11 Minim
um
12 Minim
um
16
Maxi
mum
54 Maxi
mum
43 Maxi
mum
36 Maxi
mum
31 Maxi
mum
39 Maxi
mum
33
Sum 108 Sum 86 Sum 72 Sum 62 Sum 78 Sum 66
Count 3 Count 3 Count 3 Count 3 Count 3 Count 3
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Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
4)
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 1095.3
33333
3333
Mean 1019.3
33333
3333
Mean 874.66
66666
667
Mean 751.77
77777
778
Mean 721.33
33333
333
Mean 634.88
88888
889
Standa
rd
Error
381.45
51815
817
Standa
rd
Error
363.86
70010
381
Standa
rd
Error
303.73
48533
032
Standa
rd
Error
258.21
39389
568
Standa
rd
Error
232.38
53958
884
Standa
rd
Error
197.65
06770
124
Media
n
518 Media
n
567 Media
n
497 Media
n
450 Media
n
444 Media
n
415
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
1144.3
65544
7452
Standa
rd
Deviat
ion
1091.6
01003
1142
Standa
rd
Deviat
ion
911.20
45599
096
Standa
rd
Deviat
ion
774.64
18168
705
Standa
rd
Deviat
ion
697.15
61876
653
Standa
rd
Deviat
ion
592.95
20310
372
Sampl
e
Varian
ce
13095
72.5
Sampl
e
Varian
ce
11915
92.75
Sampl
e
Varian
ce
83029
3.75
Sampl
e
Varian
ce
60006
9.9444
44445
Sampl
e
Varian
ce
48602
6.75
Sampl
e
Varian
ce
35159
2.1111
11111
Kurtos
is
0.3707
44706
8
Kurtos
is
0.5231
91198
7
Kurtos
is
0.5132
29441
Kurtos
is
0.5418
08823
8
Kurtos
is
0.4545
21756
5
Kurtos
is
0.4755
87361
2
Skewn 1.3855 Skewn 1.4449 Skewn 1.4272 Skewn 1.4311 Skewn 1.3613 Skewn 1.3423
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
4)
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 1095.3
33333
3333
Mean 1019.3
33333
3333
Mean 874.66
66666
667
Mean 751.77
77777
778
Mean 721.33
33333
333
Mean 634.88
88888
889
Standa
rd
Error
381.45
51815
817
Standa
rd
Error
363.86
70010
381
Standa
rd
Error
303.73
48533
032
Standa
rd
Error
258.21
39389
568
Standa
rd
Error
232.38
53958
884
Standa
rd
Error
197.65
06770
124
Media
n
518 Media
n
567 Media
n
497 Media
n
450 Media
n
444 Media
n
415
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
1144.3
65544
7452
Standa
rd
Deviat
ion
1091.6
01003
1142
Standa
rd
Deviat
ion
911.20
45599
096
Standa
rd
Deviat
ion
774.64
18168
705
Standa
rd
Deviat
ion
697.15
61876
653
Standa
rd
Deviat
ion
592.95
20310
372
Sampl
e
Varian
ce
13095
72.5
Sampl
e
Varian
ce
11915
92.75
Sampl
e
Varian
ce
83029
3.75
Sampl
e
Varian
ce
60006
9.9444
44445
Sampl
e
Varian
ce
48602
6.75
Sampl
e
Varian
ce
35159
2.1111
11111
Kurtos
is
0.3707
44706
8
Kurtos
is
0.5231
91198
7
Kurtos
is
0.5132
29441
Kurtos
is
0.5418
08823
8
Kurtos
is
0.4545
21756
5
Kurtos
is
0.4755
87361
2
Skewn 1.3855 Skewn 1.4449 Skewn 1.4272 Skewn 1.4311 Skewn 1.3613 Skewn 1.3423
Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
ess 94002
5
ess 23493
7
ess 98374
7
ess 26733
4
ess 82956
4
ess 11843
6
Range 3061 Range 2919 Range 2482 Range 2113 Range 1946 Range 1684
Minim
um
157 Minim
um
145 Minim
um
105 Minim
um
102 Minim
um
94 Minim
um
82
Maxi
mum
3218 Maxi
mum
3064 Maxi
mum
2587 Maxi
mum
2215 Maxi
mum
2040 Maxi
mum
1766
Sum 9858 Sum 9174 Sum 7872 Sum 6766 Sum 6492 Sum 5714
Count 9 Count 9 Count 9 Count 9 Count 9 Count 9
5) Data regarding with ethnicity and gender.
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
ess 94002
5
ess 23493
7
ess 98374
7
ess 26733
4
ess 82956
4
ess 11843
6
Range 3061 Range 2919 Range 2482 Range 2113 Range 1946 Range 1684
Minim
um
157 Minim
um
145 Minim
um
105 Minim
um
102 Minim
um
94 Minim
um
82
Maxi
mum
3218 Maxi
mum
3064 Maxi
mum
2587 Maxi
mum
2215 Maxi
mum
2040 Maxi
mum
1766
Sum 9858 Sum 9174 Sum 7872 Sum 6766 Sum 6492 Sum 5714
Count 9 Count 9 Count 9 Count 9 Count 9 Count 9
5) Data regarding with ethnicity and gender.
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Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 1092 Mean 1011.4 Mean 884 Mean 771.8 Mean 737.6 Mean 659.6
Standa
rd
Error
386.54
21063
739
Standa
rd
Error
323.03
19798
41
Standa
rd
Error
287.13
93389
976
Standa
rd
Error
226.99
21584
549
Standa
rd
Error
200.09
63767
788
Standa
rd
Error
167.52
77887
397
Media
n
938 Media
n
1009 Media
n
839 Media
n
742 Media
n
690 Media
n
591
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
864.33
44260
181
Standa
rd
Deviat
ion
722.32
14658
308
Standa
rd
Deviat
ion
642.06
30810
131
Standa
rd
Deviat
ion
507.56
98966
645
Standa
rd
Deviat
ion
447.42
91005
288
Standa
rd
Deviat
ion
374.60
35237
421
Sampl
e
Varian
ce
74707
4
Sampl
e
Varian
ce
52174
8.3
Sampl
e
Varian
ce
41224
5
Sampl
e
Varian
ce
25762
7.2
Sampl
e
Varian
ce
20019
2.8
Sampl
e
Varian
ce
14032
7.8
Kurtos
is
1.4427
48294
Kurtos
is
1.5054
76501
8
Kurtos
is
1.8172
10898
7
Kurtos
is
1.0319
48211
Kurtos
is
0.4056
22693
Kurtos
is
-
0.2646
69045
5
Skewn
ess
1.2518
25954
8
Skewn
ess
1.1865
70642
Skewn
ess
1.3057
459
Skewn
ess
1.0908
35934
7
Skewn
ess
0.8242
7313
Skewn
ess
0.8017
25915
8
Range 2154 Range 1827 Range 1609 Range 1256 Range 1152 Range 929
Minim
um
324 Minim
um
339 Minim
um
316 Minim
um
314 Minim
um
262 Minim
um
286
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Mean 1092 Mean 1011.4 Mean 884 Mean 771.8 Mean 737.6 Mean 659.6
Standa
rd
Error
386.54
21063
739
Standa
rd
Error
323.03
19798
41
Standa
rd
Error
287.13
93389
976
Standa
rd
Error
226.99
21584
549
Standa
rd
Error
200.09
63767
788
Standa
rd
Error
167.52
77887
397
Media
n
938 Media
n
1009 Media
n
839 Media
n
742 Media
n
690 Media
n
591
Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviat
ion
864.33
44260
181
Standa
rd
Deviat
ion
722.32
14658
308
Standa
rd
Deviat
ion
642.06
30810
131
Standa
rd
Deviat
ion
507.56
98966
645
Standa
rd
Deviat
ion
447.42
91005
288
Standa
rd
Deviat
ion
374.60
35237
421
Sampl
e
Varian
ce
74707
4
Sampl
e
Varian
ce
52174
8.3
Sampl
e
Varian
ce
41224
5
Sampl
e
Varian
ce
25762
7.2
Sampl
e
Varian
ce
20019
2.8
Sampl
e
Varian
ce
14032
7.8
Kurtos
is
1.4427
48294
Kurtos
is
1.5054
76501
8
Kurtos
is
1.8172
10898
7
Kurtos
is
1.0319
48211
Kurtos
is
0.4056
22693
Kurtos
is
-
0.2646
69045
5
Skewn
ess
1.2518
25954
8
Skewn
ess
1.1865
70642
Skewn
ess
1.3057
459
Skewn
ess
1.0908
35934
7
Skewn
ess
0.8242
7313
Skewn
ess
0.8017
25915
8
Range 2154 Range 1827 Range 1609 Range 1256 Range 1152 Range 929
Minim
um
324 Minim
um
339 Minim
um
316 Minim
um
314 Minim
um
262 Minim
um
286
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Colu
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Maxi
mum
2478 Maxi
mum
2166 Maxi
mum
1925 Maxi
mum
1570 Maxi
mum
1414 Maxi
mum
1215
Sum 5460 Sum 5057 Sum 4420 Sum 3859 Sum 3688 Sum 3298
Count 5 Count 5 Count 5 Count 5 Count 5 Count 5
CONCLUSION
From the above analysis it has been concluded that information & communication
technique are play vital role while collecting and presenting data. On the basis of using different
technique which includes informative and constructive technique, researcher able to find out
sources for collection of relevant information for their research project. And by using or
calculating value of mean, mode , median and standard deviation relation between different
variable of data series can be measured as well as these value help in analyasing research data
information in effective manner. On the basis of measuring value of these data research able
take decision for their further policies ans strategies regarding solving issue for specific problem.
As with the use of ICT technologies UK government able to find out rate of people died due to
Aids and impact of this disease on the basis of gender, these information useful for formulate
further polices to control issue regarding with this disease in UK.
REFERENCES
Books and journals
Falck, O., Heimisch-Roecker, A. and Wiederhold, S., 2020. Returns to ICT skills. Research
Policy, p.104064.
Kahan, D. M. and et.al., 2017. Motivated numeracy and enlightened self-government.
Behavioural public policy. 1(1). pp.54-86.
Lane, M. and Conlon, G., 2016. The impact of literacy, numeracy and computer skills on
earnings and employment outcomes.
Pinto, M. and et.al., 2016. Defining the key competences and skills for young low achievers’ in
lifelong learning by the voices of students, trainers and teachers. JSSE-Journal of Social
Science Education. pp.53-62.
Sgobbi, F., 2018. The Skills of European ICT Specialists. In Encyclopedia of Information
Science and Technology, Fourth Edition (pp. 4785-4796). IGI Global.
mn1
Colu
mn2
Colu
mn3
Colu
mn4
Colu
mn5
Colu
mn6
Maxi
mum
2478 Maxi
mum
2166 Maxi
mum
1925 Maxi
mum
1570 Maxi
mum
1414 Maxi
mum
1215
Sum 5460 Sum 5057 Sum 4420 Sum 3859 Sum 3688 Sum 3298
Count 5 Count 5 Count 5 Count 5 Count 5 Count 5
CONCLUSION
From the above analysis it has been concluded that information & communication
technique are play vital role while collecting and presenting data. On the basis of using different
technique which includes informative and constructive technique, researcher able to find out
sources for collection of relevant information for their research project. And by using or
calculating value of mean, mode , median and standard deviation relation between different
variable of data series can be measured as well as these value help in analyasing research data
information in effective manner. On the basis of measuring value of these data research able
take decision for their further policies ans strategies regarding solving issue for specific problem.
As with the use of ICT technologies UK government able to find out rate of people died due to
Aids and impact of this disease on the basis of gender, these information useful for formulate
further polices to control issue regarding with this disease in UK.
REFERENCES
Books and journals
Falck, O., Heimisch-Roecker, A. and Wiederhold, S., 2020. Returns to ICT skills. Research
Policy, p.104064.
Kahan, D. M. and et.al., 2017. Motivated numeracy and enlightened self-government.
Behavioural public policy. 1(1). pp.54-86.
Lane, M. and Conlon, G., 2016. The impact of literacy, numeracy and computer skills on
earnings and employment outcomes.
Pinto, M. and et.al., 2016. Defining the key competences and skills for young low achievers’ in
lifelong learning by the voices of students, trainers and teachers. JSSE-Journal of Social
Science Education. pp.53-62.
Sgobbi, F., 2018. The Skills of European ICT Specialists. In Encyclopedia of Information
Science and Technology, Fourth Edition (pp. 4785-4796). IGI Global.
Windisch, H. C., 2016. How to motivate adults with low literacy and numeracy skills to engage
and persist in learning: A literature review of policy interventions. International Review
of Education. 62(3). pp.279-297.
and persist in learning: A literature review of policy interventions. International Review
of Education. 62(3). pp.279-297.
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