Effects of Science and Technology on Work and the UK Society

This report investigates the complex relationship between technology and jobs in the UK, examining public perception and its influence on job creation. The study utilizes data from the World Values Survey Wave 5 of 2015, focusing on variables such as the importance of work, opinions on science and technology, and their impact on health, ease of life, and job opportunities. Employing descriptive statistics, frequencies, proximities, sequence plots, correlations, and t-tests, the analysis aims to test the hypotheses regarding the positive or negative effects of technology on the UK job market and societal well-being. The findings provide insights into the general opinions on the role played by science and technology in the given sample space, considering the role of employment, welfare of the society and also how technology affects individual lives. The results will be used to accept or nullify the original hypotheses.

Title: Effects of Science and Technology on Work and the UK
Society
Task: Utilization of Various Analytics Tools and Techniques to
Provide Insights on Data
Student Name:
Tutor’s Name:
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Table of Contents
1. Introduction..............................................................................................................................3
1.1 Background Information...............................................................................................3
1.2 Aim................................................................................................................................4
2. Conceptual Framework............................................................................................................5
2.1 Literature Review..........................................................................................................5
2.2 Relevance of research....................................................................................................6
2.3 Hypotheses....................................................................................................................6
Null hypothesis............................................................................................................................6
Alternative hypotheses.................................................................................................................6
3. Methodology............................................................................................................................8
3.1 Data collection...............................................................................................................8
3.2 Data justification...........................................................................................................8
3.3 Data Description............................................................................................................8
4. Data analysis..........................................................................................................................11
4.1 Descriptive statistics....................................................................................................11
4.2 Frequencies..................................................................................................................12
4.3 Proximities...................................................................................................................15
4.4 Sequence plot..............................................................................................................15
4.5 Complex Samples: Plan...............................................................................................17

4.6 Correlations.................................................................................................................18
4.7 P-P plot........................................................................................................................21
4.8 Non-Parametric Tests..................................................................................................24
4.9 T-test............................................................................................................................26
5. Results....................................................................................................................................27
6. Discussion..............................................................................................................................28
6.1 Proof of hypotheses.........................................................................................................28
6.2 General inference........................................................................................................29
7. Conclusion.............................................................................................................................30
8. Bibliography..........................................................................................................................31

1. Introduction
1.1 Background Information
Technology is here to stay whether we admit or deny, even more fascinating is the way most
aspects of our lives have become dependent on it. From Medicine, agriculture, education, space
exploration, maritime and the widely debated field of Work, technology is literally present in
every sector covered by human activity and life. With not more than a century since
technological integration into human life, it is easy to dub it the fastest adopted concept.
However, as it is with every concept or system, there must be flaws and strengths, those who are
for and those against. Taking into consideration the effect of technology in the field of work,
there has been considerable debate on its ability to either cause harm or good in the economical
sense of job creation. According to Holland & Bardoel (2016), “The twenty-first century has
seen significant expansion in the use and availability of technology, which has created a
paradigm shift in how we can work.” Therefore, largely technology is directly overhead in
shaping the direction of our economy.
In his paper on technology and the future of jobs, Manyika notes that, “Automation, digital
platforms, and other innovations are changing the fundamental nature of work. Understanding
these shifts can help policy makers, business leaders, and workers move forward.” Manyika
(2017). As well, it may lead to more innovative ways of creating more jobs.
Despite all the benefits that are ideally raking from technology, still there is a word of
cautionary on the role of technology and its adoption by businesses. In a report for the G-20
summit in Turkey 2015 on the effects of technology on employment it is argued that in as much

as technology is shaping structure of employment relationships, It also has implications on
individuals and even the likelihood of dragging behind World Bank Group (2015).
1.2 Aim
The aim of our paper is to explore the relationship between technology and jobs in the UK
population, and examine the perception of technology as well as the importance attached to it.
The study will then enable us answer the question of, “Does technology influence job creation in
the United Kingdom?”

2. Conceptual Framework
2.1 Literature Review
There are several components that make up technology, some of which include:
i. Automation i.e. robotics
ii. Digital platforms such as search engines
iii. Artificial Intelligence
iv. Information Technology
v. Cloud technology, etcetera
Morgan (2014), in an article about the future of work notes that numerous interesting changes are
evident throughout different technological realms that are affecting work. Consequently, the
scope of work is constantly changing. In relation, Harvey debates on the role of information
technology as in, “The use and control of IT provides an opportunity to be innovative in: when
we work, where we work, and the way we work,” Harvey (2010).
A journal by World Bank in 2009 on the advancement of technology over time argues that,
“Technologies such as smart machines, smart devices, and smart techniques,” have greatly
revolutionized over the past two decades, IC4D (2009). Hence, an argument that, as technology
develops more into precision, accuracy, and intelligence there is a likelihood of more adoption is
possible, which in turn may influence innovations and aid in the creation of more jobs.
However, as Makortoff (2015) notes, there is a general ‘myth’ of technology being a cause of job
loss. She nevertheless refutes this, arguing that research shows that over the past one and half a

century there has been, “… growth of jobs in the creative, care, tech and business service
industries have more than offset the loss of jobs in the agricultural and manufacturing sectors.”
2.2 Relevance of research
Our research aim is to investigate the role of technology is a given the UK economy with
specific interest on its effect on jobs and the society’s well-being. As viewed, technology has a
hand in the creation of jobs, which translate to better societal welfare or being a time bomb with
crippling capabilities of the job market, hence potentially causing a job crisis.
In the research, we will focus on how science and technology have affected the UK society; we
will additionally explore the role of science and technology in creating job opportunities, as well
as the acceptance of technology by the workers in relation to job security.
Moreover, we will identify the relationship between science and technology and the well-being
of the society.
2.3 Hypotheses
Null hypothesis
Manyika (2017) relates that, with modern day automation of many sectors, there is no full
guarantee of job security in a number of fields.
H0- Science and Technology has negatively affected job creations in the UK, i.e. technology
does not contribute to more jobs.
Alternative hypotheses
In an interview with CNBC, Stewart, a Deloitte economist says that, "I'm not saying the tech is
the answer to everything, but there's very strong evidence of job creation." CNBC (2015).

H1- Science and Technology leads to more job opportunities in the UK
In another study on the role of medical technology conducted by Tan et al (2002) indicates that,
“Without doubt, medical technology is indispensable for people's health and better quality of life
in some areas.”
H2- Better scientific and technological advancement translate to prospectively better healthcare
in the UK

3. Methodology
3.1 Data collection
Data used in the research is from World Values Survey Wave 5 of 2015, in a survey conducted in
the UK to determine the opinion of a sample population on a range of topics, including:
i. Politics
ii. Religion
iii. Technology
iv. Happiness
v. Government
vi. Self-development
vii. Work
3.2 Data justification
Normalization test of the sample data was conducted to investigate for normality with
population. The survey took place in eleven regions in the UK
3.3 Data Description
The data before cleaning has 1041 entries and 416 variables. After cleaning and removing
redundant, missing values, duplicate values, and prepared for data analysis, we sort out five
variables for consideration having 990 sample population valid entries.
The variables are:

i. V8-Work important
The measurements of the responses were:
 1- work is conclusively important
 2- work is not conclusively important
 3- Not sure
ii. V90- Opinion about Science and Technology
Measurement:
 1- Science and technology is great
 2- Science and technology is not significant
 3- Not sure
iii. V91- Science and technology are making our lives healthier, easier
Measurement:
 1- Yes
 2- No
 3- Other
iv. V92- Because of science and technology, there will be more work opportunities
Measurement:
 1- agrees
 2-Disagrees
 Not sure
v. V93- Science and technology make our way of life change too fast

Measurement:
 1-Agrees
 2-Disagrees
 Other
In our study, V90 is the dependent variable while, V91, V92 and V93 will be the independent
variables. We will examine the general opinion on the role played by science and technology in
the given sample space considering the role of employment, welfare of the society and also how
technology affects individual lives.
With the outcomes, we will infer and be able to accept or nullify the original hypotheses.

4. Data analysis
4.1 Descriptive statistics
Descriptive Statistics
N Range Minimu
m
Maximu
m
Mean Std.
Deviati
on
Varianc
e
Skewness Kurtosis
Statisti
c
Statisti
c
Statisti
c
Statistic Statisti
c
Statistic Statisti
c
Statisti
c
Std.
Erro
r
Statisti
c
Std.
Erro
r
Opinion
about
scientific
advance
990 2 1 3 1.71 .825 .680 .577 .07
8
-1.291 .15
5
Science
and
technolog
y are
making
our lives
healthier,
easier
0
Because
of
science
and
technolog
y, there
will be
more
opportuni
ty
0
Science
and
technolog
0

y make
our way
of life
change
too fast
Valid N
(listwise)
0
4.2 Frequencies
Statistics
Opinion about
scientific
advance
Science and
technology are
making our
lives healthier,
easier
Because of
science and
technology,
there will be
more
opportunity
Science and
technology
make our way
of life change
too fast
N Valid 990 0 0 0
Missing 51 1041 1041 1041
Frequency Table
Opinion about scientific advance
Frequency Percent Valid Percent Cumulative
Percent
Valid Will help 520 50.0 52.5 52.5
Will harm 235 22.6 23.7 76.3
Some of each 235 22.6 23.7 100.0
Total 990 95.1 100.0
Missing Missing; Not asked by the
interviewer
1 .1
No answer 2 .2
Don´t know 48 4.6
Total 51 4.9
Total 1041 100.0

Science and technology are making our lives
healthier, easier
Frequency Percent
Missing Not asked 1041 100.0
Because of science and technology, there will
be more opportunity
Frequency Percent
Missing Not asked 1041 100.0

Science and technology make our way of life
change too fast
Frequency Percent
Missing Not asked 1041 100.0

4.3 Proximities
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
0 .0% 1041 100.0% 1041 100.0%
4.4 Sequence plot
Model Description
Model Name MOD_1
Series or Sequence 1 Opinion about scientific
advance

Transformation Natural logarithm
Non-Seasonal Differencing 1
Seasonal Differencing 0
Length of Seasonal Period No periodicity
Horizontal Axis Labels Sequence numbers
Intervention Onsets None
Reference Lines None
Area Below the Curve Not filled
Applying the model specifications from MOD_1
Case Processing Summary
Opinion about
scientific
advance
Series or Sequence Length 1041
Number of Missing Values
in the Plot
Negative or Zero Before
Log Transform
51a
User-Missing 51
System-Missing 0
a. The minimum value is 1.000.

4.5 Complex Samples: Plan
Summary
Stage 1
Design Variables Stratification 1 Work important
2 Because of science and
technology, there will be
more opportunity
3 Science and technology
make our way of life change
too fast
4 We depend too much on
science and not enough on
faith
Cluster 1 Opinion about scientific
advance

Sample Information Selection Method
Analysis Information Estimator Assumption Sampling with replacement
Plan File: D:\Assigned\statistics\New folder\New folder
ew.csaplan
Weight Variable: Science and technology are making our lives healthier, easier
SRS Estimator: Sampling without replacement
4.6 Correlations
Descriptive Statistics
Mean Std. Deviation N
Opinion about scientific
advance
1.71 .825 990
Science and technology are
making our lives healthier,
easier
. . 0
Because of science and
technology, there will be
more opportunity
. . 0
Science and technology
make our way of life
change too fast
. . 0
Correlations
Opinion about
scientific
advance
Science and
technology are
making our
lives healthier,
easier
Because of
science and
technology,
there will be
more
opportunity
Science and
technology
make our way
of life change
too fast
Opinion about scientific
advance
Pearson Correlation 1 .a .a .a
Sig. (2-tailed) . . .
Sum of Squares and
Cross-products
672.955 . . .
Covariance .680 . . .

N 990 0 0 0
Science and technology
are making our lives
healthier, easier
Pearson Correlation .a .a .a .a
Sig. (2-tailed) . . .
Sum of Squares and
Cross-products
. . . .
Covariance . . . .
N 0 0 0 0
Because of science and
technology, there will be
more opportunity
Pearson Correlation .a .a .a .a
Sig. (2-tailed) . . .
Sum of Squares and
Cross-products
. . . .
Covariance . . . .
N 0 0 0 0
Science and technology
make our way of life
change too fast
Pearson Correlation .a .a .a .a
Sig. (2-tailed) . . .
Sum of Squares and
Cross-products
. . . .
Covariance . . . .
N 0 0 0 0
a. Cannot be computed because at least one of the variables is constant.

4.7 P-P plot
Model Description
Model Name MOD_6
Series or Sequence 1 Opinion about scientific
advance
2 Science and technology are
making our lives healthier,
easier
3 Because of science and
technology, there will be more
opportunity
4 Science and technology make
our way of life change too fast

5 We depend too much on
science and not enough on
faith
Transformation None
Non-Seasonal Differencing 0
Seasonal Differencing 0
Length of Seasonal Period No periodicity
Standardization Applied
Distribution Type Normal
Location Estimated
Scale Estimated
Fractional Rank Estimation Method Blom's
Rank Assigned to Ties Mean rank of tied values
Applying the model specifications from MOD_6
Case Processing Summary
Opinion
about
scientific
advance
Science
and
technology
are making
our lives
healthier,
easier
Because of
science
and
technology
, there will
be more
opportunity
Science
and
technology
make our
way of life
change too
fast
We
depend too
much on
science
and not
enough on
faith
Series or Sequence Length 1041 1041 1041 1041 1041
Number of Missing
Values in the Plot
User-Missing 51 1041 1041 1041 1041
System-Missing 0 0 0 0 0
The cases are unweighted.
Opinion about scientific advance

4.8 Non-Parametric Tests
4.8.1 Chi-Square Test
Frequencies
Opinion about scientific advance
Observed N Expected N Residual
Will help 520 330.0 190.0
Will harm 235 330.0 -95.0
Some of each 235 330.0 -95.0
Total 990

Test Statistics
Opinion about
scientific
advance
Chi-Square 164.091a
df 2
Asymp. Sig. .000
Exact Sig. .000
Point Probability .000
a. 0 cells (.0%) have expected
frequencies less than 5. The
minimum expected cell frequency is
330.0.
4.8.2 Kolmogorov-Smirnov
One-Sample Kolmogorov-Smirnov Test
Opinion about
scientific
advance
N 990
Normal Parametersa,,b Mean 1.71
Std. Deviation .825
Most Extreme Differences Absolute .331
Positive .331
Negative -.194
Kolmogorov-Smirnov Z 10.423
Asymp. Sig. (2-tailed) .000
a. Test distribution is Normal.
b. Calculated from data.

4.9 T-test
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
95%
Confidence
Interval of the
Difference
F Sig. t df Sig.
(2-
tailed
)
Mean
Differenc
e
Std. Error
Differenc
e
Lower Upper
Work
importan
t
Equal
variances
assumed
1.817 .178 .14
6
682 .884 .012 .081 -.147 .171
Equal
variances not
assumed
.14
3
399.31
6
.887 .012 .083 -.151 .175

5. Results
From an analysis of the data, the following Observations are made:
The sample data used contains 990 valid entries, having:
 Mean- 1.71
 Standard deviation- 0.85
 Variance- 0.680
 Skewness statistic- 0.577 and skewness standard error- 0.078
 Negative kurtosis of -1.291 and std error of 0.155
In addition, the level of asymptotic significance for the opinion on science in the sample is 0.000
whereas the exact significance is 0.000 equally. The statistics, chi-square value is 164.091 with 2
degrees of freedom.
The frequencies indicate 520 residents think science and technology will be more helpful than it
will cause harm, while 235 expect more harm from technology, whereas 235 are split between
the harm and promise offered by science.
The significance level of the importance of work with equal variances assumed is 0.884 while for
unequal variances is 0.887, the mean difference in Levene’s test for both variances is 0.12
whereas the upper and lower differences are -0.147 for lower and 0.171 for upper in equal
variances and -0.151 for lower and 0.175 for upper in unequal variances
Elsewhere, the Pearson correlation coefficient is zero for all the independent variables, in
addition to the test of normality; Kolmogorov-Smirnov Z Asymptotic test has a Significance

level of 0.000. However, the opinion on science has a Pearson correlation of one, sum of least
squares of 672.955 and a covariance of 0.680.
The data reflect a normal distribution from the shape of the gauss curve
6. Discussion
6.1 Proof of hypotheses
Null hypothesis
Our original null hypothesis states that, “Science and Technology has negatively affected job
creations in the UK.” From the results, the significance level for the opinion on whether
technology is likely to create more jobs is 0.171 therefore making it insignificant. As such, we
therefore reject the null hypothesis
Alternative Hypotheses
i. H1
The first alternative hypothesis is, “Science and Technology leads to more job opportunities in
UK.” From the chi- test, the significance level of the question on job creation is 0.000 therefore
making the test variable significant. Hence, we accept the null hypothesis, indicating that
technology is about the effect of creating more jobs in the UK.
ii. H2
The second alternative hypothesis is “Better scientific and technological advancement translate
to prospectively better healthcare in the UK.” From the chi- test, the significance level for the

effect of technology on health care is 0.000 making technology significant for healthcare. Hence,
we accept the alternative hypothesis.
6.2 General inference
From the graphs, we infer that the population follows a normal distribution where the majority of
the residents in the sample population are of the opinion that science and technology will be of
good to the UK as a whole than its injurious potential. The opinion on science and technology is
a general reflection of the underlying issues such as:
i. How it affects work
ii. Its role in health care
iii. How it influences communication and ultimately socialization
iv. Its relationship with religion

7. Conclusion
Change comes in numerous ways, more often; the society is to deal with the implication and the
effect of either adopting or rejecting the proposed change. As it is with every change, science and
technology have its positives and negatives alike and therefore it is prone to varied opinions such
as:
 Causing societal alienations through disrupting communication
 Improving health care service delivery
 Increasing business productivity
 Rendering some job sectors redundant and therefore the risk of brushing off
All these are the effects that come from adopting science and technology. It is therefore
imperative to weight the measures between the potential for good and that for bad caused in
order to determine the effectiveness of technology. In our case, we find out that science and
technology in the UK has the ability to:
i. Create more job opportunities
ii. Improve health care in the society and hence the welfare
iii. Radically change the way of life of citizens
Our research therefore aids, to provide a base for an argument in the widespread debate on the
role technology has grown to play in various aspects of human life. Given our research findings,
we can stand for the opinion that science and technology is more of benefit to the society.

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