Two research questions (hypothesis) in the quantitative part of Business Research Method course

1. LUT School of Business and Management
A350A0050 Business Research Methods
Course Mentor: Mika Vanhala D.Sc. (Econ. & Bus.Adm.)
PAPER TYPE: QUANTITATIVE RESEARCH PAPER 2016
Date: 07.12.2016
Prepared by: Group 10
Md Zulfiqur Islam 0459285
Petruchuk Liisa 0408281
Rohan Erava 0504101
Sultan Islam 0500192
Tatichek Gleb 0499290

2. 2
Contents
1 Introduction ................................................................................................................ 3
2 Theoretical Framework.............................................................................................. 4
3 Methodology............................................................................................................... 8
3.1 Hypothesis ............................................................................................................. 8
3.2 Sampling................................................................................................................ 9
3.3 Data collection ..................................................................................................... 10
3.4 Reliability and Validity .......................................................................................... 11
4 Descriptives.............................................................................................................. 13
4.1 Mean Comparison Hypothesis.......................................................................... 13
4.1.1 Type of contract (BV13)................................................................................. 13
4.1.2 Employee Satisfaction and Attitude towards work ......................................... 14
4.2 Correlation hypothesis...................................................................................... 15
4.2.1 Rewards and Career...................................................................................... 15
4.2.2 Work is seen as honor ................................................................................... 16
5. Analyses .................................................................................................................. 17
5.1 Mean Comparison Test...................................................................................... 17
5.1.1 Two Tailed Two Sample T-Test..................................................................... 18
5.2 Correlation analysis........................................................................................... 19
5.3 Distribution analysis.......................................................................................... 21
5.3.1 Q2_rewardsandcareer distribution................................................................. 21
5.3.1 Q4_honor....................................................................................................... 22
6 Discussion................................................................................................................ 23
6.1 Mean Comparison test......................................................................................... 23
6.2 Correlation test..................................................................................................... 25
Conclusion................................................................................................................... 26
References................................................................................................................... 27
Appendices.................................................................................................................. 29

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1 Introduction
Management in general and Human Resource Management (HRM) in particular aim to
increase productivity of an organization through various policies, communication and
interaction with employees. Productivity of an organization can be derived from efficient
processes, lower costs or higher value for customers. However, it can be argued that
productivity is always a result of the workers’ efforts, which consequently depend on
employees’ motivation, satisfaction and general perception of the work environment and
conditions.
In this regard business and scientific communities have been looking for ever deeper
understanding of factors that might influence employee motivation and satisfaction with
their work. Beckmann, Cornelissen and Schauenberg (2009) in their study of the
German labor market have suggested that even such factor as a type of contract might
have an effect on work satisfaction and attitude and hence on productivity.
Therefore, in this paper, we are aiming to support or negate the assumptions using the
data from the Survey on Finnish Values and Attitudes (2010). Using the mean
comparison method our first hypothesis (H1) evaluates whether or not and to which
degree fixed-term and permanent contracts influence employees’ satisfaction and
attitude toward work. Our findings confirmed results received by Beckmann,
Cornelissen and Schauenberg (2009).
Additionally, due to availability of data we decided to assess an extra hypothesis (H2) -
finding the relation of reward and career to honor as perceived by employees using the
correlation analysis. The analysis shows a rather strong correlation and supports our
hypothesis.
Following chapter will introduce reader to theoretical rationale behind the two
hypothesis and possible benefits to managerial practices from the findings if they are
confirmed. Chapter three will discuss methodology, followed by chapter four, which will
introduce the descriptives. Lastly in chapters five and six we summarize our analysis
and review the findings.

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2 Theoretical Framework
1st Research Question: Our first research question relates type of work contract and
employee satisfaction and attitude towards job. The question is – Do employee
satisfaction and their attitude work differ because of different work contract?
Despite an increased interest in research on the employee satisfaction and attitude
toward work, there is still limited amount of evidence that the type of contract has any
influence on those two pivotal measurements for managers. Much of the prior research
concentrates on relationship between working hours, organizational culture, managerial
style and how they relate to the employee satisfaction and attitude toward work. Thus
influence of the type of contract on satisfaction and attitude of workers remain a grey
area. The two types of contracts that we put to scrutiny in our first hypothesis are fixed-
term and permanent contracts.
Fixed term contract refers to the contractual relationships between an employer and an
employee that ends up accomplishing a particular task for a specified period.
Employees hired under fixed-term contract are called fixed-term employees. They are
entitled to do works mostly in absence of other employees and to meet the increased
seasonal demand for businesses. For example, in case of maternity leave of a
permanent employee in an organization, a fixed term employee can be hired for a
period no longer than the maternity leave for the purpose of continuing activities
simultaneously. The duration of fixed term contract varies among countries. The
duration ranges from one year (including renewal) to no specified limits held by many
countries (UK Government, 2016a).
On contrary permanent contract is a contractual relationship between an employer and
an employee with no specified time. A permanent employee is appointed for a position
without pre-determining any time limit. Permanent employees work longer time in
organizations and become experienced and loyal to the organizations. However, in case
of business downturn, they are often fired by employers as cost-cutting strategy in order
to control the cost structure and thus, the profitability (UK Government, 2016b).
Clearly if the type of contract has any effects on employee satisfaction and attitude the
findings might have profound implications for managers, employees and organizations

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as such. In short, understanding this fact better would help managers to adopt suitable
practices and stimulate workers to achieve higher productivity. In the literature fixed-
term and permanent contracts in relation to employee satisfaction and attitude usually
associated with task diversity, stress aversion, relationships with peers and perception
of career growth (Beckmann, Cornelissen and Schauenberg, 2009, p.24). In other
words, permanent employees have a more diverse range of tasks at work and it is
normally perceived with higher satisfaction with the job. At the same time fixed term
employees tend to be more stress averse, since their presence in the organization is
limited and they approach tasks with less enthusiasm and more stress. Although these
variables go beyond our hypothesis this perspective is essential for understanding the
interconnectedness of the phenomena and identifying future areas of research.
Additionally, attitude toward work can be defined as how an employee feels about his /
her task or responsibility. It can be good (positive) or bad (negative). For example,
commonly speaking, what one is interested in what he / she is doing and is enjoying it.
Does the work make him / her passionate, does it encourage him / her to do more?
These may be a few of questions that can help people identifying their attitude toward
work. In brief, in terms of employees’ attitude, it defines how they feel about the
assigned work.
Furthermore, satisfaction with work reflects an employee’s positive feeling about his job
resulting from evaluating the traits of that job. However, the positive feeling lies on many
different factors, including working environment, benefits, duties and responsibilities,
flexibility, decentralized power and so on (Beckmann, Cornelissen and Schauenberg,
2009, p.25). An individual employee’s satisfaction might vary depending on which factor
he / she places more weight in determining his / her own level of satisfaction. For
example, for some employees better and safer working environment is higher priority
than for others who seek more compensation benefits. We presume that employees
with a permanent contract have higher satisfaction with work than those with a fixed
term contract, the reasons behind their satisfaction might range from a diverse array of
things mentioned earlier.
During our research we came to know that permanent contracts have more influence
employee satisfaction and attitude as compared to fixed-term contract because

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employees under permanent contracts have assurance of safety of their job and also
they can build a strong relationship with their team member. There is also a benefits of
holiday, pension, sick pay etc. which is usually not available for the employee having
fixed contract. The company usually invest more on permanent employees such as for
training or sending abroad for new projects etc. It has been seen that statistically the
permanent employees are more likely to achieve higher status in the company as
compared to the fixed term contract employees hence because of this reasons
permanent contract employees have more satisfaction and attitude towards the job as
compare to the fixed term contract employees.
2nd Research Question: How much rewards and career are correlated to the concept of
seeing work as a matter of honor?
In our second hypothesis we make an assumption that reward and career are related to
honor.
In the work-related context we define reward as tangible and intangible benefits that
employees receive in return for the performed work. On one hand tangible benefits can
be defined as benefits that take form of compensation, bonus, salary increments,
performance-based benefits and, etc. On the other hand, intangible benefits can be for
example, praise for good work and performance by the boss, promotion, safety and
health schemes for employees and so forth. In other words, benefits can be related
either directly to monetary compensation or to the well-being of employees and their
families. Management science has proven that both types of rewards are necessary for
better employee performance.
In case of tangible benefits, it is rather clear that monetary compensation motivates
employees to a certain degree. It is often the case that our performance at work is
directly related to the sum of money that we receive, which can be seen by some as a
degree of appreciation and honoring of their work. After all, our income allows us to buy
things that we want and to live the lifestyle that we enjoy. Therefore, additionally
monetary rewards might be related to honor in a sense that employees, who get
performance benefits are admired / honored by their colleagues and friends.

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At the same time management gurus were always concerned about increasing
employee motivation and productivity through more indirect or intangible rewards. In
1960s a behavioral management school started showing evidence that employees can
be motivated beyond traditional means of pay and control. Elton Mayo, Abraham
Maslow and Douglas McGregor, who contributed to this school viewed employees as
individuals, resources, and assets to be developed and worked with — not as
machines, as in the past (Cliffnotes, 2016).
Typically, intangible rewards are associated with the culture, business model and
hierarchy within an organization that translates into appreciation and respect towards
employees. In fact, employees see benefits extended to them by the organization as
symbol of honor and respect not only for their past efforts, but also because the
organization genuinely cares about the workers. As mentioned before, organizations
and employers see those benefits and awards as a way of motivating so that employees
can deliver their best output for organizational growth and prosperity. Thus, it is a win-
win situation for employers to increase employees’ productivity and make profitable
business as well.
However, reward is not the only variable in our hypothesis, we argue that career is
related to honor too. Career is a term that can be defined from many perspectives. In
general, what we understand by career is an employee’s attempt to progress in his / her
occupational life by taking actions at different phases in life while realizing own
potential. In organizational context, employee’s position within the hierarchy and
consequent progression to the top play an important role. Career growth in this regard
can be perceived as appreciation and honor of the performance of an employee in the
eyes of his / her superiors, friends and relatives. One’s progress in career implies that
he / she has new role, new responsibilities, and thus he / she will be treated differently
than before. An employee’s rank and position affect the way he / she is treated by
others (whether it is internally or externally) it can be seen as a successful sign of
realizing one’s potential.

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As a brief recap one should mention that our second research question assumes that
tangible, intangible rewards and career related to honor whether it be external or
internal one.
3 Methodology
In this chapter, we will discuss about the general approach which we are going to carry
out in our research paper. Quantitative research is classified into three types which are
descriptive, experimental and casual comparative. For our research paper, we will go
with descriptive research method in which correlational, developmental design,
observational studies, and survey research are used. Our research model is divided into
six phases which are shown in figure 1. The illustrated path from hypothesis to
conclusion is a path we are going to follow to get the result of our research question.
The data we would be using for our hypothesis is the survey with structured
questionnaires whereas for the data management, descriptive and statistical analysis
we would be using the software called statistical analysis software (SAS) which can
mine, alter, manage and retrieve data from a variety of sources and perform statistical
analysis on it.
Figure 01: quantitative research method path.
3.1 Hypothesis
In this research paper, we are going to work on two hypotheses where one will be
related to mean comparison and the other one will be correlation analysis as mentioned
in the theoretical part. In order to test the hypothesis, we have used the deductive
method which is shown in figure 2. A deductive approach is developing a hypothesis
based on existing theory, and then designing a research strategy to test the hypothesis.
(Wilson, J. (2010))

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Figure 02: Application of Deductive Approach (Wilson, J. (2010))
In our research paper, for the 1st hypothesis we have taken the variables for the attitude
and satisfaction (Q1_satisfactionandattitude) of the people towards work and linked it
with the type of contract (BV13) which is permanent and fixed term contract whereas for
2nd hypothesis we have taken variables of rewarding and career (Q2_rewardandcareer)
and related it with work which is seen as honor (Q4_honor). These variables will be
tested and analyze using statistical analysis software to get the result of confirmation or
rejection.
3.2 Sampling
Our research is mainly focused on the people of Finland. As our both research question
is related toward the employment hence we would be concentrating on people who is
employed and having age group between 18-70. In general, there are two type of
sampling which is probability sampling and non-probability sampling but for our
research paper we would go with probability sampling which include random selection in
choosing some population elements. The internet survey with structured questionnaires
would be the best option for sampling the data for our research question and the people
who are employed can participate in that survey.
The data which we would be using for sample will be the surveys on Finnish Values and
Attitudes which was conducted by Finnish Business and Policy Forum (EVA) in 2010.
The data consist of two separate samples. The first sample was the internet survey
conducted by Taloustutkimus, with 2,048 respondents completing the questionnaire.
The second sample was the traditional simple random sample drawn from the Finnish

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population register (excluding the Åland Islands inhabitants) used for EVA surveys. In
this sample the number of adequately completed posted questionnaires was 1,124
persons. Both samples received the same questions. (Finnish Social Science Data
Archive, 2010)
3.3 Data collection
Data collection is the process of gathering and measuring information on variables of
interest, in an established systematic fashion that enables one to answer stated
research questions, test hypotheses, and evaluate outcomes. The data collection
component of research is common to all fields of study including physical and social
sciences, humanities, business, etc. While methods vary by discipline, the emphasis on
ensuring accurate and honest collection remains the same. (Northern Illinois University)
The data which we have collected is survey conducted by Finnish Business and Policy
Forum (EVA) in the form of SPSS portable file. The management of the file is done by
using SAS software. The survey was conducted in Finland with the age group between
18 and 70. The data contains 114 variables and 3172 cases. And the type of method for
data collection used is cross-sectional study. The main themes of this survey were
occupational life, working conditions in Finnish workplaces, national economy,
employment, time use and work-life balance. Other topics included the significance of
certain job characteristics and paid work in general. First, the respondents were asked
whether they agreed with several statements relating to working life and the Finnish
society. The next set of questions problems views on the importance of certain job/work
characteristics to the respondents. And finally, the respondents evaluated how likely it
was that certain changes would take place in occupational life in Finland. (Finnish
Social Science Data Archive, 2010)
In this data, they have used two different survey which is internet and postal with same
questions and combine it into one data. The biggest disadvantages of both survey are
that there is no control over who has responded the survey hence the result of the
survey is not completely reliable because there is possibility that out of 3172
respondents not all would be employed may be some are unemployed or students. The
more better option would be to make structured questionnaires in paper and go the

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companies where it can be distributed among the employers to fill the data hence it
would give the assurance that all the respondents are employers.
3.4 Reliability and Validity
The purpose of reliability and validity of measure is to evaluate the performance of the
hypothesis to identify possible issues related to its internal consistency, ability to
measure the phenomenon and potential sources of measurement error. Of special
importance is its ability of discriminate between virtual and traditional teams.
Reliability refers to the consistency, stability and repeatability of results i.e. the result of
a researcher is considered reliable if consistent results have been obtained in identical
situations but different circumstances (Twycross and Shields, 2004, p.36)
For our research paper hypotheses, we will be using Cronbach's alpha to measure
internal consistency that is, how closely related a set of items are as a group. It is a
measure of scale reliability. The scale to check whether the variable is acceptable or not
is shown in figure 3.
Figure 03: Scale to check reliability (Tavakol and Dennick, 2011)
The variables which we are used for our hypothesis are:
1. Work is seen as honor
2. Rewarding and career related
3. Attitude and satisfaction towards work

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For the variable 1 and 2 the Cronbach's alpha value is 0.84 and 0.74 which is coming in
the acceptable and good range whereas for the variable 3 the Cronbach's alpha value is
0.49 which is in the marginal range of poor range but there can be several probable
reasons for the value to be very low like:
 Different person finds satisfaction and attitude in different means. Thus, the
response will vary in the same group.
 It is also noted that there are around 900 missing values out of 3172
respondents.
 Not proper understanding of the question regarding this satisfaction and attitude
towards work question as it is sometimes difficult to understand and the
understanding varies from person to person.
Hence due to above reason we have neglected the low value and taken this variable in
our hypothesis to formulate the research question which we are going to analyze and
test in the following chapters.
Validity is the extent to which any measuring instrument measures what it is intended to
measure. It is possible for a measurement to be reliable but invalid however, if a
measurement is unreliable, then it cannot be valid (Thatcher, 2010, p.125; Twycross
and Shields, 2004, p.36). There are generally four type of validity i.e conclusion,
internal, construct and external and we are going with construct validity which define
how well a test or experiment measures up to its claims for example a test designed to
measure Attitude and satisfaction towards work must only measure that construct.
In this research paper, we are analyzing two hypotheses i.e. mean comparison and
correlation analysis and we will be using statistical analysis software (SAS) to measure
the validity of both hypotheses hence we will be using the ANOVA, t test, correlation
and distribution analysis in order to measure how well the questions which we have
formulated are related to the hypothesis. Moreover, the variables were grouped by the
survey authority according to their relevance to the themes. From these point of view,
we can state that we are conducting our research on the data with better validity.

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4 Descriptives
Descriptive statistics is a term of the data analysis which describes, shows and
summarizes data in a meaningful way using tables, charts and images (Lund Research,
2013). In this research paper, we have two different hypotheses and the summary
statistics of the related variables have been extracted using SAS. For descriptive
statistics, we mainly used bar chart, histogram, pie chart, frequency table and scatter
plot. We used all of these because all of these are necessary to show the movement of
data and frequency of data.
4.1 Mean Comparison Hypothesis
According to 1st research question, our 1st hypothesis about mean comparison is
related to two variables, type of contract (BV13) and employee attitude and satisfaction
(Q1_satisfactionandattitude) towards the work.
4.1.1 Type of contract (BV13)
In the research data respondents had to answer what kind of job contract they have with
the employers. There were three types of responses: permanent contract (1) and fixed-
term contract (2). According the frequency indicators, the biggest part of respondent has
permanent contract type. Only 12% of respondent have said that their type of job
contract is fixed-term. Unfortunately, big amount of respondents with 28% had refused
to reveal this information which stays as unknown. We extracted the frequency
distribution table (Appendix 01), frequency distribution chart (Appendix 02) and
histogram of BV13 (Appendix 03) which shows more detailed statistics than the pie
chart below.

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Figure 04: Response statistics of BV13 variable
4.1.2 Employee Satisfaction and Attitude towards work
In the research data respondents had to answer do they have positive level of
satisfaction and good attitudes towards work. There were five types of responses:
strongly agree (1), agree to some extent (2), difficult to say (3), disagree in some extent
(4) and strongly disagree (5). According the frequency indicators 29% of employees are
strongly agreeing and 45% of them are agreeing to some extent that they do have
satisfaction and positive attitudes towards their work. Nevertheless, 20% of the
respondents had a difficulty to confirm about the satisfaction and attitude toward work.
Based on the responses, we plotted a scatter plot of the whole population response
(Appendix 11).
From the descriptive statistics (Appendix 04), we found the mean 2.24, median 2.00
with a standard deviation of 0.85. We extracted the frequency distribution table
(Appendix 05), frequency distribution chart (Appendix 06) and histogram of employee
satisfaction and attitude towards work variable (Appendix 07) which shows more
detailed statistics than the pie chart below. Moreover, to understand independent
variable’s group wise (Permanent contract & Fixed contract) responses, we plotted bar
chart of the dependent variables responses in different independent variable group
(Appendix 08-10).
Permanent
Contract
60%
Fixed
Contract
12%
No
Response
28%
Response Stats : Type of Contract

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Figure 05: Response statistics of Q1_satisfactionandattitude variable
4.2 Correlation hypothesis
Our 2nd hypothesis about correlation is related to two variables, rewards and career
(Q2_rewardandcareer) and work seen as honor (Q4_honor).
4.2.1 Rewards and Career
In the research data respondents had to answer what is the importance level of
rewarding system is related to worker career. There were six types of responses: very
important (1), important (2), fairly important (3), not very important (4), not at all
important (5) and can’t say (6). According the frequency indicators, the most common
answer was that rewarding system is fairly important for the career perspectives, with
47% and 33% of the respondents think it is important in career. Based on the
responses, we plotted a scatter plot of the whole population response (Appendix 12).
From the descriptive statistics (Appendix 13), we found the mean 2.68, median 2.75
with a standard deviation of 0.74. We extracted the frequency distribution table
(Appendix 14), frequency distribution chart (Appendix 15) and histogram of rewards and
career variable (Appendix 16) which shows more detailed statistics than the pie chart
below.
Strongly Agree
29%
Agree to some
extent
45%
Difficult to say
20%
Disagree to
some extent
5%
Strongly
disagree
1%
Response Stats : Satisfaction & Attitude

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Figure 06. Response statistics of Q2_rewardandcareer variable
4.2.2 Work is seen as honor
In the research data respondents had to answer in what extent they value their work as
an honor. There were six types of responses: to a great extent (1), to a fairly large
extent (2), to some extent (3), to a small extent (4), not at all (5) and can’t response (6).
According the frequency indicators less than 1% of respondents can’t respond or did not
respond at all to this matter. Meanwhile only 2% of people stated that work is honor for
them in great extent because more than half of people took to some extent. Based on
the responses, we plotted a scatter plot of the whole population response (Appendix
17). From the descriptive statistics (Appendix 18), we found the mean 2.88 with a
standard deviation of 0.69. We extracted the frequency distribution table (Appendix 19),
frequency distribution chart (Appendix 20) and histogram of work is seen as honor
variable (Appendix 21) which shows more detailed statistics than the pie chart below.
Figure 07: Response statistics of Q4_Honor variable
Very important
7%
Important
33%
Fairly important
47%
Not very
important
12%
Not at all
important
0%
Can't say
1%
Response Stats : Rewards and Career
Great extent
2%
Fairly large
extenet
27%
To some extent
52%
To a small extent
17%
Not at all
1%
Can't say
1%
Work is seen as Honor

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If we see the correlation matrix, we can see the relation between these two variables:
Variable Mean Std. Dev.
Correlation
Q2_rewardandcareer Q4_honor
Q2_rewardandcareer 2.6778835 0.7428307 1.00 0.30305
Q4_honor 2.8787749 0.6857290 0.30305 1.00
Table 01: Correlation Matrix between Q2_rewardandcareer and Q4_honor
5. Analyses
5.1 Mean Comparison Test
To conduct the hypothesis test, we have conducted the test for difference between two
means which is known as Mean Comparison Test. For mean comparison test, we have
conducted a two-tailed two sample T-test with our 1st Hypothesis which is:
Ho: Permanent contract (BV13) doesn’t influence employee satisfaction and attitude
(Q1_attitudeandsatisfaction) more than Fixed term contract (BV13).
H1: Permanent contract (BV13) influences employee satisfaction and attitude
(Q1_attitudeandsatisfaction) more than Fixed term contract (BV13).
However, there is a technical reasoning behind the usage of T-Test instead of ANOVA
for this hypothesis. The reason behind choosing T-test is there are only two (2) distinct
variable response or classes in the classification variable whereas as per the
instruction, there should be at least three or more classes in the classification variable to
perform the complete ANOVA testing.

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5.1.1 Two Tailed Two Sample T-Test
This test has two parts where in the first part we have conducted the test to see whether
there is any difference between the variance. In that case, our hypothesis becomes:
Ho: Variances of two groups are equal.
H1: Variances of two groups are not equal.
From two tailed two sample T-Test, firstly we found the below data:
Equality of Variances
Method Num DF Den DF F Value Pr > F
Folded F 1887 383 1.01 0.9181
Table 02: Equality of Variance Test
From the P value of the test, it is eminent that the null hypothesis (Ho) is accepted, as P
value>0.05, which indicates that the variances of two groups are equal. In that case, as
the null hypothesis is accepted, we need to read the first line of the two methods of
mean equality testing which is Pooled Method. The hypothesis of Pooled Method is:
Ho: Means of two groups are equal.
H1: Means of two groups are not equal.
Based on the test, the result of the test is given on table below:
Method Variances DF t Value Pr > |t|
Pooled Equal 2270 -2.52 0.0117
Satterthwaite Unequal 551.72 -2.53 0.0116
Table 03: Pooled method of Mean Equality Test
Based on the Pooled Method result, P value is much smaller than 0.05 which indicates
the inequality of means, hence, rejects null hypothesis of equal means.
Moving forward to the next step, where we need to check the difference of the means
from the test as the Pooled Method Null Hypothesis has been rejected based on P

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value. We need to see how much the mean differs between the groups using the upper
limit and lower limit at 95% confidence interval:
Independent variable
(BV13)
Method Mean 95% CL Mean Std Dev 95% CL Std Dev
Permanent contract (1) 2.1504 2.1115 2.1893 0.8619 0.8353 0.8903
Fixed contract (2) 2.2721 2.1861 2.3582 0.8578 0.8011 0.9232
Difference (1-2) Pooled -0.1217 -0.2163 -0.0272 0.8612 0.8369 0.8870
Difference (1-2) Satterthwaite -0.1217 -0.2161 -0.0273
Table 04: Mean Difference between groups in different methods
From the above table, we derived the upper limit and lower limit at 95% confidence
interval of the mean difference as below:
-0.2163 < Permanent Contract mean – Fixed Contract mean < -0.0272
Point to be noted here that if the score is closer to 1, it indicates that the specific type of
contract has more influence in employee satisfaction and attitude towards job. As the
mean is coming from the responses of the respondents, so if the mean is closer to 1,
then it indicates more influence to satisfaction and attitude. From this relationship
equation, it is visible that Permanent Contract mean has lower value, hence, more
influence in employee satisfaction and attitude.
This above two tailed two sample T-Test confirms the rejection of our null hypothesis
which says that Permanent term contract doesn’t influences employee satisfaction and
attitude more than Fixed term contract. This rejection has been confirmed based on two
step testing of variance and means between these two groups.
5.2 Correlation analysis
This analysis assesses the correlation between two continuous variables and for our
report, we have selected Q2_rewardsandcareer and Q4_honor. We wanted to look
through the correlation between these two variables. As these two variables should
correlate with each other as per the theory, we wanted to check the statistical measure
to see how much correlation is there between these two variables. As both of these

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variables are non-normally distributed, we used Spearman Correlation Coefficient to
assess the correlation. In this analysis, our hypothesis will be:
Ho: Q2_rewardsandcareer and Q4_honor are not correlated.
H1: Q2_rewardsandcareer and Q4_honor are correlated.
By putting both variables in analysis variables, we found below result:
Spearman Correlation Coefficients
Prob > |r| under H0: Rho=0
Number of Observations
Q2_rewardsandcareer Q4_honour
Q2_rewardsandcareer
Rewarding and career
1.00000
3153
0.29967
<.0001
3140
Q4_honour
Honour
0.29967
<.0001
3140
1.00000
3151
Table 05: Correlation Analysis
From the above correlation analysis, we found P value less than 0.05 (P<0.05) which
indicates the positive correlation between these two variables and rejection of Null
Hypothesis of no correlation. The correlation measure is approximately 30%.
Figure 08: Correlation Analysis Result against the standard
-1.00
PERFECTLY
NEGATIVE
CORRELATION
-0.50
EVIDENT
NEGATIVE
CORRELATION
0.00
NO
CORRELATION
0.50
EVIDENT
POSITIVE
CORRELATION
1.00
PERFECTLY
POSITIVE
CORRELATION
0.30
EVIDENT
POSITIVE
CORRELATION
BETWEEN THE
ANALYSIS
VARIABLES

21. 21
5.3 Distribution analysis
In terms of distribution analysis, to see whether the distribution is normal or not, we
conducted Kolmogov-Smirnov test. In our second hypothesis of correlation, there are
two variables Q2_rewardsandcareer and Q4_honor. We conducted the same test for
both variables to have the understanding about their distribution normality.
5.3.1 Q2_rewardsandcareer distribution
In Kolmogorov-Smirnov test, we conducted the test with the null hypothesis of normally
distribution. So, our hypothesis for this test is:
Ho: Tested variable is normally distributed.
H1: Tested variable is not normally distributed.
As per the test, the normality of distribution can be derived from the below result table:
Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.0657564 Pr > D <0.010
Cramer-von Mises W-Sq 1.8032802 Pr > W-Sq <0.005
Anderson-Darling A-Sq 10.1246632 Pr > A-Sq <0.005
Table 06: Goodness of Fit test for normal distribution for Q2_rewardsandcareer
From the above table, we can see the P value is less than 0.05 which rejects the Null
Hypothesis that means the analysis variable (Q2_rewardsandcareer) does not have
normality in the distribution. From the histogram of the data series, it can be seen that
the series is slightly skewed to the left, hence, it is not normally distributed. Also, strong
responses can be seen at the most left corner (positive response to importance) which
can be another reason behind the non-normality of the distribution. It is logical that this
distribution would be skewed to left because generally people tend to put more
importance in rewards and career. Moreover, the normal percentile plot has been
derived from SAS as well for this variable (Appendix 22).

22. 22
Figure 09: Histogram of Q2_rewardsandcareer
5.3.1 Q4_honor
In Kolmogorov-Smirnov test, we conducted the test with the null hypothesis of normally
distribution. So, our hypothesis for this test is:
Ho: Tested variable is normally distributed.
H1: Tested variable is not normally distributed.
As per the test, the normality of distribution can be derived from the below result table:
Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.04615180 Pr > D <0.010
Cramer-von Mises W-Sq 0.73468148 Pr > W-Sq <0.005
Anderson-Darling A-Sq 3.91890101 Pr > A-Sq <0.005
Table 07: Goodness of Fit test for normal distribution for Q4_honor
From the above table, we can see the P value is less than 0.05 which rejects the Null
Hypothesis which means the analysis variable, (Q2_rewardsandcareer), does not have

23. 23
normality in the distribution. From the histogram of the data series, it can be seen that
the series is slightly skewed to the left, hence, it is not normally distributed. But, it can
be said from the histogram that this distribution has more normality tendency than
Q2_rewardsandcareer. Also, more responses can be seen at the left corner (positive
response to work is seen as honor) which can be another reason behind the non-
normality of the distribution. It is logical for people to consider their work as an honor for
them.
Figure 10: Histogram of Q4_honor
6 Discussion
We have conducted both of our hypothesis tests in SAS software and came up with the
results and decisions. However, in some cases, the data didn’t act as per our
expectation but it is quite understandable because of the large population and their
different mindset about the workplace related factors.
6.1 Mean Comparison test
In this stage, we conducted a two tailed two sample T-test in two steps, 1st step is to
check the variance variability and 2nd step is to check the mean variability, and tested

24. 24
our hypothesis. Our hypothesis was to check the influence variability of different type of
contracts (Permanent and Fixed) in employee satisfaction and attitude towards their job.
Statistically, there has not been significant variance difference in responses of two
groups of permanent contract employees and fixed contract employees. Based on the
Pooled method, we found the means are not equal and from the detailed data, we found
that, permanent contract employees tend to possess higher satisfaction and better
attitude towards work than fixed term contract.
In our theoretical part, we provided sufficient reasoning behind the permanent contract
employee’s satisfaction and attitude. The mean comparison test confirmed our
assumption on the support of permanent contract employees thus, the tests didn’t
provide any surprising result.
However, an influencing factor to support the permanent contract can be a large
number of respondent group, six times bigger than fixed term contract. Moreover,
despite of having such reasoning behind, it is quite understandable from the present
workplace phenomena that permanent contract employees tend to have more
satisfaction as they have their job security and better know-how about the job. Thus, it
influences their attitude towards their work. On the other hand, due to having a certain
period contract, fixed term contract employees lack in the satisfaction as they know that
at the end of the contract period, they have to search for another job. We can tell that
the present workplace phenomena support our hypothesis that there is a difference of
satisfaction and attitude in these two groups and permanent contract employees have
been proven to be the group whose satisfaction and attitude is more influenced by their
work contract.
However, this result may vary in different countries like China where project work can
be more readily available because of boom of different industry. And in this era of online
work platform, fixed term contract may reign in the workplace industry soon.

25. 25
6.2 Correlation test
In this stage of testing, we conducted a correlation test to see whether reward and
career related matters have any correlation with the concept of seeing work as a matter
of honor.
Using the Spearman correlation test, we found there is a slight positive correlation
between rewarding system in career and feeling honored about the career. Though
according to correlation standard, at least 50% correlation can be said as strong
evidence of correlation. But, our result indicates at least some correlation exists
between these two variables.
Theoretically, reward system in a career motivates an employee and keep him
considering his/her career as a matter of honor in the society. As everyone favors
career recognition and the matter of honor is related to this recognition system, thus,
our testing proves the present workplace phenomena to some extent.
The lower value of the correlation may be influenced by the large number of
respondents. As the matter of honor is relative to person to person, thus, a person can
consider the reward as a part of honored career, whereas another person can value
something else as a part of the honored career. This relativity influenced this concept of
honored career and lowered the correlation. However, this may vary from country to
country and industry to industry. But, we need to mention again about the progression
of online work platform where millions of freelance workers are working with integrity
and earning good reviews (can be seen as reward or recognition) which gives them a
satisfaction and honor of working in that industry or sector or for a specific company.

26. 26
Conclusion
Our analysis has supported initial hypothesis that permanent contract has higher
influence over employee satisfaction and attitude toward work than fixed-term contract.
It is important to note that although the reliability measure value was rather low, we still
were able to receive the expected results. We assume that the low reliability measure
was due to the missing data from 900 respondents. Nevertheless, the outcome in
general satisfies our assumptions and follows the pattern of our logic. Therefore, our
first hypothesis serves reasonable grounds and can be considered as a correct one.
At the same time, the second hypothesis showed positive correlation between reward
and honor. This means that reward-based work leads to employees’ honor. Similar to
the first hypothesis the variables did not completely correlate with each other as per our
assumption. Nevertheless, the result that we received is positive and shows some
correlation between reward and honor.
For further research we suggest to study the same questions using the data that was
collected primarily for the purpose of finding the effect of the type of contract on
employee satisfaction and attitude toward work. Similarly, suggestion can be made in
relation to the second hypothesis, since partially we attribute lower correlation than
expected to a slightly vague definition of the variable ‘honor’ in this particular data set.

27. 27
References
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https://www.gov.uk/fixed-term-contracts/what-counts-as-a-fixedterm-contract
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Government UK (2016) Fixed-term employment contracts. Available at:
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(Accessed: 28 November 2016).
Beckmann, M., Cornelissen, T. and Schauenberg, B. (2009) ‘Fixed-term employment,
work organization and job satisfaction: Evidence from German individual-level data’,
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28. 28
TWYCROSS, A. & SHIELDS, L. (2004). Validity and reliability - What's it all about? Part
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29. 29
Appendices
Appendix 01
Figure 11: Frequency Distribution of Type of Contract (BV13)
Appendix 02
Response of BV13 Count %
Permanent Contract 1888 60%
Fixed Contract 384 12%
No Response 900 28%
Grand Total 3172 100%
Table 08: Frequency Distribution Table of Type of Contract (BV13)
Appendix 03
Figure 12: Histogram of Type of Contract (BV13)
[1: Permanent Contract, 2: Fixed Contract]
1 2
Type of Contract (BV13)

30. 30
Appendix 04
Basic Statistical Measures
Location Variability
Mean 2.238178 Standard Deviation 0.85449
Median 2.000000 Variance 0.73015
Mode 2.000000 Range 4.00000
Interquartile Range 1.50000
Table 09: Descriptive statistic of Q1_satisfactionandattitude
Appendix 05
Attitude and satisfaction
Q1_attitudeandsatisfaction Frequency Percent
Cumulative
Frequency
Cumulative
Percent
1 76 8.44 76 8.44
1.5 86 9.56 162 18.00
2 241 26.78 403 44.78
2.5 241 26.78 644 71.56
3 110 12.22 754 83.78
3.5 98 10.89 852 94.67
4 31 3.44 883 98.11
4.5 9 1.00 892 99.11
5 8 0.89 900 100.00
Table 10: Frequency Distribution Table of Q1_satisfactionandattitude

31. 31
Appendix 06
Figure 13: Frequency Distribution of Q1_satisfactionandattitude
Appendix 07
Figure 14: Histogram of Q1_satisfactionandattitude
0 50 100 150 200 250
Frequency
1
1.5
2
2.5
3
3.5
4
4.5
5
Attitudeandsatisfaction
Distribution of Q1_attitudeandsatisfaction

32. 32
Appendix 08
Figure 15: Bar Chart of Q1_satisfactionandattitude (No classification)
Appendix 09
Figure 16: Bar Chart of Q1_satisfactionandattitude (Permanent Contract)

33. 33
Appendix 10
Figure 17: Bar Chart of Q1_satisfactionandattitude (Fixed Contract)
Appendix 11
Figure 18: Scatter Plot of Q1_satisfactionandattitude
0
1
2
3
4
5
6
0 500 1000 1500 2000 2500 3000 3500
Q1_attitudeandsatisfaction

34. 34
Appendix 12
Variable Label Mean Std Dev Variance Minimum Maximum N N Miss
Q2_rewardsand
career
Rewarding
and career
2.68 0.74 0.55 1.00 5.00 3153 19
Table 11: Descriptive statistic of Q2_rewardandcareer
Appendix 13
Responses
Count of
Q2_rewardandcareer
%
Scale of
score
Very important 212 7% 1-1.5
Important 1058 33% 1.51-2.5
Fairly important 1481 47% 2.51-3.5
Not very important 384 12% 3.51-4.5
Not at all important 18 1% 4.5-5
Can't say 19 1%
Grand total 3172 100%
Table 12: Frequency Distribution Table of Q2_rewardandcareer
Appendix 14
Figure 19: Frequency Distribution Chart of Q2_rewardandcareer
1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0
Rewarding and career
0
2
4
6
8
10
12
Percent
Distribution of Q2_rewardsandcareer

35. 35
Appendix 15
Figure 20: Histogram of Q2_rewardandcareer
Appendix 16
Figure 21: Scatter Plot of Q2_rewardandcareer
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 50 100 150 200
Q2_rewardsandcareer

36. 36
Appendix 17
Variable Label Mean Std Dev Variance Minimum Maximum N N Miss
Q4_Honor Honor 2.88 0.69 0.47 1.00 5.00 3151 21
Table 13: Descriptive statistic of Q4_Honor
Appendix 18
Honor Count % Scale of score
Great extent 67 2% 1-1.5
Fairly large
extent 857 27%
1.51-2.5
To some extent 1651 52% 2.51-3.5
To a small extent 538 17% 3.51-4.5
Not at all 38 1% 4.5-5
Can't say 21 1%
Grand Total 3172 100%
Table 14: Frequency Distribution Table of Q4_Honor
Appendix 19
Figure 22: Frequency Distribution Chart of Q4_Honor
1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0
Honour
0.0
2.5
5.0
7.5
10.0
12.5
15.0
Percent
Distribution of Q4_honour

37. 37
Appendix 20
Figure 23: Histogram of Q4_Honor
Appendix 21
Figure 24: Scatter Plot of Q4_honor
0
1
2
3
4
5
6
0 50 100 150 200
Q4_honour

38. 38
Appendix 22
Figure 25: Normal Percentile Plot of Q2_rewardandcareer