Applied Statistics and Forecasting

This study explores the application of statistics and forecasting in business performance. It discusses the relationship between casual factors and salary, and the impact of casual factors on innovation in UK companies. The study uses quantitative research type, interpretivism philosophy, and deductive research approach. Data is collected through secondary data collection methods and analysed using SPSS. The findings suggest that companies need to consider casual factors while evaluating salary and indulge in different factors to improve business performance.

Applied statistics and Forecasting

INTRODUCTION
Statistics is a science which is related with developing and studying methods for
collecting and analyzing the empirical data. This in turn also assist in the forecasting and that is
why most of the top companies uses this tool in order to recover the business presentation. The
present study also assist to increase the information relating to the statistics and this will further
be helpful to create a better outcome in order to generate a brand image at global level. The
current study is based upon two different topics in which inferential tool will be applied that
helps to determine about usage of different tools over it.
METHODOLOGY AND DATA
It is necessary for the scholar to choose the methodology according to the research
questions which in turn assist to accomplish the set aim and objectives. The methodology for the
present study is as mentioned below:
Research type: Generally, there are two types of research i.e. qualitative and
quantitative. For the current report only quantitative research type has been adopted which in
turn deals with figures and facts and also help to understand the trend (Hacker and et.al., 2022).
In the context of present research, scholar actually uses tools and technique in order to
understand the relationship between factors. Thus, deal with figures and numbers, the selected
type has been accepted over other.
Research approach and philosophy: As per the chosen research type, scholar adopted
only interpretivism philosophy and deductive research approach that helps to determine the
issues. With the help of this approach, researcher can easily answer the research questions and
also assist to generate a better outcome (Garrison, 2022). That is why, to conclude the answer
and make the research more effective, the chosen approach will be beneficial.
Data collection: There are two ways through which the data can be collected and in the
current report, only secondary data collection methods has been used which assist to meet the set
research questions. In this, the data are already collected from the official sites and this in turn
assist meet the defined aim. Also, in order to support the results, relevant books and articles has
been selected to meet the set aim.

Data analysis: Once the data has collected, it is necessary for the researcher to analyse
the information in order to reach to a valid results. There are two ways through which the data
can be analysed which includes Thematic and SPSS. For the present research, only SPSS as a
data analysis method has been adopted in which scholar can generate the valid result. With the
help of this software, the study uses different tools that assist to create a better consequence and
answer the investigation queries. With the help of such analysis, the scholar can present the
findings in an actual way in order to reach a valid conclusion.
ANALYSIS AND FINDINGS
Task 1: relationship between casual factors and effect on probability of ability salary
Null hypothesis: There is no statistical difference between the mean value of salary and casual
factors (publication, position, universities, state)
Alternative hypothesis: There is a statistical difference between the mean value of salary and
casual factors (publication, position, universities, state)

Interpretation: With the help of model summary statistics, it has been identified that the
correlation between both variable is moderate which means that when the value of constant
factors changes, there will be 65% chances that salary affects. Also, according to R square value,
it entails that when the publication and position changes there is 43% change identified over
salary and this reflected that salary actually affected from the casual factors (Goolab, 2021).
Further, according to anova table, it has been identified that there is a significance
difference between the mean value of salary and casual factors. As a result, alternative
hypothesis is accepted over the other because the value of significance difference is 0.00 which
is lower than 0.05.
By applying Durbin Watson test whose value is 1.3 signposted that there is a positive
autocorrelation between the variables. Thus, it has been shows that both factors will run in a

similar direction. Moreover, according to scatter plot and residual statistics, it can be interpreted
that variable are constant across the predictor and thus, the observed value do not varied more
easily. Thus, it has further evaluated by collinearity statistics under a coefficient table that the
value of VIF is in between 0 to 10 in all cases rather than professor. Therefore, there is a need to
remove the outlier from professor case in order to fall the same into 0 to 10. Rest of the others
shows the positive relationship between the factors.
In accordance with the error of distribution, it can be reflected through the graphs i.e.
little circles are actually follows the normality line and as a result, there is no specific drastic
deviation identified between the factors. Also, it can be stated that there is a need to understand
the ways through which the issues can be determined and complete the same.
Task 2: Impact of casual factors like size and cooperation upon the possibility of innovation in
UK companies.
Factor analysis
With the help of factor analysis, it has been identified that there is a substantial alteration
between the sample size because the value of p is 0.00 < standard criteria i.e. 0.05. Also, as per
Kaiser Meyer test, it can be stated that the value is 0.74 which is high and that is why, the model
is adequate to calculate and this in turn determine the strong correlation between different
variables. Also, in accordance with Bartlett test of Spherecity it has been reflected that the
selected sample size entails about the valid results and that is why, it shows best outcome as
well. This in turn reflected that scholar can generate a better results and analyse the research
questions as well.

One way anova
Null hypothesis: There is no difference between the mean value of innovation and size as well as
cooperation within UK companies.
Alternative hypothesis: There is a difference between the mean value of innovation and size as
well as cooperation within UK companies.
Interpretation: By applying one way anova test, it has interpreted that there is a
difference between the mean of innovation in UK companies and casual factors because the
value of significance difference is 0.00 which is lower than standard criteria. Therefore, it can be
reflected that with the change in the casual factors, the chances of innovation among UK
companies automatically changes because the difference between the mean value is high and that
is a minor change has a direct impact over an innovation within a companies.
Cluster analysis

In accordance with the final cluster, it has been identified that bunch 1 to 15 are differ
from the profile and that is why, it can be stated that companies in UK need to work upon the
innovation so that effective results can be generated. As cluster 2 has a uppermost cluster and
that is why, it determines the opinions in a collection in more effectively as compared to others
so that best outcome can be generated.
DISCUSSION
Through the above calculations it has been identified that salary have a direct impact over
the casual factors as proved in regression test. However, there are many other external factors
that also cause a direct influence over the business presentation and this in turn reflected that
while deciding the salary, there is a need to consider the factors that helps to analyse whether the
person should actually offer the salary or not (Acharya and et.al., 2022). Therefore, by

considering more casual factors will also assist to derive effectual results. Further, with the help
of one way anova, it has been identified that there is a change between the mean group of casual
innovation factors of UK companies and size and cooperation. This in turn reflected that
innovation within a small companies will be beneficial in order to attract new range of customers
and this also helps to create a better outcome. However, Sancho-Zamora and et.al., (2022)
explained that in small companies innovation is consider the only key of success because it help
to attract the customers whereas in large companies, the chances of invention is higher that is
why, small companies are more focused upon the innovation that is why, the relationship is
positively identified.
CONCLUSION
Through the above study it has been identified that with the help of statistics, companies
can be easily forecasting and that is why, through quantitative method, the researcher also
determine the interdependency upon variables. Through the regression analysis, it has been
further evaluated that salary and other factors are loosely interrelated with each other and that is
why, companies need to consider the factors while evaluating the salary. Further, through one
way anova method, it has been evaluated that there is a direct association between the origination
of UK companies and other casual factors. This in turn reflected that there is a need to improve
the overall performance and that is why, companies need to indulge in different factors that assist
to create a better outcome and improve business performance.

REFERENCES
Books and Journals
Acharya, C. and et.al., 2022. Managing information for innovation using knowledge integration
capability: The role of boundary spanning objects. International Journal of Information
Management. 62. p.102438.
Garrison, M., 2022. Critical Research Methodology: A Realist Approach. In Handbook of
Critical Approaches to Politics and Policy of Education (pp. 53-64). Routledge.
Goolab, M., 2021. Factors affecting your salary package. Personal Finance
Magazine, 2021(490), pp.20-20.
Hacker, N., and et.al., 2022. Centering Oppression in Research Methodology Toward
Developing Interventions to Address Health Inequities. Journal of Pediatric Psychology.
Sancho-Zamora, R. and et.al., 2022. The Impact of Absorptive Capacity on Innovation: The
Mediating Role of Organizational Learning. International Journal of Environmental
Research and Public Health. 19(2). p.842.