Quality and Statistics | Research Study

Running head: QUALITY AND STATISTICS
Quality and Statistics
Name (First M. Last)
School or Institution Name (University at Place or Town, State)

QUALITY AND STATISTICS
Table of Contents
Introduction.................................................................................................................................3
Demographic essay.....................................................................................................................4
Trends essay................................................................................................................................4
Ranking analysis.........................................................................................................................4
References...................................................................................................................................9
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Introduction
Measurements of some variables and factors such as perception in research study cannot be
distinctively identified. Statistical analysis helps researchers to measure these factors in various
ways, such as using different scales to rate these variables as argued by Aberson (2019). By
these, we obtain the numerical equivalence of these factors. This facilitates the calculation of
various statistical tests and test hypotheses on these variables.
A survey is one of the most powerful statistical methodologies of researching some unknown
factors such as respondent’s expectation and perception in the domain of interest. Questionnaires
are the key components of a survey, as they are used in getting the data of interest from the
respondents as portrayed by Gray (2019). Proper preparation of the survey and the designing of
the questionnaires are required to ensure the correct data is obtained and ensure the objectives of
the study are met.
This study comprises of three parts, the demographic study, trend analysis and ranking
analysis. To understand clearly expectation and perception as portrayed by museum visitors, a
sample survey will be implemented on the visitors coming to visit the museum on a random day.
Visitors will be presented by the questionnaires containing 28 questions measuring the visitor's
expectation s before visiting the museum and visitor's perception after they visit the museum.
Data will be codded in SPSS and descriptive statistics conducted to understand these
underlying factors from a statistical perspective. According to Ang and Van Dyne (2015),
“Descriptive statistics helps to understand the data more clearly before complex analysis has
begun”. The distribution of the variables will also be accessed, to check for any skewness in the
data which might affect the analysis results as illustrated by Meloun and Militky (2011).
Additionally, trends in the data will also be constructed and described using charts and graphs. A
comparison of the visitor’s expectation and perception will be investigated, explained and the
results presented in a ranking analysis table. King and Minium (2008) argue that, with correct
data analysis and understanding of the results, visitor's expectations and perceptions will be
clearly understood and any association between these factors and demographic factors illustrated.
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Demographic essay (in different file)
Trends essay (in different file)
Ranking analysis
As brought out by Moser and Kalton (2017), in statistics and data analysis, the process of
comprehensively analyzing the data and obtaining useful information is very crucial and should
be conducted with clarity and accuracy. Several factors can lead to inaccurate and inconsistent
results during data analysis such as in-correctly collected data. Inaccurate data, very skewed data
as well as sampling bias. Sampling bias refers to the error that occurs when the respondents in
the study are not well sampled from the population. This lead to some cases having a higher
probability of being included in the study.
To avoid these errors, correct sampling should be conducted using the appropriate sampling
methods and data cleaning should be conducted before data analysis (Heeringa et al.2017). The
analysis of the visitor’s expectation and perception in a ranking analysis chart will be computed
and explained. The ranking of the questions will be computed as perceived by the visitors. This
will show which variables tend to more affect the expectations and perception of the visitors as
Ross (2017) argues.
Ranking analysis of the pre-trip expectations for the visitors:
Responsive and assurance: the highest expectation for visitors is the location of the service desk
(5.83) while the most undesirable visitor’s expectation is the interactive display at the museum
(5.15). Tangibility: the highest expectation from visitors is the ticket cancelation process being
convenient (6.09) and the most undesirable expectation is the landscape design is spacious and
pretty. (4.68).
Safety: the data analysis shows that the highest expectation from visitors is the provision of
rooms for deposits, babies, and nursing and (6.13) the most undesirable expectation is the
temporal baggage storage services (6.02). Convenience: the highest expectation from visitors is
the directional signage’s are well illustrated in the parking lots & inside the museums (6.18) and
the most undesirable expectation is the prayer room is close and spacious (5.97).
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Affordability: the variable categorized under the affordability which scored the highest is the
visitor's expectation that the and services at retail shops are affordable (5.97) and the most
undesirable expectation is that food and beverages are affordable and they exist in various types
depending on the visitor's taste (5.87). Empathy: the highest expectation from visitors is toilets
are sufficient (6.43) and the most undesirable expectation is people with special needs have
access to all facilities (6.35).
A comparison of variables and factors in data analysis is important to understand the
underlying relationship between these variables and investigate their difference and similarities
as argued by Ayyub and McCuen (2016). Comparing the visitor’s expectation and perception as
represented by the variables as argued by Lane (2017). The pre-trip expectations and perception
scores prove that the most important variable in measuring the visitor's expectation and
perception is that visitors toilets are sufficient, which is ranked No. 1, this implies that the
general cleanliness of the museum plays a significant role in explaining the perception and
expectation of the visitors. While the most ignored and undesirable item is the outdoor resting
area is mind refreshing (4.56)
Table 1.2 Ranking analysis
The actual questions
and sections
Pre-trip expectations Perception and expectation
N Mean Std.
Deviation
Ranking mean Std.
Deviation
Ranking
Responsive and
assurance
1. The interactive
displays at x museum
offer engaging
information
270 5.15 1.682 22 5.15 1.682 22
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2. The pop-up art
workshops at x
museum are
entertaining
270 5.19 1.541 21 5.19 1.541 21
3. The content of x
museum is attractive 270 5.23 1.504 20 5.23 1.504 20
4. The audio guides at
x museums are clear
and easy to use
270 5.34 1.399 19 5.34 1.399 19
5. The displayed
objects at x museum
are interesting
270 5.23 1.446 18 5.23 1.446 18
6. The service people
at x do not ignore the
needs of visitors
although they are busy
270 5.66 1.050 17 5.66 1.050 17
7.x service staff has a
good attitude in
treating visitors'
problems
270 5.74 .925 16 5.74 .925 16
8.x tour guides have
rich professional
knowledge
270 5.74 1.012 13 5.74 1.012 13
9. The narration said
by x tour guides is easy
to understand
270 5.73 .932 14 5.73 .932 14
10. x service desks
provide good
consulting services
270 5.71 .902 15 5.71 .902 15
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12. The location of x
service desk is near 270 5.83 .909 9 5.83 .909 9
Tangibility
17. The overall
landscape design of x
is spacious and pretty
270 4.68 1.145 24 4.68 1.145 24
18. x outdoor resting
area is mind refreshing 270 4.56 1.331 23 4.56 1.331 23
19. The overall
environment at x is
clean and comfortable
270 5.79 1.000 8 5.79 1.000 8
24. The ticket
cancelation process at
x is convenient
270 6.09 .964 7 6.09 .964 7
Safety
13. There is a
temporary baggage
storage service at x
museum
270 6.02 .892 6 6.02 .892 6
14. There is a room for
baby sitting at x
museum
270 6.13 .918 4 6.13 .918 4
Convenience
21.The ticketing
purchase process at x is
simple
270 6.11 .835 5 6.11 .835 5
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22. In x ,the directional
siganages are well
illustrated in the
parking lots & inside
the museums
268 6.18 .798 3 6.18 .798 3
23. x prayer room is
close and spacious 270 5.97 .846 10 5.97 .846 10
Affordability
16. The products at x
retail shops are
affordable
270 5.94 .880 11 5.94 .880 11
26. Food and beverages
at x are available and
various
270 5.87 1.059 12 5.87 1.059 12
Empathy
27. x toilets are
sufficient 270 6.43 .685 1 6.43 .685 1
28. At x museum,
people with special
needs have access to all
facility zones
270 6.35 .751 2 6.35 .751 2
Valid N (listwise) 270
The analysis of the entire visitor’s expectation and perception in this research study have been
categorized into two parts, the overall expectation, and the overall visitor’s perception. A 7 point
scale was used to measure the visitor’s perception and expectations after visiting the museum
and before visiting the museum (Weaver et al.2017). The presentation of the report has been
divided into three main parts, the demographic study, trend analysis, and ranking analysis
generally the overall visitor's expectation: the total number of people whose score is 3 or above is
230, covering 88.7%. It indicates that the tourists have an overall high expectation for the
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Museum before their visit. Additionally, overall perception: the total number of people whose
score is 3 or above is 223, covering 85.3%. It indicates that the visitors have a higher perception
before their actual visit to the museum.
The analysis results put through several insights and directions that can be employed by the
museum management to ensure an increased number of visitors and ensure visitor's expectations
are meet as argued by George and Mallery (2016). The museum management should employ
various strategies, such as museum marketing using different platforms to ensure they reach as
many visitors as possible. Additionally, the museum should introduce various activities in the
museum to attract different categories of people.
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References
Aberson, C. L. (2019). Applied power analysis for the behavioral sciences. Routledge.
Gray, D. E. (2019). Doing research in the business world. Sage Publications Limited.
Ang, S., & Van Dyne, L. (2015). Handbook of cultural intelligence: Theory, measurement, and
applications. Routledge.
Berry, W. (2018). Understanding multivariate research: a primer for beginning social scientists.
Routledge.
Berry, W. (2018). Understanding multivariate research: a primer for beginning social scientists.
Routledge.
Gray, D. E. (2019). Doing research in the business world. Sage Publications Limited.
Moser, C. A., & Kalton, G. (2017). Survey methods in social investigation. Routledge.
Heeringa, S. G., West, B. T., & Berglund, P. A. (2017). Applied survey data analysis. Chapman
and Hall/CRC.
Ross, S. M. (2017). Introductory statistics. Academic Press.
Lane, D. M., Scott, D., Hebl, M., Guerra, R., Osherson, D., & Zimmer, H. (2017). An
Introduction to Statistics. Rice University.
Weaver, K. F., Morales, V. C., Dunn, S. L., Godde, K., & Weaver, P. F. (2017). An introduction
to statistical analysis in research: with applications in the biological and life sciences. John
Wiley & Sons.
George, D., & Mallery, P. (2016). IBM SPSS statistics 23 step by step: A simple guide and
reference. Routledge.
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Ayyub, B. M., & McCuen, R. H. (2016). Probability, statistics, and reliability for engineers and
scientists. CRC press.
Meloun, M., & Militky, J. (2011). Statistical data analysis: A practical guide. Woodhead
Publishing, Limited.
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