Analyzing Trends in Museum Visitor Data: Survey and Demographics

This report analyzes trends in museum visitor data collected through a survey. The analysis focuses on identifying patterns and correlations between demographics and visitor satisfaction levels. The study examines responses from 270 participants, exploring the distribution of demographics such as gender, age, and marital status, presented with pie charts. The report further investigates trends, for example, how different age groups perceive interactive screens or outdoor environments. A ranking analysis compares pre-trip expectations with post-visit experiences, providing insights into visitor satisfaction. The findings highlight key areas for museum management to improve services and enhance the visitor experience, including staff attitude, food prices and variety, and babysitting room availability. The data reveals that the age group 18-24 tend to love the display screen more as compared to the age groups with a mean of 6.31 and the above 50 age group are not interested in the display with a mean of 2.08. Additionally, females tend to believe that the service desk has better services with a mean of 5.94 as compared to men with a mean of 5.57. The retired ground is more contented by the food prices and varieties in the museum with a mean of 6.42 while the student is less contented with a mean of 5.72. Consequently, the married respondents are more concerned with the presence of babysitting rooms with a mean of 6.30 as compared to the single respondents with a mean of 6.03. Finally, another trend-worthy noting, the retired group of respondents are less contented with the way visitors are treated at the museum and the staff’s altitude with a mean of 4.74 while students are more contented with the staff's attitude and how visitors are being treated.

Running head: TRENDS IN THE DATA
Trends in Data
Name (First M. Last)
School or Institution Name (University at Place or Town, State)

TRENDS IN THE DATA
Trends in data analysis refer to the existent of distinctive patterns in the data under
investigation. Additionally, trends are used in complex data analysis models especially in time
series analysis as well as in prediction. King and Minium (2008) argue that frequency tables can
also depict trends in data by clearly analyzing the frequency scores of each category in a
variable. The questions presented to the visitors in the museum will be used to check for the
trends described by how the respondents responded to the questions. Precisely, we are
investigating any association between the variables in the dataset as this will indicate the
existence of these trends.
Gray (2019) argues that tends in statistical data analysis can be investigated through the use of
statistical charts and graphs. There also exist some statistical techniques that are used to deliver
any trends in data. The direction of the data and the data variables can be outlined by computing
these trends. When dealing with categorical data analysis, trend analysis techniques differ from
continuous data as argued by Nardi (2018). Chi-square test of independence and contingency
tables are used to compute trends in the categorical data analysis as portrayed by Agresti
(2018). Correlations, t-tests, and ANOVA can also be used to evaluate trends in the scale and
discrete data sets. Data analysis shows that the age group 18-24 tend to love the display screen
more as compared to the age groups with a mean of 6.31. The above 50 age group are not
interested in the display with a mean of 2.08.
Additionally, females tend to believe that the service desk has better services with a mean of
5.94 as compared to men with a mean of 5.57. The retired ground is more contented by the food
prices and varieties in the museum with a mean of 6.42 while the student is less contented with a
mean of 5.72. Consequently, the married respondents are more concerned with the presence of
babysitting rooms with a mean of 6.30 as compared to the single respondents with a mean of
6.03.
Finally, another trend-worthy noting, the retired group of respondents are less contented with
the way visitors are treated at the museum and the staff’s altitude with a mean of 4.74 while
students are more contented with the staff's attitude and how visitors are being treated. The
distribution noticed in the dataset from the respondent's perception and expectation forms a rich
background for making decisions and strategies to improve the services offered in the museum
by the management team.

TRENDS IN THE DATA
References
Agresti, A. (2018). An introduction to categorical data analysis. Chambers, J. M.
(2017). Graphical methods for data analysis: 0. Chapman and Hall/CRC.
Gray, D. E. (2019). Doing research in the business world. Sage Publications Limited.
King, B. M., & Minium, E. W. (2008). Statistical reasoning in the behavioral sciences. John
Wiley & Sons Inc.
Nardi, P. M. (2018). Doing survey research: A guide to quantitative methods. Routledge.