University Research and Communication Assignment: Data Analysis

This document presents a comprehensive analysis of a professional research and communication assignment. It addresses the validity of data summarization methods, distinguishing between adding customer counts and percentages. The assignment explores how survey data can reflect or misrepresent customer perceptions, considering factors such as customer engagement and satisfaction. It also classifies data types, differentiating between nominal (gender), interval (temperature), ordinal (number of items), and ratio (bank balances) scales. Furthermore, the document outlines different study types, including descriptive non-experimental, quasi-experimental, and experimental studies, emphasizing the strength of evidence each provides. The solution demonstrates a clear understanding of research methodologies and data analysis techniques, providing valuable insights for students studying business development.

Running head: PROFESSIONAL RESEARCH AND COMMUNICATION
Professional Research and Communication
Name of the Student
Name of the University
Author’s Note

1PROFESSIONAL RESEARCH AND COMMUNICATION
Answer to [1]
As per the provided situation, it can be said that there are 100 customers and all of them
provides response of the survey. The scores will be represented as strongly disagree, disagree,
unsure, agree and strongly agree. Two types of processes have been shown in the situation. In the
first situation, it is 100 if all the number of customers is added up. On the other hand, it will be
100% in case the total percentage of responses is added up. Thus, it can be seen that it is a
correct and effective process to summaries the data. However, in case of the second situation, it
can be seen that the number of customers in each slot is multiplied with the number of ranks. For
this reason, the total number of surveys customers becomes 319. This is wrong information, as
the total number of surveyed customers is 100. For this reason, this process fails to provide the
valid summary. In this reason, it needs to be mentioned that the first method is more valid
process to present the data as it provides the actual and correct value of the customers and values.
Answer to [2]
From the provided situation, it can be seen that the customers can fill out the survey from
the store’s website. In this regard, it needs to be mentioned that in some situations, the collected
data from the survey do not reflect the true perception of the customers; and in some situations,
the collected data from the survey do reflect the true perception of the customers. There are
many reasons of this. It can be happened that the customers fill the survey out of fun. Thus, in
this case, the survey will not reflect the true intention of the customers. There are situations
where the customer is extremely happy with the product or service or is not satisfied with the
products and services of the company. In these situations, the customers may share their
satisfaction or dissatisfaction by taking participation in the survey. In this cases, the data

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collected will reflect the true perception of the customers. Thus, based on the above analysis, it
can be said that collected data does not always reflect the true perception of the customers.
Answer to [3]
In case of Gender, nominal data are collected. Nominal data are collected as gender is
considered as categorical variable that have two categories; they are male and female. In
addition, there is not any intrinsic ordering to the categories.
In case of Fahrenheit thermometers and Kelvin thermometers, interval data will be
collected. Temperature is a kind of element that is used to illustrate an interval scale. Thus,
interval data will be collected.
In case of the number of items a customer buys, ordinal data will be collected. Ordinal
variables helps to categorize different kinds of values. Thus, in this case, ordinal data will be
collected.
In case of bank account balances, ratio scale type of data will be collected. Ratio scale
variables are considered as interval variables. In this case, zero (0) measurement indicates that
there is not any balance left in the bank. This same theory is applicable for the bank balances.
Answer to [4]
In case of descriptive non-experimental study, predictor variable can be seen. With the
help of these variables, the hypothesis can be tested in a descriptive way. For this reason, case
study can be developed to test the hypothesis. Quasi experiment study is the next step of
descriptive non-experimental study. In this case, variables are taken into consideration; the
variables are three times per week and four days each week. However, in the experimental study,

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the hypothesis is tested in a proper basis, as this is the combination of above two steps. Thus, an
experimental study will provide firmest evidence.