Analyzing Data & Testing Hypotheses: Research & Communication

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This assignment focuses on data analysis and research communication, addressing the validity of summary data, the reflection of customer perceptions through surveys, types of quantitative data, and hypothesis testing methods. It begins by critiquing the use of a single score from a Likert scale as a data summary, advocating for frequency distribution instead. It questions whether data collected from online surveys accurately represents all customers' perceptions, considering factors like website access and technical skills. The assignment identifies data types (nominal, ordinal, ratio, interval) in various scenarios, such as gender, Fahrenheit thermometers, Kelvin thermometers, customer purchases, and bank account balances. Finally, it explores different approaches to testing a hypothesis, including descriptive non-experimental, quasi-experimental, and experimental studies. The document provides references to support its analysis and conclusions. Desklib offers this and other solved assignments to aid students.

Professional Research and Communication
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Contents
Assignment 1............................................................................................................................................... 3
1 Explain why this value is not a valid summary of the data collected. Suggest a more valid way of
representing the data. Justify your response................................................................................................ 3
2 This question continues from question 1. Let’s assume that the survey is not necessarily answered by
every customer. If a customer wishes to fill out the survey they need to go to the relevant web page on the
store’s web site. This way the store can automate the collection and analysis of data. Does the data
collected provide a true reflection of the perceptions of all of the store’s customers? Why or why not?
Justify your answer...................................................................................................................................... 4
3 We discussed four types of quantitative data in class – nominal, ordinal, ratio and interval. What types
of data are collected from each of the following questions? Justify your answer........................................5
4 Explain how you could test this hypothesis in each of the following ways:.............................................6
References:.................................................................................................................................................. 7
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Assignment 1
1 Explain why this value is not a valid summary of the data collected. Suggest a more valid
way of representing the data. Justify your response.
Likert scale is basically used to research the questionnaires of the employees. The summaries
data in a single score is 3.19 which is not the valid summary for data collected because this
approach gives the customers many choices as it is the uni dimensional but the space between
those choices are cannot be equidistant. So this data collected cannot be measure the true
perception of the service by the customers at the local store. The average response on the Likert
scale is often difficult to distinguish so we couldn’t find the people respond on a particular scale.
The survey of this response can’t reflect the actual response also.
Frequency distribution is the more appropriate way of distributing the data as it shows the list on
a table or a graph of the various outcomes of data (Dumais, et.al., 2016). The table summarizes
the data of distribution of table to the frequency or the count of the values. In this method the
summarize data collected is divided into an exclusive classes and number of outcomes in the
survey. This method is the best approach of showing the inappropriate data in a proper form.
This methods shows large data like the survey of 100 customers in a concise manner and the
comparison can be done easily with the help of this method.
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2 This question continues from question 1. Let’s assume that the survey is not necessarily
answered by every customer. If a customer wishes to fill out the survey they need to go to
the relevant web page on the store’s web site. This way the store can automate the
collection and analysis of data. Does the data collected provide a true reflection of the
perceptions of all of the store’s customers? Why or why not? Justify your answer.
The data provided gives the true and clear reflection of all the customers’ perception on a store
website or a webpage it properly shows the services or the product and tells the true direction of
the business. The customers get to know about the actual store and them analysis the data
through the website.
But many of the stores don’t even have the website and most of them don’t reveal their survey in
that year (Dumais, et.al., 2016). They used to reveal the current perception of the customers in
the next year. Many of stores are too small so they don’t even warrant a website or webpage so
they can’t show the data. The analysis and the collection of the data can be done through the
websites or WebPages when the customers have the knowledge of the technical skills. So the
collection of the data is quite difficult in the webpage and website.
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3 We discussed four types of quantitative data in class – nominal, ordinal, ratio and
interval. What types of data are collected from each of the following questions? Justify
your answer.
Gender: Gender is the type of the nominal data which is used for the measurement scale. It helps
in labeling the variables without the use of the quantitative value. The other name of the nominal
scale is labels. Gender doesn’t have any numerical significance they are simply represented as
male or female (Hussein,2015). Gender is the dichotomous scale which is the sun type of the
nominal scale which specifies two categories male or female.
Fahrenheit thermometers: Fahrenheit thermometers are the type of internal data. Internal data
is basically used to measure the attributes between the two extremes along an arbitrator scale
(Clement, et.al., 2015). This data is used to measure the position which is equidistant from one
another. Fahrenheit thermometers differs from zero degrees is arbitrator on interval scales.
Kelvin thermometers: The Kelvin scale is come under the ratio scale of quantitative data. The
difference between the Kelvin values is meaningful in this scale. In this scale there is the
absolute zero and the values can be ordered, doubles and have a meaningful difference.
The number of items a customer buys: It is the type of the discrete numerical variable which
is used to measure the variables or count the whole number. It is the numerical variable which is
used to measure the number of items. In this the number of fractions is not meaningful if it is in
the fraction.
Bank account balances: It is the type of ordinal data which can be ranked or ordered. The
numbers and the amounts can be ranked or ordered so bank account falls under this category.
This helps in arranging the various categories in meaningful order (Hussein,2015). It is the
numerical description of the person and the use of the eliminatory social statistics.
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4 Explain how you could test this hypothesis in each of the following ways:
a. As a descriptive non-experimental study: It is the research which lacks in the manipulation
of the independent variables and the orders of condition, or both. The test of this hypothesis can
be done by applying the participant to fulfill that condition. This can be done by analyzing how
the people will perform when they drink the orange juice three times a day. Then they study
about the mathematical and verbal intelligence. Does this research does damage to any person,
after analyzing all this study could be measured. In this study observation, interviews,
questionnaires are conducted to know the response.
b. A quasi experimental study: It is the study which is used to help the estimate the impact of
the estimation on the people. It resembles and it is the relation between the correlation studies
and true experiments (Pulerwitz, et.al., 2015). In this experiment it is found that three glasses of
orange juice per day for four times in a week can boost up the mind of the performer and helps in
increasing the stamina, so the player performs better. In this method true experimental research
can’t be found.
c. An experimental study: An experimental study is the study which is considered with the true
results in the laboratory, field and natural. Drinking orange juice three times a day will be
applied on laboratory and gives the result that the players should drink the juice four days in a
week so that the better performance of the player can be figure out. It helps in determining the
casual affects on the certain conditions on a particular item (Bastiaensens, et.al., 2015).
The experimental theory gives the best firmest evidence because it is the best confident theory
which provides gold standard for determining the casual effects. This methods gives the more
confident results than the other method.
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References:
 Bastiaensens, S., Vandebosch, H., Poels, K., Van Cleemput, K., Desmet, A., & De
Bourdeaudhuij, I. (2014). Cyberbullying on social network sites. An experimental study
into bystanders’ behavioural intentions to help the victim or reinforce the
bully. Computers in Human Behavior, 31, 259-271.
 Clement, S., Schauman, O., Graham, T., Maggioni, F., Evans-Lacko, S., Bezborodovs,
N., ... & Thornicroft, G. (2015). What is the impact of mental health-related stigma on
help-seeking? A systematic review of quantitative and qualitative studies. Psychological
medicine, 45(1), 11-27.
 Dumais, S., Cutrell, E., Cadiz, J. J., Jancke, G., Sarin, R., & Robbins, D. C. (2016,
January). Stuff I've seen: a system for personal information retrieval and re-use. In ACM
SIGIR Forum (Vol. 49, No. 2, pp. 28-35). ACM.
 Hussein, A. (2015). The use of triangulation in social sciences research: Can qualitative
and quantitative methods be combined?. Journal of comparative social work, 4(1).
 Pulerwitz, J., Hughes, L., Mehta, M., Kidanu, A., Verani, F., & Tewolde, S. (2015).
Changing gender norms and reducing intimate partner violence: results from a quasi-
experimental intervention study with young men in Ethiopia. American Journal of Public
Health, 105(1), 132-137.
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