Name: Jhonna Marie E. Quirao
Course & Year: BSBA-2B
Date: 09, 12, 2023
Professor: Pearly Joy G. Mirasol
MM 104- MARKETING MANAGEMENT MODULE 5
Assessment
1. Explain the importance of data analysis.
Data analysis is essential in research as it helps uncover meaningful patterns,
relationships, and insights from raw data, allowing researchers to draw valid
conclusions and make informed decisions. It enables the identification of trends,
outliers, and correlations, which can lead to the discovery of new knowledge and the
validation of hypotheses. Effective data analysis not only enhances the credibility of
research findings but also guides future investigations and informs evidence-based
decision-making in various fields.
2. What are the different levels of measure of variables?
In research, variables are classified into different levels of measurement, each with its
own characteristics and implications for data analysis. The four primary levels of
measurement are:
1. Nominal Level- Variables at the nominal level are categorical and represent distinct
categories or groups with no inherent order or ranking. Examples include gender,
ethnicity, or types of fruits. Nominal data can be used for qualitative analysis, such
as frequency counts and mode calculations.
2. Ordinal Level- Ordinal variables also represent categories or groups, but they have
a natural order or ranking between them. However, the intervals between values
are not consistent or meaningful. Examples include education levels (e.g., high
school, college, graduate), Likert scale responses (e.g., strongly agree, agree, neutral,
disagree, strongly disagree), or socioeconomic status (e.g., low-income, middleincome, high-income).
3. Interval Level- Interval variables have a consistent interval between values, but
they lack a true zero point. Temperature measured in Celsius or Fahrenheit is a
classic example. While you can perform arithmetic operations like addition and
subtraction with interval data, you cannot say that a value of zero represents the
complete absence of the attribute.
4. Ratio Level- Ratio variables have all the properties of interval variables but also
have a true zero point, indicating the complete absence of the attribute. Examples
include height, weight, age, income, and time. You can perform all arithmetic
operations (addition, subtraction, multiplication, division) with ratio data, and
statistical measures like means, standard deviations, and percentages are
meaningful.
3. What are the different ways of analyzing data.
Descriptive analysis
is a statistical method used to summarize and describe the key characteristics of
a dataset. It provides a snapshot of the data's central tendencies, variability, and
distribution, allowing researchers to gain a preliminary understanding of their data.
Common measures used in descriptive analysis include mean, median, mode, standard
deviation, and various graphical representations like histograms and scatterplots.
Inferential analysis
is a statistical approach used in research to make inferences or draw conclusions
about a population based on a sample of data. It involves the application of various
statistical tests and techniques to assess the significance of observed differences or
relationships in the sample and to determine whether those findings can be generalized
to the larger population from which the sample was drawn. Hypothesis testing,
confidence intervals, and regression analysis are common methods within inferential
analysis, helping researchers assess the reliability and significance of their research
findings.
Activity
Select the appropriate data analysis scheme for your specific research problem in your research
proposal.
Descriptive analysis is used to describe the nature and characteristics of an event or
population under investigation. It is used to describe the characteristics of a variable or
a set of data and/or the variance within the data.
The appropriate data analysis scheme for our specific research problem in our research
proposal is Descriptive Analysis. Descriptive analysis is crucial for our study on
"Customer Satisfaction on Quality Service of Shakey's Pizza: Input to Marketing
Strategy" for several reasons. Firstly, it allows us to paint a clear and comprehensive
picture of the current state of customer satisfaction by summarizing data on factors like
service quality, delivery times, and overall dining experience. Secondly, it helps us
identify key trends and patterns in customer feedback, enabling us to pinpoint areas
where Shakey's excels and areas that require improvement. Lastly, descriptive analysis
serves as the foundation for informed decision-making in our marketing strategy,
providing us with valuable insights to tailor our approach and enhance customer
satisfaction, ultimately boosting Shakey's Pizza's success.