Engineering Data Analysis Learning Mateial (1 week).pdf

AGUSAN DEL SUR STATE COLLEGE OF AGRICULTURE AND TECHNOLOGY
COLLEGE OF ENGINEERING AND INFORMATION SCIENCES
Bunawan, Agusan del Sur
ENGINEERING DATA
ANALYSIS
Learning Material
PREPARED BY:
JANICE C. PUSPOS, ECE
INSTRUCTOR
This is not for sale!

VISION
ASSCAT as the premier agro-industrial Higher Education
Institution in Caraga Region capable of producing morally
upright, competent and globally
competitive human resource capable to effectively undertake
and implement sustainable development.
MISSION
ASSCAT shall primarily provide higher professional, technical
and special instructions for special purposes and to promote
research and extension services, advanced studies and
progressive leadership in agriculture, education,
forestry, fishery, engineering, arts and sciences and other
relevant fields.
QUALITY POLICY
Agusan del Sur State College of Agriculture and Technology’s
vision to be a premier agro-industrial Higher Education
Institution in Caraga Region is fostered by the following
principles:
· sustaining quality education experience and
community engagement;
· encouraging optimum resource management;
· developing an environment that is conducive for
intellectual and personal growth; and
· generating relevant knowledge through innovative
thinking.
To continually improve our Quality Management System, we
commit to comply with all applicable requirements and provide
service excellence in our four-fold functions.

AGUSAN DEL SUR STATE COLLEGE OF AGRICULTURE AND TECHNOLOGY
San Teodoro, Bunawan, Agusan del Sur College of Engineering
e-mail address: op@asscat.edu.ph and Information Sciences
website: www.asscat.edu.ph; mobile no: +639486379266 email address: asscatceis01@gmail.com
LEARNING GUIDE
AY 2020-2021, 1st
semester
Course No.: Math 18; Math 4; Math 68
Course Title: Engineering Data Analysis
No. of Hours: 3 hours/week
Course Description: This course is designed for undergraduate engineering students with emphasis on
problem solving related to societal issues that engineers and scientists are called upon to solve. It introduces
different methods of data collection and the suitability of using a particular method for a given situation. The
relationship of probability to statistics is also discussed, providing students with the tools they need to
understand how "chance" plays a role in statistical analysis. Probability distributions of random variables and
their uses are also considered, along with a discussion of linear functions of random variables within the context
of their application to data analysis and inference. The course also includes estimation techniques for unknown
parameters; and hypothesis testing used in making inferences from sample to population; inference for
regression parameters and build models for estimating means and predicting future values of key variables
under study. Finally, statistically based experimental design techniques and analysis of outcomes of
experiments are discussed with the aid of statistical software.
Learning Objectives:
At the end of this course, the students are expected to:
1. Apply statistical methods in the analysis of data
2. Design experiments involving several factors
Course Requirement:
To successfully complete the course, you are required to perform/conduct all the learning activities
specified in each topic. Overall assessment of the outputs will be based on the following:
Grading System:
Criterion Reference
Student’s Output 60%
Term Exam 40%
TOTAL 100%
Semestral Grade
Midterm 40%
Final 60%
TOTAL 100%
References:
1. D. Montgomery and G. Runger (2003) Applied Statistics and Probability for Engineers, 3rd
edition
2. W.J. DeCoursey (2003). Statistics and Probability for Engineering Applications with Microsoft Excel
3. S. Brandt (2014). Data Analysis, 4th
edition
4. H. Guerrero (2019). Excel Data Analysis, 2nd
edition
5. T. Agami Reddy (2011). Applied Data Analysis and Modeling for Energy Engineers and Scientists
Assessment Weight (%)
1 6.25
2 6.25
3 6.25
4 6.25
5 6.25
6 6.25
7 6.25
8 6.25
9 6.25
10 6.25
11 6.25
12 6.25
13 6.25
14 6.25
15 6.25
16 6.25
TOTAL 100

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Engineering Data AnalysisEngr.
Janice C. Puspos
College of Engineering and Information Sciences
Agusan del Sur State College of Agriculture and Technology
Topic 1 : OBTAINING DATA
1.1. Methods of Data Collection
1.2. Planning and Conducting Surveys
1.3. Planning and Conducting Experiments: Introduction to Design of Experiments
Learning Activity per Topic:
1. Discuss the Overview of the Basic Statistics
2. Discuss the methods of collecting data through surveys, and experiments.
3. Explain basic ways on planning and conducting experiments through different statistical designs.
Lecture Notes:
METHODS OF DATA COLLECTION
 Data collection is the process of gathering and measuring information on variables of interest, in an
established systematic fashion that enables one to answer stated research questions, test hypotheses,
and evaluate outcomes.
TYPES OF DATA
1. PRIMARY DATA - data which are collected a fresh and for the first time and thus happen to be
original in character and known as PRIMARY DATA.
2. SECONDARY DATA - data which have been collected by someone else and which have already been
passed through the statistical process.
 METHODS OF DATA COLLECTION: PRIMARY DATA
1. Observation
2. Interview
3. Questionnaire
4. Case Study
5. Survey
 METHODS OF DATA COLLECTION: PRIMARY DATA OBSERVATION
 Observation method is a method under which data from the field is collected
with the help of observation by the observer or by personally going to the field.
ADVANTAGES DISADVANTAGES
Subjective bias eliminated Time consuming
Current information Limited information
Independent to respondent’s variable Unforeseen factors
TYPES OF OBSERVATION STRUCTURED and UNSTRUCTURED
1. Structured Observation - when observation is done by characterizing style of
recording the observed information, standardized conditions of observation, definition of the
units to be observed, selection of pertinent data of observation.
Example: An auditor performing inventory analysis in store

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Janice C. Puspos
2. Unstructured Observation - when observation is done without any thought before
observation.
Example: Observing children playing with new toys.
TYPES OF OBSERVATION PARTICIPANT and NON-PARTICIPANT
1. Participant - when the Observer is member of the group which he is observing.
Advantages: 1. Observation of natural behavior
2. Closeness with the group
3. Better understanding
2. Non-participant - when observer is observing people without giving any
information to them.
Advantages: 1. Objectivity and neutrality
2. More willingness of the respondent
TYPES OF OBSERVATION CONTROLLED and UNCONTROLLED
1. Controlled - when the observation takes place in natural condition. It is done to get
spontaneous picture of life and persons.
2. Uncontrolled - when observation takes place according to definite pre-arranged
plans, with experimental procedure then it is controlled observation generally done in
laboratory under controlled condition.
 METHODS OF DATA COLLECTION: PRIMARY DATA INTERVIEW METHOD
 INTERVIEW METHOD - This method of collecting data involves
presentation or oral-verbal stimuli and reply in terms of oral-verbal responses.
 Interview Method is an oral verbal communication where interviewer asks
questions (which are aimed to get information required for study) to
respondent.
TYPES OF INTERVIEW
• Personal interviews: The interviewer asks questions generally in a face to face
contact to the other person or persons.
• Structured interviews: in this case, a set of pre- decided questions are there.
• Unstructured interviews: in this case, we don’t follow a system of pre-determined
questions.
• Focused interviews: attention is focused on the given experience of the respondent
and its possible effects.
• Clinical interviews: concerned with broad underlying feelings or motivations or with
the course of individual’s life experience, rather than with the effects of the specific
experience, as in the case of focused interview.
• Group interviews: a group of 6 to 8 individuals is interviewed.
• Qualitative and quantitative interviews: divided on the basis of subject matter i.e.
whether qualitative or quantitative.
• Individual interviews: interviewer meets a single person and interviews him.
• Selection interviews: done for the selection of people for certain jobs.
• Depth interviews: it deliberately aims to elicit unconscious as well as other types of
material relating especially to personality dynamics and motivations.
• Telephonic interviews: contacting samples on telephone.
 METHODS OF DATA COLLECTION: PRIMARY DATA QUESTIONNAIRE
METHOD
 QUESTIONNAIRE METHOD - This method of data collection is quite popular,
particularly in case of big enquiries.
 The questionnaire is mailed to respondents who are expected to read and
understand the questions and write down the reply in the space meant for the purpose
in the questionnaire itself. The respondents have to answer the questions on their own.

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Janice C. Puspos
Low cost even if the geographical area is too large Low rate of return of duly filled questionnaire.
Answers are in respondent’s word so free from bias. Slowest method of data collection.
Adequate time to think for answers. Difficult to know if the expected respondent have
filled the form or it is filled by someone else.
Non approachable respondents may be conveniently
contacted.
Large samples can be used so results are more
reliable.
 METHODS OF DATA COLLECTION: PRIMARY DATA CASE STUDY METHOD
 CASE STUDY METHOD is essentially an intensive investigation of the particular
unit under consideration.
They are less costly and less time-consuming; they
are advantageous when exposure data is expensive
or hard to obtain.
They are subject to selection bias
They are advantageous when studying dynamic
populations in which follow-up is difficult.
They generally do not allow calculation of
incidence (absolute risk).
 METHODS OF DATA COLLECTION: PRIMARY DATA SURVEY METHOD
 SURVEY METHOD is one of the common methods of diagnosing and solving of
social problems is that of undertaking surveys.
Relatively easy to administer Respondents may not feel encouraged to provide
accurate, honest answers
Can be developed in less time (compared to other
data-collection methods)
Surveys with closed-ended questions may have a
lower validity rate than other question types.
Cost-effective, but cost depends on survey mode Data errors due to question non-responses may
exist.
 SECONDAY DATA: SOURCES OF DATA
 Publications of Central, state, local government
 Technical and trade journals
 Books, Magazines, Newspaper
 Reports & publications of industry, bank, stock exchange
 Reports by research scholars, Universities, economist
 Public Records
FACTORS TO BE CONSIDERED BEFORE USING SECONDARY DATA
 Reliability of data – Who, when, which methods, at what time etc.
 Suitability of data – Object, scope, and nature of original inquiry should be studied, as if the
study was with different objective then that data is not suitable for current study
 Adequacy of data– Level of accuracy

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Janice C. Puspos
 Area differences then data is not adequate for study
SELECTION OF PROPER METHOD FOR COLLECTION OF DATA
 Nature, Scope and object of inquiry
 Availability of Funds
 Time Factor
 Precision Required
DESIGNING A SURVEY
 Surveys can take different forms. They can be used to ask only one question or they
can ask a series of questions. We can use surveys to test out people’s opinions or to
test a hypothesis.
When designing a survey, the following steps are useful:
1. Determine the goal of your survey: What question do you want to answer?
2. Identify the sample population: Whom will you interview?
3. Choose an interviewing method: face-to-face interview, phone interview, self-
administered paper survey, or internet survey.
4. Decide what questions you will ask in what order, and how to phrase them. (This is
important if there is more than one piece of information you are looking for.)
5. Conduct the interview and collect the information.
6. Analyze the results by making graphs and drawing conclusions.
Example:
Example:
1. Martha wants to construct a survey that shows which sports students at her school like
to play the most.
Step 1: List the goal of the survey
Step 2: What population should she interview?
Step 3: How should she administer the survey?
Step 4: Create a data collection sheet that she can use to record her results
Step 1: GOAL
The goal of the survey is to find the answer to the question: “Which sports do students at
Martha’s school like to play the most?”
Step 2: POPULATION
A sample of the population would include a random sample of the student population in
Martha’s school. A good strategy would be to randomly select students (using dice or a random
number generator) as they walk into an all-school assembly.
Step 3: METHODS
Face-to-face interviews are a good choice in this case. Interviews will be easy to conduct
since the survey consists of only one question which can be quickly answered and recorded, and
asking the question face to face will help eliminate non-response bias.
Step 4: DATA
1. Juan wants to construct a survey that shows how many hours per week the average
student at his school works.
Step 1: List the goal of the survey
Step 2: What population should she interview?
Step 3: How should she administer the survey?
Step 4: Create a data collection sheet that she can use to record her results

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Janice C. Puspos
Step 1: GOAL
The goal of the survey is to find the answer to the question “How many hours per week do
you work?”
Step 2: POPULATION
Juan suspects that older students might work more hours per week than younger students.
He decides that a stratified sample of the student population would be appropriate in this case. The
strata are grade levels 9th through 12th. He would need to find out what proportion of the students
in his school are in each grade level, and then include the same proportions in his sample.
Step 3: METHODS
Face-to-face interviews are a good choice in this case since the survey consists of two short
questions which can be quickly answered and recorded.
Step 4: DATA
THE BASIS OF CONDUCTING AN EXPERIMENT
1. With an experiment, the researcher is trying to learn something new about the world, an explanation of
'why' something happens.
2. The experiment must maintain internal and external validity, or the results will be useless.
3. When designing an experiment, a researcher must follow all of the steps of the scientific method, from
making sure that the hypothesis is valid and testable, to using controls and statistical tests
ASSESSMENT 1.
1. Choose a subject matter which you find interesting to research (e.g. COVID-19, flexible learning,
TikTok Saga, etc.). Get to know the data collection methods introduced in topic 1. Formulate three
different aims (related to the chosen subject matter) and define the subject matter in a way that the
research could be made with three of the data collection methods introduced in topic 1. Then, collect
data using the data collection method you chose. (You may encode or write your answer in a clean
sheet of paper)

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Janice C. Puspos

Engineering Data Analysis Learning Mateial (1 week).pdf

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