ENGINEERING DATA ANALYSIS
FRAMEWORK OF STATISTICAL ANALYSIS
PLANNING
COLLECTION OF DATA
ORGANIZATION AND
PRESENTATION OF DATA
ANALYSIS OF COLLECTED
DATA
INTERPRETATIONS AND
CONCLUSIONS
RECOMMENDATIONS
BASED ON CONCLUSIONS
A. PLANNING
 Starts with a concise and clear definition of the problem
 Identify the target population and important factors that affect the problem or that
may contribute to its solution
 Choose the appropriate sampling technique or observation procedure which requires
data-gathering instruments
 Getting the sample size
B. DATA COLLECTION – the process of acquitting measurements, counts, or raw data
C. ORGANIZATION AND PRESENTATIONS OF DATA
 Summarizing, organizing and presenting of data
 Presentation can use graphs, frequency distribution tables, charts, diagrams, or
numerical techniques
D. DATA ANALYSIS – includes the conversion of the data into relevant information that leads
to the formulations of clear, summarized and comprehensible numerical description
- Involves the treatment of data with appropriate and carefully selected statistical tools
E. INTERPRETATIONS AND CONCLUSIONS – this is where intelligent conclusions are drawn
- Statistical inferences or generalizations are made about the population of interest and
predictions are also usually formulated
- Inferences has three categories: estimation, hypothesis testing, and association
F. RECOMMENDATIONS – based on the interpretations and conclusions
- These may take the form of suggested actions to be undertaken or recommended
solutions and further research on the problem investigated upon
THE NATURE OF DATA
A. PRIMARY DATA
- Gathered directly from an original source
- The analyst/researcher himself is involved in collecting the data relevant to his/her
investigation and the information gathered is based on the direct or first-hand
experience such as in an interview, in questionnaires, diaries, etc.
B. SECONDARY DATA
- Gathered from published or unpublished materials that have been previously obtained
by other individuals or agencies
- Some sources are books, journals, theses, newspapers, registrations of birth, deaths,
marriages from the local civil registry, enrollment statistics, etc.
C. QUALITATIVE DATA
- Measures quality, which is an attribute or a characteristic on each experimental unit
- They are labels in categories or class of an individual, object, or process
- They produce data that can be categorized according to similarities or differences in
kind and they are often called attribute data or categorical variables
- Examples are blood type, gender, eye color, civil status, etc.
D. QUANTITATIVE DATA
- Measures a numerical quantity or amount in each experimental unit
- Examples are interest rate, weight, height, scores in a test, etc.
Two Categories of Quantitative Data:
a. DISCRETE VARIABLES – can be assume a finite or countable number or values
Ex. Number of children, number of orders, number of subjects
b. CONTINUOUS VARIABLE – can be assume the infinitely many values
corresponding to the points on a line interval
- Measurable, expressed on a continuous scale
Ex. Height, weight, time, volume
METHODS OF DATA COLLECTION
1. INTERVIEW METHOD
- This is a direct method of investigation because the collection of information and data is
face-to-face or through a direct verbal interaction between the interviewer and the
interviewee
- It is a meeting between the interviewer and the interviewee for the purpose of extracting
information relevant to a certain issue of interest
- Ways to conduct an interview: mail, telephone, on-line, personal
1. QUESTIONNAIRE METHOD
- This is an indirect method of investigation
- The respondents are asked to provide responses to the prepared and well-planned list
of questions
- A questionnaire is used to elicit answers to the problems of the study and it is the most
commonly used tool to generate primary data – sometimes called survey form
2. REGISTRATION METHOD
- This method of gathering information is usually enforced by the law
- Examples are the following
o Registration of births, marriages, and deaths with the National Statistics Offices
(NSO) or Philippine Statistics Authority (PSA)
o Registration of motor vehicles and securing drivers’ licenses form the Land
Transportation Office (LTO)
o Securing licenses to practice a profession from the Philippine Regulation
Commission (PRC)
o Obtaining licenses to operate a business or organization from the Securities and
Exchange Commission (SEC) or from the Department of Trade and Industry (DTI
4. OBSERVATION METHOD
- The investigator collects information on the characteristics of the units under study by
actual measurement or by observing the behavior of persons or organizations and their
outcomes
- It is usually used when there is a very limited means of communication with the subjects
(when they cannot talk or write)
- The investigator is concerned with the direct description of the situation and the best
way to achieve this is to watch and record the observations objectively
5. EXPERIMENTATION
- This method is used to describe any process that generates a set of set
- It is used when the objective is to determine the cause-and-effect relationship of certain
phenomena under controlled conditions such as scientific researches
CLASSIFICATION OF MEASUREMENT OF DATA
MEASUREMENT – the assignment of values or numbers to objects or events according to some
rules or criteria set by the investigator
1. NOMINAL SCALE
- Lowest level of measurement
- Consists of labels or names to classify the observed elements to the categories which
they belong
- The data or observations cannot be arranged in an ordering scheme and they do not
have a meaningful numerical scale
Ex. Gender distribution (male or female); marital status (single, married, widowed,
separated, annulled); outcomes of tossing a coin (head or tail); quality of a product
(defective or not defective)
2. ORDINAL OR RANKING SCALE
- Elements are arranged in some meaningful kind of natural order which corresponds to
their relative position or size but no information about the difference between adjacent
positions
- Elements are ranked or arranged according to whether they possess more, less, or the
same amount of the variable being measured
Ex. Academic performance of students (poor, fair, good, very good, outstanding); size of
shirt (extra small, small, medium, large, extra large)
3. INTERVAL SCALE
- The elements can be differentiated according to characteristics; can be ranked or
ordered, and the arithmetic difference between elements is meaningful
Ex. Temperatures in degrees Celsius; Mental ability scores, blood pressure readings
4. RATIO SCALE
- This is considered the highest level of measurement
- Elements have order property, a unit of measurement, a meaningful difference (interval)
and a fixed origin or zero point
Ex. Temperature in Kelvin scale, height, volume of helium gas in balloons, time of each
runner in a marathon, pressure, speed
Measurement
Scale
Qualitive Scale
(Non-numeric)
Quantitative Scale
(Numeric)
Nominal
Interval
Ordinal
Ratio