This document provides information on conceptual frameworks and quantitative data collection and analysis techniques for research. It defines conceptual and theoretical frameworks, and examples including IPO and IV-DV. It also describes quantitative data collection techniques such as observation, surveys, experiments, and content analysis. It discusses measurement scales, preparing data through coding and tabulation, and analyzing data with descriptive statistics and advanced methods like correlation, ANOVA, and regression.

1. Conceptual
Framework
Practical Research 2

2. Conceptual Framework
+ Graphical presentation of your concepts or ideas on the
basic structure or components of your research as well as
on the relationships of these elements with one another.
+ A broad outline or plan to give shape to your research.
(Shields & Rangarjan 2013)

3. Conceptual vs. Theoretical Framework
+ Theoretical frameworks involve established theories
guiding research.
+ Conceptual frameworks focus on organizing ideas and
guiding the research process (your own).

4. Conceptual vs. Theoretical Framework
+ Theoretical - using Freud's psychoanalytic theory
+ Conceptual - organizing study variables in psychology
research.

5. Examples
+ IPO
+ Input: the variables that causes the problem, phenomenon
or transformation
+ Process: the method by which the variables are collected
and synthesized
+ Output: the problem, phenomenon, or transformation; the
outcome of the variables

6. Examples
+ IPO

7. Examples
+ IV-DV
+ Independent Variable: The expected cause (the predictor,
or explanatory variable).
+ Dependent Variable: The expected effect (the response, or
outcome variable).

8. Examples
+ IV-DV

9. Data
Collection
Procedure
Practical Research 2

10. Quantitative Data Collection
Techniques
+ Observation
- Using your sense organs, you gather facts or information
about people, things, places, events, and so on, by watching
and listening to them; then, record the results of the
functioning of your eyes and ears.
- Expressing these sensory experiences to quantitative data,
you record them with the use of numbers.

11. Quantitative Data Collection
Techniques
+ Survey
- Survey is a data-gathering technique that makes you obtain
facts or information about the subject or object of your
research through the data gathering instruments of interview
and questionnaire.

12. Quantitative Data Collection
Techniques
+ Survey
Questionnaire - is a paper containing series of questions
formulated for an individual and independent answering by
several respondents for obtaining statistical information.
Interview - like a questionnaire, interview makes you ask a
set of questions, only that, this time, you do it orally.

13. Quantitative Data Collection
Techniques
+ Experiment
- a scientific method of collecting data whereby you give the
subjects a sort of treatment or condition then evaluate the
results to find out how the treatment affected the subjects
and to discover the reasons behind the effects of such
treatment on the subjects.

14. Quantitative Data Collection
Techniques
+ Content Analysis
- is another quantitative data-collection technique that makes you
search through several oral or written forms of communication to
find answers to your research questions.
- not only for examining printed materials but also for analyzing
information coming from non book materials like photographs,
films, video tapes, paintings, drawings, and the like.

15. Measurement Scales
+ Nominal Scale
- categorizing people based on gender, religion, position, etc. (one point for
each)
religion – Catholic, Buddhist, Protestant, Muslim
gender – male, female
position – CEO, vice-president, director, manager, assistant manager
Summing up the points per variable, you will arrive at a certain total that
you can express in terms of percentages, fractions, or decimals like 30% of
males, 25% of females, 10% of Catholics, 405 of Buddhists, and so forth.

16. Measurement Scales
+ Ordinal Scale
- ranking or arranging the classified variables to determine
who should be the 1st, 2nd, 3rd, 4th, etc., in the group
+ Interval Scale
- showing equal intervals or differences of people’s views or
attitudes.
+ Ratio Scale
- rating something from zero to a certain point
Performance in Math subject – a grade of 89% (from 0 to 100%)

17. Measurement Scales
Likert Attitude Scale

18. Data
Analysis
Practical Research 2

19. Preparing the Data
1. Coding System - to quantify or change the verbally
expressed data into numerical information.
2. Data Tabulation - for easy classification and distribution
of numbers based on a certain criterion, you must collate
them with the help of a graph called Table.

20. Preparing the
Data

21. Analyzing the Data
+ Descriptive Statistical
Technique
Frequency Distribution - gives
you the frequency of distribution
and percentage of the
occurrence of an item in asset
of data.

22. Analyzing the Data
+ Descriptive Statistical Technique
Measure of Central Tendency - indicates the different positions or
values of the items.
- Mean: average of all the items or scores
- Median: the score in the middle of the set of items that cuts or divides
the set into two groups
- Mode: refers to the item or score in the data set that has the most
repeated appearance in the set.
- Standard Deviation and Variance: shows the extent of the difference of
the data from the mean.

23. Analyzing the Data
+ Advanced Quantitative Analytical Methods
- An analysis of quantitative data that involves the use of
more complex statistical methods needing computer software
like the SPSS, STATA, or MINITAB.

24. Analyzing the Data
+ Advanced Quantitative Analytical Methods
- Correlation: uses statistical analysis to yield results that describe
the relationship of two variables.
- Analysis of Variance (ANOVA): the results of this statistical
analysis are sued to determine if the difference in the means or
averages of two categories of data are statistically significant.
- Regression: it helps us understand how changes in one variable
(let's call it X) can predict changes in another variable (let's call it
Y).