Topic: Understanding Data and Ways to 2 Types of Sampling Technique

Systematically Collect Data

1. Probability Sampling, not choosing
respondent (random)
2. Non- Probability Sampling, choosing
Quantitative Research Design
respondent (nonrandom)
- stands as the blueprint of a study.
4 Types of Probability Sampling:
- outlines the data collection procedure,
instruments to be used in the data 1. Simple Random Sampling
gathering, analyzation and - Members of the population have an
interpretation. equal chance of being selected
2. Stratified Random Sampling
2 Types of Research Design
- Population is divided into homogenous
1. Experimental Design subgroups
2. Non- Experimental Design 3. Systematic Random Sampling
- K=N/n
EXPERIMENTAL DESIGN

- establish cause and effect relationships 4. Cluster or Area Sampling

- determines the effect of an intervention - population is dispersed across a wide
geographic region
There are 2 types of experimental design;

1. True- Experiment (random samples) 6 Types of Non- Probability Sampling

2. Quasi- Experiment (no random samples)
1. Accidental or Convenience
NON- EXPERIMENTAL DESIGN 2. Modal Instance
- do not employ intervention 3. Expert Sampling
4. Proportional and Non-proportional
There are 3 types of non-experimental design; 5. Heterogeneity
6. Snowball
1. Descriptive, collect information
2. Predictive, predict future event INSTRUMENTATION
3. Explanatory, develop and test a theory
- Process of collecting data
Also, 3 types of non-exp. according to TIME; - Answers how to gather, where and
when to collect, how to analyze DATA
1. Retrospective, past data
2. Cross- sectional, single point in time
3. Longitudinal, across time
RESEARCH INSTRUMENT
Sampling Technique
1. Researcher- Completed, researcher
- process of obtaining the participants of supplies data
a study from a larger pool of potential 2. Participant- Completed, participants give
participants termed as the population data
(Pulmones, 2016).
Technical Qualities of Research Instrument Topic: Finding Answers Through Data
Collection
 Validity, measures what it intends to
measure Data Collection
 Reliability, consistency of measurement
- allows the researcher to obtain relevant
TYPES OF VALIDITY information regarding the specified
research questions or objectives
1. Content Validity, measures the
important and essential dimensions of Tools for data collection:
the variable
1. Questionnaire
2. Criterion Validity, instrument to predict
2. Tests, assess various skills
future performance or estimate current
- Recall
performance on another measure
- Recognition
3. Construct Validity, scores obtained by
- Open-ended
the instrument can be related and
3. Interview
influence another variable
4. Observation, assess behavior
TYPES OF RELIABILITY through performances

1. Stability Data-Processing Techniques

2. Equivalence
1. Editing
3. Homogeneity
2. Coding
4. Scorer Reliability
3. Tabulation
Threats to Internal Validity
DATA ANALYSIS
• History
- It is the section where you will describe
• Maturation
how the data in your study were
• Testing
analyzed
• Instrumentation
• Statistical Regression Steps in Constructing a Research Instrument
• Differential Selection
• Experimental Mortality 1. Planning
• Experimental Treatment Diffusion 2. Construction
• Compensatory Rivalry of the Control 3. Quantitative Evaluation
Group 4. Validation
• Compensatory Equalization of Topic: Analyzing Quantitative Data: Descriptive
Treatment Statistics and Inferential Statistics
• Resentful Demoralization of the Control
Group Descriptive Statistics- procedures that
• The Hawthorne Effect researchers use to describe data.
• Experimenter Bias 1. Frequency/ Counts
• Location 2. Percentages
3. Measures of Central Tendency: Mean,
Median, Mode
 4. Measures of Variability: Range,
Standard Deviation, Variable
5. Use of Pie Charts and Bar Graphs

Inferential Statistics- infers or makes

judgements about the participants through
hypothesis testing and the use of tests of
significance.

1. State null hypothesis

2. State the alternative hypothesis
3. State the statistical significance
4. Collect data
5. Calculate the test statistic
6. Draw conclusion about the null
hypothesis