Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Quantitative Research

2,764 views

Published on

Published in: Education, Technology
  • Be the first to comment

Quantitative Research

  1. 1. Basic Characteristics of Quantitative Research Elements of Quantitative Research Quantitative Design Issues Causal Relationships and Hypothesis Aspect of Explanation in Quantitative Research Ways to Select Topic in Quantitative Research Quantitative Measurement Types of Sampling Method Analysis of Data
  2. 2. Basic Characteristics of Quantitative Research Test Hypothesis that the researcher begins with Concepts are in the form of distinct variables Measures are systematically created before data collection and are standardized Data are in the form of numbers from precise measurement Theory is largely causal and deductive Procedures are standard and replication is assumed Analysis proceeds by using statistics, tables or charts and discussing how, what, they show relates to hypothesis
  3. 3. Elements of Quantitative Research Reconstructed Logic Logic of how to do research is highly organized and restated in an idealized, formal and systematic form. Technocratic Perspective Researcher is the expert, and the research questions often originate with the sponsors of the research.
  4. 4. Linear Path A research path that follows a fixed and well-defined sequence of steps. Thinking and way of looking at issues is direct, narrow, and straight to the point. Triangulation Observing from different viewpoints. 1. Triangulation of Measures 2. Triangulation of Observers 3. Triangulation of Theory 4. Triangulation of Method
  5. 5. Objectivity and Integrity More “mechanical” technique Principles of Replication Adhere to standardized methodological procedures Measure with numbers Analyze data with statistics
  6. 6. Quantitative Design Issues Variation and variables VARIABLES- are factors that can take on more than one value in a given study. Types of Variables: 1. Independent Variable- is a variable presumed to effect/influence other variables. 2. Dependent/Outcome Variable- is a variable presumed to be effected by one or more independent variable. 3. Intervening/Mediating Variable-is the intervening variable that controls/affects the dependent variable.
  7. 7. Example: An Evaluation on the use of Filipino as Medium of Instruction in the Social Science: Impact to Students’ Performance Independent- medium of instruction (Filipino) Dependent- students’ performance Mediating- effectiveness of the teacher IQ of student Student’s interest and preparation
  8. 8. Causal Relationships and Hypothesis Quantitative researchers test hypothesis and establish relations of events by strong reliance to statistical procedures. Five Characteristics of Causal Hypothesis: 1. It has at least two variables 2. It express a causal/cause-effect relationship between the variables 3. It can be expressed as a prediction or an expected future outcome 4. It is logically linked to a research question and theory. 5. It is falsifiable
  9. 9. HYPOTHESIS- refers to a prediction of results made before the study commences. Types of Hypothesis: 1. Null (Ho)- is a denial of the presence of relationship among variables. It is always stated in the negative form because it is easier to disprove. Ex. There is no significant difference on the effectiveness of directive and non-directive teachers as perceived by respondents.
  10. 10. 2. Alternative (Ha)- is the opposite of the null hypothesis and it is always stated in the positive form to affirm the existence of an observed phenomenon. Ex. There is a significant difference on the effectiveness of directive and non-directive teachers as perceived by respondents.
  11. 11. Characteristics of Hypothesis: 1. It should be reasonable 2.It should be consistent with known facts/theories 3. It should be stated in such a way that it can be tested and found to be probably true/false. 4. It should be stated in simplest possible term 5.It should be clearly in the from of declarative sentence
  12. 12. Aspect of Explanation in Quantitative Research Level of Analysis- The level of social reality to which theoretical explanation refer. The level of social reality varies on a continuum from micro level (small group/individual processses) to macro level (civilizations/structural aspects of society).
  13. 13. Unit of Analysis- The type of unit a researcher uses when measuring. 1. Individual 2. Group 3. Organization 4. Social Institution 5. Social Category 6. Society
  14. 14. Ways to Select Topic in Quantitative Research Personal experience Curiosity State of knowledge in the field Solving a problem Social premiums Personal values Every life
  15. 15. Techniques for Narrowing a Topic into a Research Question: 1. Examine the literature 2. Talk over ideas with others 3. Apply specific context 4. Define the aim of the desired outcome of the study
  16. 16. Quantitative Measurement Conceptualization- process of thinking through meaning of construct. Operationalization- process of linking a conceptual definition to a specific set of measurement techniques/procedures. Data Collection- process of obtaining data through specific/combination of techniques/procedure. Data Analysis- apply the statistical principles and procedures to extract essential information from the data collected.
  17. 17. Five Suggestions in Coming Up with a Measure: 1. Remember the conceptual definition 2.Keep an open mind 3. Borrow from others 4.Anticipate difficulties 5.Do not forget your unit analysis
  18. 18. VALIDITY- refers to the appropriateness, meaningfulness, correctness, and usefulness of any inferences a researcher draws based on data obtained through the use of an instrument.
  19. 19. Types of Validity: 1. Content Validity- degree of representativeness of the content/domain of definition in a measure. 2. Criterion Validity- uses some standard/criterion to indicate a construct accurately. 3. Construct Validity- the extent to which the measure defines the construct.
  20. 20. RELIABILITY- refers to the consistency of scores/answers provided by an instrument. How to Increase Reliability: 1. Clearly conceptualize construct 2.Use precise level of measurement 3. Use multiple indicators 4.Use pilots
  21. 21. Types of Reliability: 1. Stability Reliability (Test-retest method) -involves administering the same instrument twice to the same group of individuals after certain time interval elapsed. 2. Equivalence Reliability (Reliability using multiple indicators) - involves administering two different, but equivalent, forms of instrument to the same group of individuals at the same time.
  22. 22. 3. Representative Reliability (Internal-consistency method/Reliability across groups) - involves comparing responses to different sets of items that are part of an instrument.
  23. 23. Types of Sampling Method Probability Sampling Description- estimate of group characteristics Inference-testing of empirical hypothesis Non-Probability Sampling  Exploration and theory development Developing and testing survey research instrument Selection of a small number of first stage units
  24. 24. Analysis of Data Dealing with Data 1. Coding-systematically reorganizing raw data into a format that is easily readable 2. Entering Data 3. Cleaning Data-checking accuracy of coding and encoding data
  25. 25. Statistical Analysis 1. Universal Statistics- one variable is analyzed Frequency Distribution Measures of Central Tendency Measures of Variations 2. Bivariate Statistics- two variables are analyzed Simple Correlation T-test Analysis One-Way Analysis of Variance (ANOVA) Chi-Square
  26. 26. 3. Multivariate Statistics- three/more variables are analyzed  Factorial ANOVA Factor Analysis Multiple Regression Structural Equation Modeling Path Analysis
  27. 27. Reference: Amante, Diosdado A. et.al. Essentials of Research Methodology. pp. 48-56

×