1. Handout One: Quantitative Research Methodology-Question, Design, Data, Analysis, & Inference
EPSE 592
Experimental Designs and Analysis in Educational Research
Instructor: Dr. Amery Wu

2. Learning Strategies for Successful Outcomes
Contextualizing through preview
Building through mastery
Digesting by slicing
Consolidating by review and application
Internalizing through communication

3. Research Question Give me a research question of your Interest.
Contextualizing Learning by a Research Example
Give me a research question of your Interest.

4. What is “Data”?
“Data” is originally a Latin noun meaning “something given.” Today, the word data is used in English as a plural noun meaning “facts or pieces of information”. In statistics, data is conceived of as information given, observed, or obtained.

5. Types of Data
Continuous data (numerical or quantitative data) refer to the information indicated by numbers that represent the amount of the studied phenomenon.
Categorical data (discrete or qualitative data)
refer to the information indicated by numbers or symbols that represent the type of the studied phenomenon, where the types can be ordered (ordinal) or disordered (nominal).

6. A Plan for Data Collection
What is Research Design?
A Plan for Data Collection
A plan of what type of data to gather, from whom, how and when to collect the data, and how to analyze the obtained data in order to answer the research questions, hence making intended inferences.

7. Types of Research Design
Experimental (clinical trials): typically used when the intended inference is uni-directional and causal, e.g., smoking causes lung cancer.
Observational (correlational, survey): typically used when the intended inference is dual-directional and relational, e.g., smoking is related to lung cancer.
With observational data, some particular conditions must be met in order to make directional or causal inferences.

8. Modeling the Data (Statistical Analysis)
Data = Model + Residual
Types of Modeling
Describing or summarizing: uncovering the data pattern hidden in one single variable of interest, no other variables are involved to explain/predict the pattern (e.g., central tendency and dispersion of income).
Explaining or predicting: explaining and predicting the outcome (response, dependent) variable using other variable(s) (e.g., t-test, odds ratio, ANOVA, multiple regression).

9. Q: Are the following statistical techniques type 1) or 2) Models?
correlation
contingency table (chi-square table)
percentage
ranks
percentile
mean
variance
t-test
Median
mode

10. Data

11. Model Data Fit Data Model Residual = + 9 1 8 = + 10 6 4 = + 5 7 -2 = +• • • 5 7 -2 = +
Since the data is given, a statistician’s task is to, within the availability of data, maximize the fit between the model and data, which is equivalent to minimize the residual (because of the additive property)

12. Descriptive vs. Inferential
Types of Statistical Inferences
Causal vs. Relational
Causal inference entails the claim about the direction between variables, i.e., cause→ effect, IV →DV, or factor →outcome. In a manipulationist view, causal relationship is conceptualized as “change in the IV leading to change in the DV.” experimental design/data is often required.
Relational inference is the claim about the bi-directional relationship/association between observational data.
Descriptive vs. Inferential
Descriptive inference is claims made about the given sample.
Inferential inference is claims made about the target population based on the given sample using hypothesis testing technique.

13. Activity
Classify the following statistical methods into one of the four categories (A-D)
Mode
Percentage
Two-tailed correlation test
Correlation
Chi-square test
Variance
Histogram
ANOVA
One-sample t- test
Percentile
Two-sample t-test
Ranks
Simple regression
Mean
Skewness
Bar chart

14. Activity
Place each of the research elements listed below in one of the boxes next to the vertices of the pentagon, draw lines (connecting vertices) and arrows to explain the relationships among these concepts. Note that the terms are not ordered.
Research Design
Data
Inference
Statistical Analysis
Research Question

16. What Do Statisticians/Methodologist Do?
Ask questions: formulating good and researchable questions
Design: participating in research design to make sure data obtained is valid for answering the research question (intended inferences)
Model: using statistical techniques to describe, summarize, explain or predict data
Communicate: clearly and accurately disseminating the research results and their implications to the stakeholders and audience.