The document discusses different types of variables in experimental research: - Independent variable: Factor manipulated by researcher to determine its effect - Dependent variable: Factor observed and measured to determine effect of independent variable - Moderator variable: Factor that modifies relationship between independent and dependent variables - Control variable: Factors controlled by researcher to neutralize their effects - Intervening variable: Factor that theoretically affects phenomena but cannot be directly observed It also discusses data types, central tendency measures, data variability measures, and statistical techniques like correlation analysis, t-tests, ANOVA that are used for quantitative analysis.

4. Steps in data processing

5. Quantitative Analysis Strategies There are two types of quantitative analysis: Descriptive : Utilizes numerical and graphical methods to find patterns in a data set, summarizes the information, and present information in a convenient form. Inferential : Utilizes a sample to make estimates, decisions, or predictions about population . It consists of Estimation technique and Hypothesis of testing.

9. Summary of Data Classification Increasing Complexity

11. Frequency table and cross tabulation What is a Frequency table? It is a tabular summary of a set of data showing the frequency (or number) of items in each of several non-overlapping (with each data value belonging to one and only one group or class) groups or classes. Note: In qualitative data , class is one of the category of the variable and in quantitative data it is the range of values established to divide the data into categories. What is Cross tabulation? It is the tabular summary of a set of data when two or more variables are observed at the same time.