- Data analysis and interpretation examines data using statistical techniques to answer research questions. It involves examining variables in terms of quantity, quality, attributes, patterns, and relationships. - There are different types of statistical tests for examining single variables, relationships between two variables, and relationships between multiple independent and dependent variables. - Analysis of variance (ANOVA) tests for differences across multiple dependent variables based on an independent nominal variable. It uses sums of squares and cross-product matrices.

1. Date Analysis and Interpretation

2. - It may be defined as the examination of
data or fact in terms of quantity, quality,
attribute, trait, pattern, trend, relationship
among others so as to answer research
questions which involve statistical
techniques and procedures.

3. - Tests a single variable to determine
whether the sample is similar to the
population from which it has been
drawn.

7. -Tests two variables on how they
differ with each other.
- Statistical tool
Correlation coefficient – use in both descriptive and
experimental design.
Z test – descriptive research only.
T-test – experimental only.

9. -Tests three or more independent variables at
a time in the degree of relationship with the
dependent variable.

10. • Also known as “MANOVA”.
• This examine several variable and their
relationships simultaneously
• In contrast to bivariate analysis which examine
relationship between 2 variables, and univariate
analyses where one variable at a time is
examined for generalization from the sample to
the population.

11. • MANOVA test means differences among groups
across several dependent variables
simultaneously, by using sums of squares and
cross product matrices.
• In MANOVA test the independent variable is
measured on a nominal scale and the
dependent variables on an interval or ratio
scale

12. Illustration 1: Experimental design

14. Illustration 2 ( Experimental design

16. Computation of sum of squares for samples (SS)

21.  Is a type of data analysis wherein the
results of the study is compared with the
norm or standard. the statistical tools
used in this type are the arithmetic mean
and the standard deviation.

23. Computation of arithmetic mean