Statistical Test Interpretation and SPSS Decision Rules
Statistical Significance: The Main Rule
The decision rule for hypothesis testing is based on the p-value:
- p < 0.05: Significant → Reject H0 (Null Hypothesis)
- p ≥ 0.05: Not significant → Fail to reject H0
Choosing the Appropriate Test:
- 1 group vs known value → One-Sample T-Test
- 2 groups (different people) → Independent Samples T-Test
- 2 groups (same people before/after) → Paired Samples T-Test
- 3+ groups → ANOVA (+ Tukey Post-Hoc if significant)
- Numeric ↔ Numeric relationship → Correlation
- Predict
Mastering APA Statistical Reporting and Research Design Principles
APA Statistical Reporting Examples
This section demonstrates how to report key statistical findings and sample characteristics using proper APA format.
Sample Size and Demographics
- Total Participants: The total sample size was reported as N = 98. (Note: The capitalized N represents the full sample; a lowercase n represents a subset.)
- South Asian Identification: 9.20% of the sample identified as South Asian.
- Male Participants: 50.00% of the sample was identified as men.
- Non-Respondents for Age: Six participants
Essential Statistical Concepts: Data Analysis and Modeling
Statistics: techniques (collecting,organizing,analysing,interpreting data)
Data may be:
quantitative (values expressed numerically) qualitative: (characteristics being tabulated). Descriptive statistics
: techniques summarize, describe numerical data= easier interpretation – can be graphical/involve computational analysis. Inferential statistics: techniques about decisions about statistical population/process are made based only on a sample being observed – use of probability concepts. VARIABLES:
Essential Quality Tools for Process Improvement and Analysis
Quality Tools for Process Control
Quality tools are essential instruments used to control a process, identify faults, improve risk analysis systems, and drive continuous improvement.
Brainstorming
Brainstorming is a technique where a group encourages every member to participate and generate ideas, focusing on quantity over complexity. It is crucial that the group avoids criticizing ideas during the generation phase, as only some ideas will ultimately be valid.
Requirements for Effective Brainstorming
- The
Essential Statistical Concepts and Tests
Simple Linear Regression
Purpose: Predict a numerical outcome (dependent variable Y) from a numerical predictor (independent variable X).
Equation: Y = a + bX
a (intercept): Predicted Y when X = 0
b (slope): For each 1-unit increase in X, Y increases/decreases by b units.
Example: Income = 20000 + 3000 × YearsOfEducation → Each extra year of education predicts $3,000 more income.
R² (Coefficient of Determination): Tells us how much of the variation in Y is explained by X. Ranges from 0 to 1.
Interpretation: