KISS
Prinsip dalam pembuatan karya ilmiah adalah KISS (Keep It Simple but Smart).
Ungkapan KISS ("Keep it simple, stupid") sebagai prinsip desain U.S. Navy in 1960.[1][2]
The KISS principle states that most systems work best if they are kept simple rather than made complicated; therefore simplicity should be a key goal in design and unnecessary complexity should be avoided. The phrase has been associated with aircraft engineer Kelly Johnson (1910–1990).[3] The term "KISS principle" was in popular use by 1970.[4] Variations on the phrase include "keep it short and simple" and "keep it simple and straightforward".[5][6]
Namun disini kita lebih menekankan pada Keep It Simple but Smart yaitu bahwa sebuah karya ilmiah sebaiknya ditulis sesederhana mungkin namun sarat dengan isi.
Monday, April 14, 2014
Sunday, April 13, 2014
Link untuk Pengetahuan Statistika
Descriptive Statistics
- Statistical Terms in Sampling (Research Methods Knowledge Base)
- Resources to Help You Learn and Use SPSS (UCLA)
- SPSS Online Guide (Richard M. Wielkiewicz)
- Tutorials Online (University of New England)
- Raynald’s SPSS Tools (Raynald Levesque)
- HyperStat Online Statistics Textbook (David M. Lane)
- SPSS Windows Instructions (State University of New York at Oswego)
- SPSS Lessons and Resources (East Carolina University)
- Engineering Statistics Handbook (NIST/SEMATECH)
- SPSS Tutorial (Amherst College)
- Guide to SPSS (Harvard-MIT Data Center)
Test of Significance
- Significance in Statistics & Surveys (Creative Research Systems)
- Independent Samples T Test (Wellesley College)
- Example of when equal variances cannot be assumed (Valparaiso University)
- Review of the T Test (Richard M. Wielkiewicz)
Regression Analysis
- Multiple Regression (StatSoft)
- Introduction to Regression (Princeton University)
- Statistics Tutorial: A Simple Regression Example (StatTrek)
Chi-Square and ANOVA
- Chi-Square & T Test (University of Toronto)
- Chi-Square Goodness of Fit Test (Amherst College)
- One-Way Between-Groups Analysis of Variance (Amherst College)
- Two-Way Analysis of Variance (Thomas W. MacFarland)
Video Tutorials
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