By David Kremelberg
This booklet presents readers with step by step information on working a large choice of statistical analyses in IBM® SPSS® records, Stata, and different courses. writer David Kremelberg starts his uncomplicated textual content through masking charts and graphs via regression, time-series research, and issue research. He presents a heritage of the strategy, then explains find out how to run those exams in IBM SPSS and Stata. He then progresses to extra complicated different types of information akin to HLM and SEM, the place he describes the checks and explains tips on how to run those assessments of their applicable software program together with HLM and AMOS.
This is a useful advisor for upper-level undergraduate and graduate scholars around the social and behavioral sciences who need help in figuring out a number of the statistical packages.
Read Online or Download Practical Statistics: A Quick and Easy Guide to IBM® SPSS® Statistics, STATA, and Other Statistical Software PDF
Similar mathematical & statistical books
R is an Open resource implementation of the S language. it really works on a number of computing systems and will be freely downloaded. R is now in frequent use for instructing at many degrees in addition to for useful facts research and methodological improvement. This ebook offers an elementary-level advent to R, concentrating on either non-statistician scientists in a variety of fields and scholars of information.
Anders Milhøj's functional Time sequence research utilizing SAS explains and demonstrates via examples how one can use SAS for time sequence research. It bargains smooth methods for forecasting, seasonal changes, and decomposition of time sequence that may be used with no concerned statistical reasoning.
For greater than 25 years, Mathematica has been the imperative computation setting for thousands of innovators, educators, scholars, and others around the globe. This publication is an creation to Mathematica. The aim is to supply a hands-on adventure introducing the breadth of Mathematica with a spotlight on ease of use.
Hoy más que nunca antes, aprender a programar se ha convertido en una necesidad, no sólo para el ingeniero informático, sino para aquellas personas que se desenvuelven en un ambiente laboral de tipo científico y técnico. El desarrollo de l. a. toma de decisiones a partir del análisis de datos masivos (big data), l. a. inteligencia synthetic o los angeles robótica, por poner unos ejemplos, hace que cada vez sea más necesario tener conocimientos de programación.
- Time Series Analysis and Forecasting: Selected Contributions from the ITISE Conference (Contributions to Statistics)
- Matlab by Example: Programming Basics (Elsevier Insights)
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
- A Feature-Centric View of Information Retrieval: 27 (The Information Retrieval Series)
Additional info for Practical Statistics: A Quick and Easy Guide to IBM® SPSS® Statistics, STATA, and Other Statistical Software
Categories: Mathematical Statistical