Description

Leader00779nam a2200253 i 4500
0011015408
003LB
00520220208112641.0
008220208 2022 lv 00000 lav
020 a: 9781439885383
040 a: LB
041 a: eng
080 a: 311
1001#a: Roback, Paul4: aute: Autors
2451 a: Beyond Multiple Linear Regressionb: Applied Generalized Linear Models and Multilevel Models in Rc: Julie Legler
264#1a: Boca Ratonb: Taylor&Francis Groupc: 2021
300 a: 418 p.
336##a: tekstsb: txt
337##a: tiešuztveres videb: n
338##a: sējumsb: nc
7001 a: Legler, Julie
908##a: Roback, Paul
996##a: BA

Copies

Location Address Count Shelf Status
Monetārās politikas pārvalde 07 1 311 On a shelf Available to order

Annotation


Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling.

Contact information

Any questions? Write us

Help

Follow us

Links