TY  - CHAP
M1  - Book, Section
TI  - The First Step: Understanding Simple Linear Regression
A1  - Glantz, Stanton A.
A1  - Slinker, Bryan K.
A1  - Neilands, Torsten B.
Y1  - 2017
N1  - 
T2  - Primer of Applied Regression and Analysis of Variance, 3e
AB  - The  purpose  of  this  book  is  to  teach  readers  how  to  formulate  biological,  clinical,  and  other  problems  in  terms  of  equations  that  contain  parameters  that  can  be  estimated  from  data  and,  in  turn,  can  be  used  to  gain  insights  into  the  problem  under  study.  The  power  of  multiple  regression—whether  applied  directly  or  used  to  formulate  an  analysis  of  variance—is  that  it  permits  you  to  consider  the  simultaneous  effects  of  several  variables  that  act  together  to  determine  the  value  of  some  outcome  variable.  Although  multiple  linear  regression  models  can  become  quite  complicated,  they  are  all,  in  principle,  the  same.  In  fact,  one  can  present  the  key  elements  of  any  linear  regression  in  the  context  of  a  simple  two-variable  linear  regression.*  We  will  estimate  how  much  one  variable  increases  (or  decreases)  on  the  average  as  another  variable  changes  with  a  regression  line  and  quantify  the  strength  of  the  association  between  the  two  variables  with  a  correlation  coefficient.  We  will  generalize  these  concepts  to  the  multiple  variable  case  in  Chapter  3.  The  remainder  of  the  book  will  explore  how  to  apply  these  powerful  tools  intelligently.  
SN  - 
PB  - McGraw-Hill Education
CY  - New York, NY
Y2  - 2024/04/19
UR  - accessbiomedicalscience.mhmedical.com/content.aspx?aid=1141897792
ER  -