1. Correlation and regression Log. Reg
Lesson 7
Correlation and regression
Log. Reg

2. Inferential Statistics
Correlation = In statistics, dependence is any statistical relationship between two random variables or two sets of data. Correlation refers to any of a broad class of statistical relationships involving bidirectional dependence. (2 variables are associated: perfect positive +1, perfect negative -1);
Regression = measure as independent variables (predictors) associated with the dependent variable are better
Index: r (regression) small effect >.10; medium effect >.30; large effect >.50

5. Openness to experience
Eg. Correlation more/more; more/less *** = P<.001 **=.01 *=.05 you have to look minus /plus -/+ and stars/asterisk
Variable
Self Concept Clarity
Extraversion
Emotional stability
Openness to experience
Educational identity
Commitment
.12**
-.09*
.21**
-.06
Exploration in Depth
.11***
-.11**
.16**

6. Openness to experience
Integration with linear regression Table: Standardized Betas and Proportion Explained Variance for the Regression Analyses of SCC, emot. stab. and personality on Identity (Correlation) cons/pros variance
Variable
Self Concept Clarity
Extraversion
Emotional stability
Openness to experience
Commitment
.11**
(.02)
.16**
(.13**)
.22**
(.16*)
(.22**)
Exploration in Depth
-.21**
(-.18**)
-.08*
(-.01)
-.25**
(-.14**)
.14**
(.23**)
Total R2
.03**
.06**
.08**

7. LOGISTIC REGRESSION
In statistics, logistic regression, or logit regression, or logit model is a  regression model where the dependent variable (DV) is categorical/dummy. 
logistic regression predicts the probability of particular outcomes

8. e.g. LOG REG Note: *p<.05. **p<.01. ***p<.001.
Would you be willing to spend more to be in a eco-friendly accommodation?
Coeff B
Sig.
Exp(B)
Gender
(ref females)
Males
.619
.019*
1.857
Class age
(ref adults)
Young people
-.776
.003**
.460
Constant
1.175
.000***
3.239
Case numbers
374