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Regression
A Coggle Diagram about Multiple Regression (From b to b*, Interpretation regression coefficient, Interpretation: Assess influence of X1 while controlling for influence of other independent variables, Interested in more independent variables and how the influence of Y, Multiple regression equaion: y= b0+ b1x1.., When you want to add more variables you click next and • Still one constant b0 – multiple bi coefficients
•b0: Predicted value Y when all X-variables equal zero
• Every coefficient bi indicates how much Xi influences Y…“…while holding the other X-variables at constant values”), Simple regression in practise: SPSS, Simple regression (Looking beyond relationships, Not cause and effect, Predict Y from X and Models the assymetric relatioship between 2 variables), Calculating the line of equation on SPSS, T statistic (Test the null hypothesis when regression cofficient is 0 and If significant: we gain confidence in the hypothesis that b1 is
significantly different from zero
the predictor makes a
significant contribution to predicting the outcome), Model fit- R2: What is proportion of improvement
R2= SSm/SSt
For simple regression: Pearson r: square root of R2
If the model results in better prediction than
using the mean, then we expect SSM to be
much greater than SSR and Regression Analysis is fitting a linear model to our data and use it to predict values of an outcome variable