You fitted a regression model on the height of a particular pine tree, after 20 years of growth, as a function of the elevation the tree is growing in a coastal mountain. You found that linear regression was appropriate to study this question i. e., the relationship was linear. The regression model showed that tree height decreased 0.2 meters per meter gained in elevation and that tree height at sea level height (Om elevation) was predicted to be 110 m. The slope of this model was: (use the correct sign) while the intercept was: . The model predicts that a tree growing at an elevation of 25 m should be m tall. While the predicted elevation in the mountain that a 108 m tall tree will be found ism.

Stu and ambrose are working together on a study of whether diet is related to students' mental health. first, they randomly select 10 students from the student center and 10 students from the office of counseling and psychological services. then, they ask students to rate their diet in terms of healthiness on a scale of 1-100 before completing a 20-item mental health survey. a) name one of the constructs being studied b) how was the construct you named above operationally defined in this experiment? e) was the variable you described above their independent variable, their dependent variable, or a controlled variable? d) what is a confounding variable? what is a potential confound in this study?