Question

please answer all questions.

7. Think of two variables in your field for which linear regression could be used to explain their possible association. a) Describe each component of the simple linear regression equation using your example. Y = Be + B1X + € X: Bo: B1: E: b) State the null and alternative hypotheses using words (not just symbols) of your example. He: Hi:

Answer 1

I Answer (a) equation Given rearession Y - Botß x + 6 response variable predictor / Explanatory variable r. Y is the x is the Intercept B, slope - Now this can be understand by following example au Suppose we conduct Study o experim- ent in a particolor class. In students. Now if we want to snow how to study. time of students inprese there exam mark so af we conduct exam and assion marles of student and we as them how much time they daily tours, they spend on study and data were obtained, ao in above example y pre response variable is marks Student obtain in exam x x is predictor / Explanatory variable is study time spend by student - te daily Hourse they spend on Steady Bo ! Slope Intercept Error

classmate Date Page how suppose obtain the we from regressis experiment we equation as follows compare it with y- Botß.xtC. Here, ßo 12 - intercept. it can be interpret as Pal. 2 implies when x ne study student is o the mean value eram marits is 1.2 Hours of of y it am - - 2 - Slope it com be interprete As to student imprese & Hours the marils 2 point as daily The ire a study of Student time! imprese by by In our above example Ho! ß, no this mens that there is no significant melationship between marks of student and daily study Hours of student HI B to I this means that there linear relationship between student and daily study is significant marks of Hours of student my here study time mesure in Hours mocionK of studuend is measures in or GPA (Grade point Averrage) and point