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    Having a hard time figuring out this question: ''which null-hypothesis is interesting to test in simple linear regression''. Anyone brighter than me? Pleaase!
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    I think simple linear regressions is basing predictions on x = what you expect to get from y


    I think it's just trying to get you to come up with a null hypothesis based off the above model. I'm guessing this from AS psychology?
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    (Original post by medhelp)
    I think simple linear regressions is basing predictions on x = what you expect to get from y


    I think it's just trying to get you to come up with a null hypothesis based off the above model. I'm guessing this from AS psychology?
    It's from a statistics course at University. I'm finding this very difficult, not sure I'll figure it out but thanks for your help!
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    (Original post by Muminmamman)
    It's from a statistics course at University. I'm finding this very difficult, not sure I'll figure it out but thanks for your help!
    I'm crap at stats lol
    maybe there's certain types of hypothesis testing for certain regression lines idk anyway good luck finding out what is it
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    A null hypothesis is when you predict that there is no difference or relationship between two factors or co variables
    A linear regression graph is a straight line graph
    So by deduction I'd assume that a null hypothesis linear graph would be the one with the most scattered points around the best for or low correlation coefficient
    Hope that helps!
    Doing psychology at uni and did a stats module at alevel
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