Mathematics

Mathematics, 25.07.2019 00:50, mmoore36

The slope in a regression model tells you the strength of the linear relationship between the two variables. incorrect response true correct answer false

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Mathematics, 24.06.2019 22:50, neariah24

Choose all that apply when describing r2. (hint: 5 options are correct) (select all that apply.) is only used in multiple linear regression. represents the percent of variability in y that can be explained by the model. can be inflated by removing variables. only describes the relationship between quantitative variables. in simple linear regression, it is equal to the correlation coefficient r2. referred to as the coefficient of determination or coefficient of multiple determination. can be inflated by adding more variables. is used to determine the fit of a model. r2 = 1 − =

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Mathematics, 13.09.2019 03:30, lfox21

Twenty different statistics students are randomly selected. for each of them, their body temperature (degrees°c) is measured and their head circumference (cm) is measured. if it is found that r=0, does that indicate that there is no association between these twovariables? choose the correct answer below. a.yes, because if r =0, the variables are completely unrelated. b.no, because while there is no linear correlation, there may be a relationship that is not linear. c.no, because if r=0,the variables are in a perfect linear relationship. d.no, because r does not measure the strength of the relationship, only its direction.

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Mathematics, 24.10.2019 15:43, agyinbriana

Twenty different statistics students are randomly selected. for each of them, their body temperature (degreesc) is measured and their head circumference (cm) is measured. if it is found that requals0, does that indicate that there is no association between these two variables? choose the correct answer below. a. no, because if requals0, the variables are in a perfect linear relationship. b. no, because while there is no linear correlation, there may be a relationship that is not linear. c. no, because r does not measure the strength of the relationship, only its direction. d. yes, because if requals0, the variables are completely unrelated.

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Mathematics, 15.11.2019 20:31, crtlq

You have estimated a linear regression model relating y to x. your professor says, "i think that the relationship between y and x is nonlinear." how would you test the adequacy of your linear regression? (check all that apply ) a. compare the fit between of linear regression to the non-linear regression model. b. there is evidence in favor of a non-linear relationship if there is zero correlation between the dependent and independent variable. c. if adding a quadratic term, you could test the hypothesis that the estimated coefficient of the quadratic term is significantly different from zero. d. all of the above.

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