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I have data of 20 peoples height, weight, calorie intake and skinfold thickness. I have carried out a regression of calorie on height, on weight and on height and weight. I have done the same thing for skinfold thickness. I then used R to work out the summary of results. each model also has an intercept i.e. y= beta1 + beta2X .

using the 't' values I have found for calories both height and weight are significantly different from zero in the individual models. But when I look at the model where height and weight are both included then both become non significant.

For the skinfold a similar thing happens. This time height and weight are not significantly different from zero individually but in the model including both they both become significant.

I have found the correlation between weight and height to be -0.88 which is high. Can anyone help me explain what causes the changes in signficance?

thanks in advance

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# Linear regression and high correlation problems

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