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The numerical value for a correlation_ can never be greater (select the best answer) b. than 1.00 can never be less than 1.00 can never be greater than 1.00 and d. ...

Question

The numerical value for a correlation_ can never be greater (select the best answer) b. than 1.00 can never be less than 1.00 can never be greater than 1.00 and d. can be greater than can never be less than -1.00 1.00 and can be less than -1.00

The numerical value for a correlation_ can never be greater (select the best answer) b. than 1.00 can never be less than 1.00 can never be greater than 1.00 and d. can be greater than can never be less than -1.00 1.00 and can be less than -1.00



Answers

Suppose the correlation between two variables is $-0.57 .$ If each of the $y$ -scores is multiplied by $-1,$ which of the following is true about the new scatterplot? (A) It slopes up to the right, and the correlation is -0.57. (B) It slopes up to the right, and the correlation is + 0.57 . (C) It slopes down to the right, and the correlation is - 0.57 . (D) It slopes down to the right, and the correlation is + 0.57 . (E) None of the above is true.

Yeah. We were told that the correlation between two variables is negative 0.57 And if each of the UAE scores is multiplied by negative one, which of the following is true about the new scattered blood. And so we have option a It slips up to the right and the correlation is the same be it slips up to the right and the correlation is positive, see it slips down to the right, the correlation is the same day it slips down to the right and the correlation is positive or e none of the above is true. And so the correct answer here is going to be yeah. Yeah. And that's because the slope and the correlation coefficient will have the same sign. Mhm. Yeah. Yeah. Mhm. Mhm. So multiplying every y value by negative line will change the sign but it won't change the correlation. So we know that the slope will be to the right and it will be a correlation coefficient of plus 0.57 So again, that will be answer B.

Hi, everybody. So today we're gonna be going over problem number 16 in Chapter two psychological research, and this problem is asking us about correlation. So I'm gonna write that down here. So I'm first going to draw a bit of a number line to explain correlations. So the closer we get to zero, the weaker. The correlation becomes. So at zero, there's no correlation. The further away we are from zero doesn't matter if it's in the positive or the negative direction. It's mawr. The correlation becomes stronger. So we write that down here, the further away from zero to either the positive or negative side. So it doesn't matter if the value is positive or negative, the stronger the correlation. So the closer you are to zero, the weaker the correlation. So the positive a negative just indicates the direction of the correlation. So I'm gonna write that here direction of correlation. So if the correlation is in the positive direction, that means as one variable increases, we'll just write variable a and this up arrow for increase variable B. The other variable also increases when you see negative. All that means is that as variable A our first variable increases variable B, our second variable decreases. So they're just going in opposite directions when you see a negative correlation and they're going in the same direction when you see a positive correlation. But the actual new miracle value indicates the strength of the correlation. So, for example, of correlation of negative 0.9 is going to be stronger than a correlation of negative point to. So there you go. That's a little bit about correlations.

Hi, everybody. So today we're gonna be going through problem number 14 in Chapter two Psychological research, and this problem is asking us about correlations. So I'm going to draw a number line here. So we have zero plus one and minus one, and I'm first going to explain what the positive and the negative means. So positive. So whenever you see a positive number, when you're talking about correlations means that as one variable increases so just write variable a increases, so does variable B, the other variable. On the other hand, a negative correlation means that a variable a our first variable is increasing variable be our second variable is decreasing. And I just wrote these up and down arrows to symbolize increasing and decreasing. So the strength of the correlation is given by the numeric value. So all right, that numerical value. So, for example, a correlation of minus 0.9 would be stronger then a correlation of minus 0.2. On the other hand, a correlation of plus 0.8 iss stronger, then a correlation of plus 0.3. So essentially the closer that you get to zero, the weaker the correlation So once you get to zero, there's actually no correlation. There's no association between the two variables you're testing. So I'm gonna write that key fact here, the closer you get 20 the weaker which means the less strong the correlation becomes and the larger the numerical value, the stronger the correlation becomes. So there you go. That's a little bit about correlations.


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