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Why do correlation coefficients greater than 0.50 rarely occur in the social sciences?Social scientists fail to construct experiments carefully enough to detect lar...

Question

Why do correlation coefficients greater than 0.50 rarely occur in the social sciences?Social scientists fail to construct experiments carefully enough to detect larger correlations_Social scientists have not yet discovered the variables that are the best predictors of human behavior;It is difficult to construct a measure of behavior; e.g- , depression or compassion, that adequately describes the complete range of that behavior of interest.Human behavior is the product of many interacting variabl

Why do correlation coefficients greater than 0.50 rarely occur in the social sciences? Social scientists fail to construct experiments carefully enough to detect larger correlations_ Social scientists have not yet discovered the variables that are the best predictors of human behavior; It is difficult to construct a measure of behavior; e.g- , depression or compassion, that adequately describes the complete range of that behavior of interest. Human behavior is the product of many interacting variables; any single variable will be limited in its association with a behavior:



Answers

What affects correlation? Make a scatterplot of the following data:
The correlation for these data is $0.5 .$ What is respon- sible for reducing the correlation to this value despite a strong straight-line relationship between $x$ and $y$ in most of the observations?

MM. So correlation is a word used when data is quantitative and his squad. Mhm. Mhm. I didn't say to the variables in the section are qualitative when we use the word association. Mhm. Yeah. Mhm. Okay. Carotid pulse in the section our qualitative.

In question, but to we're going to comparing two scenarios. Oh, given bombs we have fast use. But the sample size is 10 and then sample correlation is 0.6. And while this is to be tested 0.1 level of significance in the second case we have a larger sample. 42. But they some poker relation never looks. Comes is the same Russkies. So in the fastest E, we're going to be checking if there's significant reason to conclude that Polina Correlation coefficient off, the population is positive. So that means that the alternative what this is the true, it's positive, its creator. Zero. This is a one tales test and you know what one to test would be used in the top headings and not the original headaches. But we're going to use the half off the headings, that region. So in this case, the fasting you need to do to test this hypothesis is to get the degrees of freedom this case, the degrees of freedom 10 minutes to which is eight. Once we found the degrees of freedom, we need to get bonds for the people and to get the bounce with a P value 0.6 and where treats on the column for 0.60 point 01 So this is the colon mission looking for? And this is the room she's looking for. In this case, we find that the bones for zero point six uh, thes two years 0.6 should be in between 0.58 to 0.666 So the P value is going to be between zero point 0 to 5 gangs zero here to fight on 0.5 Okay, so this is to say that even you is great urban 0.25 and it's less than 0.1 So in this case, real notice that the P value is actually greater, that the level of significant. So we see that p his, uh, and when that happens, we failed to reject the now like this is And when we failed to reject and I like where this is, we make a conclusion that at the 0.1 level of significance, we feels to show that two variables are really in the second case, we have a larger samples size and that means our decrease of freedom, He et Tu minus 40 and that's 42 minutes tune and that's 42. You have 40 degrees of freedom, and in this case we will be testing to see whether there is a significant reason to conclude that the clinic relation off the population is positive. So that means the alternative hypothesis is Rome is greater than zero, just like in this House case. And that means it's also one tears test, and we want to get the P, define the bonds with the P value. So we should be looking at column for 40. And the rule that has 0.0 wants is the same group that we used class tapes. So in this guess what we should we notice that 06 there's no future acting piece for Cruz, but he it seems a safe it would be occupying a position up here. In that case, the PVA new would be much smaller than 0.0 fine so we can conclude that bound for people would be P. He's smaller than 0.0 05 and our level of significance in 0.1 So you see in this case the p the value less than level of significance for factories and a decision to reject that now. And when we reject in Alec Willis's, we conclude that after the 0.1 level off significance, there's evidence off a positive linear relationship between the two variables in the position Alicia ST positive relationship. Because our findings Stephen a 0.6 so in we can compare this to and we'll find that the first case there was a very small sample size only 10 and the second cake taking case. We had largest sighs, and we noticed that they had to seem lena coalition coefficient of 0.6, and also they had to seeing level of significance. But in the first case, the P value was much greater than level of significance, which led to the failure to reject now hypotheses. But in the second case, the P value was small. Other level of significance, which led to reject hypotheses

The relationship. What then include all the variables in one? The question. And it is possible that that have been 10 variables who significant the relationship with multiple during the ready. Thank you.

The values. Oh, individual correlation coefficients. We'll always me smaller than the values. Multiple tradition go fishing because the relationship with more variables will be better able to predict the value. The value's off the dependent value. Thank you.


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