Question
To # 8 & 9 please help answer this
for example, 28 separate bivari e rs an be computed. With 10 variables, there are 45 rs. In general, the number of bivariate correlations is equal t o k (k 1)/2, where k indicates the number of variable Excerpt 3.6, we see a orrelation matrix that summarizes the measured bivariate relationship a ong six variables In the study associated with this excerpt 90 college students too a test of creativity (the Idea Generation Tes) and filled out a personality survey that measured each student on the "Big 5" dimension of Open ness. Conscie ousness. Extravers Agree eness nd Neuroticism. As you can See this correlation matrix contains rs arranged in a triangle. Each r indicates the correlation between the two variables that label that r's row and column. For example, e value of .38 is the correlation between Openness and Agreeablene EXCERPT 3.6 A Standard Correlation Matrix TABLE 3 Correlations Between the Idea Generation Test and Personality Dimensions Test 1. Idea Generation 2. Openness 3. Conscientiousne 4. Extraversion 22 02 08 5. Agreeableness 38 28 6. Neuroticism 39 10 Source: Ellwood, S., Pallier, G., Snyder, A., & Gallate, J. (2009). The incubation effect: Hatching a solution? Creativity Research Journal, 21(1), 6-14 Two things are noteworthy about the correlation matrix shown in Excerpt 3 First, when a row and a column refer to the same variable (as is the case with th row and the left column, the second row and the second column, etc.), there positioned at the intersection of that row and column. Clearly, the correlati variable with itself is perfect. Thus, the correlation coefficients (each equ to 1) n the diagonal are not informative: the "meat" of the correlation matrix elsewhere Second, there are no correlation coefficients above the diagonal. If corre appear there, they would be a mirror image of the rs positioned below diagonal. The value .10 would appear on the top row in the second column, would appear on the top row in the third column, and so on. Such rs, if they w out into the correlation matrix, are fully redundant with the rs that already are accordingly, they add nothing.
Explanation / Answer
From the excerpt, the strongest correlation is between the variables Test 4 and Agreeableness since the scalar value corresponding to them is the highest which is 0.41 .
Also, from the excerpt, the weakest correlation is between the variables Test 1 and Agreeableness since the scalar value corresponding to them is the lowest which is 0.00 , in other words no correlation.
