Correlation & Regression

Please see in case 2, it says that the z score for employment is 2.513. This shows that the distance between the individual values and the mean is 2.513 units of VARIANCE.

• True

• False

Parametric statistics require more specific assumptions about the distribution of data

• True

• False

In correlation analysis with parametric statistics, it must fulfill the following assumption tests

• normality residual

• normality data

The correct statement regarding the residual normality (as an assumption check) in correlation analysis is

• in large samples, it is necessary to test the significance of Kolmogorov Smirnov or Shapiro Wilk.

• visual inspection through q-q plot or p-p plot

• in small samples, it is necessary to test the significance of Kolmogorov Smirnov or Shapiro Wilk.

when researcher measures the relationship between two variables after controlling the influence of one or more third variables, we used

• partial correlation

• zero order correlation

• z-test

• regression analysis

if you want to see the relationship between education and openmindedness, then the correlation analysis performed is

• pearson

• spearman's rho

The correct statement is

• there is a significant correlation between openmindedness and confirmation bias with a correlation value of -0.218.

• there is a significant correlation between openmindedness and confirmation bias with a correlation value of 0.033

• no significant correlation between openmindedness and confirmation bias with a correlation value of -0.181

• no significant correlation between openmindedness and confirmation bias with a correlation value of 0.080

The correct statement of the correlation between openmindedness and confirmation bias is

• the correlation value at the population level is -0.218

• population-level correlation values fall within the range of -0.018 to -0.402.

The wrong statement regarding the difference between the regression test and pearson correlation is

• The Pearson correlation focuses on how 2 variables are related to each other in a linear relationship without designating one variable as independent or dependent.

• Regression analysis is predictive model, helping model the relationship between one or more independent variables and a dependent variable to predict possible values.

• Regression analysis is multivariate analysis

• The regression test focuses on how two variables are related to each other in a linear relationship without designating one variable as independent or dependent.

The correct statement related to the regression formula is

• E is independent variable when there is no contribution from the independent variables.

• b is variabel dependent when there is no contribution from the independent variables.

• a is predicted value of Y when there is no contribution from the independent variables.