Exam 14: Pearson Correlation and Regression: Inferential Aspects

Suppose you were interested in conducting a study examining how ratings of similarity between oneself and another person were related to how attracted one is to the other person.You conduct this study by giving participants a description of a person named "Sarah." Participants are asked to read the description and then rate on a scale from 1 to 10 how similar Sarah is to themselves.You also ask each participant to rate on a scale from 1 to 20 how likeable they think Sarah is. X = rating of similarity to oneself Y = rating of likability of the target ("Sarah") 62 people participate in your study,and you obtain the following data: SCP = 66 SS_X = 40 SS_Y = 136 Using your calculations above,if you asked another person who was not in your original experiment to rate the similarity between themselves and "Sarah" on the same scale from 1 to 10,and their rating of similarity = 5,what would you predict their likability rating to be?

Which one of the following is NOT a condition under which the Pearson correlation is typically used?

A relationship might exist in a sample even though it does not exist in the population,because of:

If the researcher suspects that the strength of the relationship between two variables in the population is .40,as indexed by the correlation coefficient squared,what sample size should she use in a study involving an alpha level of .05,directional test,in order to achieve a power of .80?

In general,if you find a statistically significant r,what can you directly conclude about the regression line?

Confidence intervals for the correlation coefficient indicate that we are 95% confident that the true ____________________ coefficient falls within that range.

r² represent the proportion of variability that is shared by the two variables.

An important weakness of regression is that prediction procedures cannot be applied to individuals who were not included in the original data set.

Fisher's transformation of r to z permits us to _____.

Variance homogeneity can be problematic for the t test of the correlation coefficient, especially if one is going to pursue estimation of the population regression equation.

The mean of a sampling distribution of the correlation coefficient is approximately:

If you compute a statistically significant negative r between two variables (X and Y),this tells you that _____.

In the regression equation of a population,the symbol ?

The Pearson correlation cannot be used to determine the relationship between two variables when _____.

The assumption that the population distributions of X and Y are such that their joint distribution (that is,their scatterplot)represents a bivariate normal distribution implies that the distribution of Y scores at any value of X is normal in the population.

Imagine you are interested in researching the relationship between job experience and income among early-career working professionals.You take a random sample of 32 professionals from the nearest city,and you ask them to report their annual income and submit a resumé outlining their professional experience.You later calculate their years of experience from their resumés.You compute the following information: Assume,for the above example,that you calculated the estimated standard error of the estimate to be,11.20.How should this standard error of the estimate be interpreted?

Because the calculation of t depends only on the value of r,it is impossible to determine values of r that will lead to a rejection of the null hypothesis that ñ = 0,given a certain sample size.

Pearson correlation is used to analyze the relationship between two variables when both variables are qualitative and measured on at least an ordinal level.

Under certain conditions,the t test for the Pearson correlation is robust with respect to violations of normality and homogeneity of variance.

The nature of the relationship between two correlated variables is determined through examination of the sign of the correlation coefficient observed in the sample.