In a research study, a power analysis was conducted to determine the sample size required to detect a significant effect. The power analysis showed that a sample size of 50 was needed to achieve 80% power. If the researcher decides to reduce the sample size to 30, what will happen to the power of the study? a. Power will decrease b. Power will remain the same c. Power will increase d. Itisimpossible to tell without conducting a new power analysis Which of the following is an example of a research question that would be best addressed using a one- tailed test? a. Is there an increase in employee productivity after a new training program? Is there a difference in |IQ scores between men and women? c. ls there a decrease in the number of crimes committed after the implementation of a community policing program d. Is there a relationship between height and weight? The tolerance value in a multiple regression model can be used to detect: a. the impact of missing data on the regression coefficients b. multicollinearity between predictors o the strength of the relationship between the predictors and the outcome variable d. outliers in the outcome variable Which of the following is NOT an assumption for simple linear regression? a. Random sample b. Independence Normality of residuals d. Linearity .0 | Which of the following can be used to detect multicollinearity in a multiple regression model? a. R-squared value b. Tolerance c. Standard error of the regression coefficients d. Correlation coefficient If the p-value for a regression coefficient is less than the alpha level (e.g., 0.05), what can be concluded about the relationship between the predictor and the outcome variable? a. There is a significant relationship between the predictor and the outcome variable b. There is no significant relationship between the predictor and the outcome variable c. The direction of the relationship between the predictor and the outcome variable cannot be determined d. The predictor is not a good fit for the regression model Which of the following statements is true about the difference between correlation analysis and regression analysis? a. Correlation analysis is only used for categorical variables, while regression analysis is used for continuous variables b. Correlation analysis is used to determine the strength of the relationship between two variables, while regression analysis is used to predict the value of one variable on the basis of other variables c. Correlation analysis and regression analysis are interchangeable and can be used in the same way to analyze data d. Correlation analysis is used to predict the value of one variable on the basis of other variables, while regression analysis is used to determine the strength of the relationship between two variables