For this case, we would like to investigate the impact of conflict on the quality of work. Research considers there to be two primary types of conflict (1) relationship conflict, (2) task conflict. Relationship conflict is the conflict that occurs between members of the group. This may invoke strong feelings of anger and frustration when dealing with individuals. Task conflict on the other hand looks at the innate ability to solve the task itself. A high task conflict implies an individual may or may not have the necessary skills to accomplish the task. Quality is measured by three variables- pride, ability to check work, and meeting expectations.
Produce a two page paper in APA format that answers the following:
What is the strength of the correlations between the variables?
What measure of quality is impacted most by relationship conflict? Task Conflict?
What is the significance of the correlations?
How might you improve quality in the workplace?
In answering these questions, please include necessary tables, figures, and text. Please remember, to focus on conveying the meaning of the data to the audience.
Please see the attachments.
Please note that this is not a hand in ready ...
The solution provides step by step method for the calculation of correlation coefficient and test statistic for significance of correlation coefficient. Formula for the calculation and Interpretations of the results are also included.
How does correlation analysis differ from regression analysis?
1. (a) How does correlation analysis differ from regression analysis? (b) What does a correlation coefficient reveal? (c) State the quick rule for a significant correlation and explain its limitations. (d) What sums are needed to calculate a correlation coefficient? (e) What are the two ways of testing a correlation coefficient for significance?
12.48 In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald's employees. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two-tailed test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = t2 for the slope. (f) In your own words, describe the fit of this regression.
12.50 In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two- tailed test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = t2 for the slope. (f) In your own words, describe the fit of this regression
13.30 A researcher used stepwise regression to create regression models to predict BirthRate (births per 1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.
13.32 An expert witness in a case of alleged racial discrimination in a state university school of nursing introduced a regression of the determinants of Salary of each professor for each year during an 8-year period (n = 423) with the following results, with dependent variable Year (year in which the salary was observed) and predictors YearHire (year when the individual was hired), Race (1 if individual is black, 0 otherwise), and Rank (1 if individual is an assistant professor, 0 otherwise). Interpret these results.
14.16 (a) Plot the data on U.S. general aviation shipments. (b) Describe the pattern and discuss possible causes. (c) Would a fitted trend be helpful? Explain. (d) Make a similar graph for 1992-2003 only. Would a fitted trend be helpful in making a prediction for 2004? (e) Fit a trend model of your choice to the 1992-2003 data. (f) Make a forecast for 2004, using either the fitted trend model or a judgment forecast. Why is it best to ignore earlier years in this data set?
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