Select two variables and Indicate the scale of measurement for each variable (nominal, ordinal, or scale). State the null and research hypotheses. Explain why it is a one- or two-tailed hypothesis. What is the degree of freedom? What is the critical value? Present results in APA format. What is a potentially confounding variable in this scenario. Why might it confound interpretations of the data? Variable names and descriptions0 = male; 1 = femalenumber of stressful life events that had occurred in the last yearGenderEventsSATISFACTIO average Likert-based (1-5) response to survey assessing workplace satisfaction (higher indicateshigher satisfaction)this number represents identification of OSHA hazards before completing the annual OSHAtraining (higher # = identification of more errors)this number represents identification of OSHA hazards after completing the annual OSHAtraining (higher # = identification of more errors)employee type (1 = sales; 2 = warehouse; 3 = management)skills assessment taken within the first week on the job (higher = better skills)skills assessment completed after 6 months on the job (higher = better skills)skills assessment completed after 1 year of service (higher = better skills)salary at time of hirecurrent salaryError1Error2EmployeeSkills1Skills2Skills3Salary1Salary2number of years employedPersonality type (1 = Type “A" or 2 = Type "B")YearsPersonality

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Select two variables and Indicate the scale of measurement for each variable (nominal, ordinal, or scale).

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter5: Inverse, Exponential, And Logarithmic Functions

Section: Chapter Questions

Problem 12DE

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Question

Select two variables and Indicate the scale of measurement for each variable (nominal, ordinal, or scale). State the null and research hypotheses. Explain why it is a one- or two-tailed hypothesis. What is the degree of freedom? What is the critical value? Present results in APA format. What is a potentially confounding variable in this scenario. Why might it confound interpretations of the data?