What type of statistical technique is used to find cause and effect relationships between one or more independent variables and one dependent variable (such as job satisfaction)? options: A) association analysis B) regression analysis C) cluster analysis D) market basket analysis
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- Regression analysis and the correlation coefficient can both be used to analyze the relationship between two economic variables. What are the advantages of using regression analysis instead of looking at the correlation coefficient?regression, econometricsO Macmillan Learning A study is designed to examine the relationship between employees' job satisfaction and the amount of sleep they get. Think about creating a data set for this study. Assume that job satisfaction is measured by a scale of 1 (very dissatisfied) to 5 (very satisfied). Cases: Label Variable(s): Quantitative Variable(s): Categorical Variable(s): Explanatory Variable(s): Response Variable(s): Employee's name Answer Bank Job satisfaction Employees Amount of sleep
- Each cell represents a regression with a different outcome variable from Krueger’s (1993) study of workers who use computers. The left hand side variable is log wages. Answer based on column 2 of the above regression table. 1. Write a sentence that explains the relationship the regression is describing in row 2. 2. What is the number in parenthesis? What is it trying to communicate? 3. Write a causal statement that captures what the authors are trying to argue in row 2.Suppose researchers use observational data to study the effect of class size and teacher experience on student score. Which of the following is a confounding variable? Student score 0000 Family income Class size Teacher experienceOil Recovery A U.S. state's Bureau of Economic Geology published a study on the economic impact of using carbon dioxide enhanced oil recovery (EOR) technology to extract additional oil from fields that have reached the end of their conventional economic life. The following table gives the approximate number of jobs for the citizens that would be created at various levels of recovery. Percent Recovery (%) 20 40 80 100 Jobs Created (Millions) 6 6 12 18 Find the regression line. j(r) = Use the regression line to estimate the number of jobs (in millions) that would be created at a recovery level of 50%. million jobs
- Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,681.31+3418.97(Education)+1194.78(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree (10 years of education). How much more money would we expect the employee with a master's degree to make?Sales Sales Force Sales Force Training Performance Effectiveness Sales Force Customer Orentation Please perform the quantitative analysis with the above variables. 1.0 Introduction 1.1 Objectives 1.2 Assumptions 1.3 Other Considerations 1.4 HypothesesWhile the salaries for all three countries (for the three industries shown) are all smaller than U.S. salaries, there is a wide variation. Of the options below, which has the greatest percentage difference in salaries across countries? SNAPSHOT Outsourcing U.S. salary 11% China India 22 18% 30% 38% 36% Mexico 50% 42% 55 50% 84% Information technology project manager 100% Software engineer 100% Customet service representatis 100% Click to view larger image. NOTE: Salaries are presented as a percentage of the typical U.S., salary. the difference in wages for software engineers in Mexico and India O the difference in wages for customer service representatives in Mexico and India the difference in wages for information technology project managers in China and Mexico O the difference in wages for information technology project managers in China and India
- What are the four assumptions of linear regression (simple linear and multiple)?To investigate the impact of wage on the number of workers employed two models of labour demand are estimated for British firms. Model 1 is a univariate model with labour employed (L) function of average yearly wage (W) with all variables measured in logs : L = 7.26 -0.51 × W Model 2 is a multivariate model with labour employed (L) function of output (Q) and average wage (W) with all variables measured in logs : L = -0.20 +0.85 × Q - 0.91 × W Select the terms from the drop down lists to complete the sentence below correctly: The coefficient of the wage variable in Model 2, -0.91, is the employed and it measures the relative change in labour dem overall biased partial growing impact of wage on labour relative increase in wage whenthe similarity between the correlation research method and experimental research method