What R code do I use to solve this?
A researcher interviews 50 employees of a large manufacturer and collects data on each worker’s hourly wage (Wage), years of higher education (EDUC), experience (EXPER), and age (AGE).
Wage,EDUC,EXPER,AGE,Male 37.85,11,2,40,1 21.72,4,1,39,0 14.34,4,2,38,0 21.26,5,9,53,1 24.65,6,15,59,1 25.65,6,12,36,1 15.45,9,5,45,0 20.39,4,12,37,0 29.13,5,14,37,1 27.33,11,3,43,1 18.02,8,5,32,0 20.39,9,18,40,1 24.18,7,1,49,1 17.29,4,10,43,0 15.61,1,9,31,0 35.07,9,22,45,0 40.33,11,3,31,1 20.39,4,14,55,0 16.61,6,5,30,1 16.33,9,3,28,0 23.15,6,15,60,1 20.39,4,13,32,0 14.88,4,9,58,1 13.88,5,4,28,0 17.65,6,5,40,1 15.45,6,2,37,0 26.35,4,18,52,1 19.15,6,4,44,0 16.61,6,4,57,0 18.39,9,3,30,1 15.45,5,8,43,0 18.02,7,6,31,1 13.44,4,3,33,0 17.66,6,23,51,1 16.96,4,15,37,0 14.34,4,9,45,0 15.45,6,3,55,0 17.43,5,14,57,0 35.89,9,16,36,1 20.39,4,20,60,1 11.81,4,5,35,0 15.45,9,10,34,0 17.66,5,4,28,1 13.87,6,1,25,0 16.35,7,10,43,1 15.45,9,2,42,1 23.67,4,17,47,0 16.02,11,2,46,1 23.15,4,15,52,0 24.18,8,11,64,0
a. Estimate: Wage = β0 + β1EDUC + β2EXPER + β3AGE + ε. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)
b. Are the signs as expected?
EDUC?
EXPER?
AGE?
Answer: y=wage, X1=EDUC, X2=EXPER, X3=AGE
R code:-
Fit=lm(y~X1+X2+X3)
Fit
summary(Fit)
From summary we get intercept , slope coefficients.
What R code do I use to solve this? A researcher interviews 50 employees of a...
A researcher interviews 50 employees of a large manufacturer and collects data on each worker’s hourly wage (Wage), years of higher education (EDUC), experience (EXPER), and age (AGE). Wage EDUC EXPER AGE Male 37.85 11 2 40 1 21.72 4 1 39 0 ⋮ ⋮ ⋮ ⋮ ⋮ 24.18 8 11 64 0 A researcher interviews 50 employees of a large manufacturer and collects data on each worker's hourly wage (Wage), years of higher education (EDUC), experience (EXPER), and age...
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Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.17 4.26 1.68 0.0991 Education 1.81 0.35 5.17 0.0000 Experience 0.45 0.10 4.50 0.0000 Age −0.01...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.73 3.94 1.96 0.0558 Education 1.15 0.39 2.95 0.0050 Experience 0.45 0.11 4.09 0.0002 Age −0.03...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 8.23 4.40 1.87 0.0678 Education 1.23 0.38 3.24 0.0022 Experience 0.53 0.18 2.94 0.0051 Age −0.08...
Here is the information that is needed for this work: A researcher interviews 50 employees of a large manufacturer and colects data on each worker's hourly wage (Wage), years of higher education (EDUC), experience (EXPER) and age AGE). The data can be found in the SPSS 6 Wage excel data file posted on Connect. Use SPSS to generate the output. Upload the one page Word file on to Connect by the due date. The face to face and hybrid students...
An over-the-counter drug manufacturer wants to examine the effectiveness of a new drug in curing an illness most commonly found in older patients. Thirteen patients are given the new drug and 13 patients are given the old drug. To avoid bias in the experiment, they are not told which drug is given to them. To check how the effectiveness depends on the age of patients, the following data have been collected. To examine the differences between salaries of male and...
Using data from 50 workers, a researcher estimates Wage = ?0 + ?1Education + ?2Experience + ?3Age + ?, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.58 4.42 1.71 0.0931 Education 1.68 0.37 4.54 0.0000 Experience 0.35 0.18 1.94 0.0580 Age ?0.06...
Suppose you estimate the following model by OLS: wage = β0 + β1educ + β2exper + u wage : hourly age in dollars educ : years of education exper : years of experience You obtain the following fitted model using STATA, where standard errors are given in parenthesis wage [ = 3.5 + 0.9educ + 1.5exper (2.0) (0.7) (0.5) Number obs. : 523 R 2 = 0.45 For the following questions, make use to the relevant statistical tables. If you...
2 Using data from 50 workers, a researcher estimates Wage BoIEducation + 2Experience B3Age E, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker respectively. The regression results are shown in the following table. 10 points Standard Coefficients t Stat P-Value 0.1310 0.0003 0.0022 Error 4.24 Intercept Education Experience Age 6.52 1.32 1.54 0.34 0.12 3.88 3.25 -0.20 0.39 0.01 0.05...