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# The relationship between changing of labor force(total labor number ) and Unemployment rate - Scholarship Essay Example

Summary
εij is the random error term which is normally distributed with mean zero and constant variance σ2.The estimate of β is 0.207 which is not significant at 5% since the p-value of 0.207 is greater than 5%level of significance.
From the results above an Adjusted R-squared:…

## Extract of sample "The relationship between changing of labor force(total labor number ) and Unemployment rate"

The relationship between changing of labor force(total labor number and Unemployment rate Table: Researched data for unemployment rate and labor force
RESULTS
REGRESION MODEL
> linear_2
Call:
lm(formula = unemployment_rate ~ labor_force1)
Coefficients:
(Intercept) labor_force1
5.460e+00 9.854e-06
> summary(linear_2)
Call:
lm(formula = unemployment_rate ~ labor_force1)
Residuals:
Min 1Q Median 3Q Max
-1.37110 -0.48546 -0.09936 0.50767 1.79138
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.460e+00 2.123e-01 25.718 linear_cor
Pearsons product-moment correlation
data: labor_force and unemployment_rate
t = 1.2783, df = 50, p-value = 0.207
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.09985401 0.42992268
sample estimates:
cor
0.177894
DISCUSSION
Pearsons product-moment correlation gives a value of 0.177894 as the estimate of the correlation coefficient β with a p-value of 0.207 which is greater than 5% this is a clear indication that unemployment rate doesn’t influence the labour force at 5% level of significance.
Reference
Bureau of Labour Statistics. Regional And State Employment And Unemployment — March 2015. U.S Department of Labour, 2015. Retrieved from: http//www.bls.gov/new.release/pdf/laus.pdf Read More
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