In the picture, there is a summary of regression analysis output in the R program. Please comment on the Estimate, Std. Error, t value, Pr(>|t|), F-statistic , P value and Residual standard error.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
In the picture, there is a summary of regression analysis output in the R program. Please comment on the Estimate, Std. Error, t value, Pr(>|t|), F-statistic , P value and Residual standard error.
![call:
1m(formula = lifeexpectancy - gdp + thinness1019years + hivaids +
incomecompositionofresources + percentageexpenditure + schooling +
adultmortality + bmi, data = data)
Residuals:
Median
1Q
-20.9507 -2.1990 -0.0606
Min
3Q
2.3697
22.3862
Max
Coefficients:
Estimate Std. Error t value Pr(>|t|)
5.481e+01 5.110e-01 107.254 < 2e-16 ***
(Intercept)
gdp
thinness1019years
hivaids
0.010 *
-9.929e-02 2.293e-02 -4.330 1.55e-05 ***
< 2e-16 ***
3.587e-05 1.393e-05
2.576
-4.933e-01 1.834e-02 -26.905
incomecompositionofresources 8.745e+00 6.902e-01 12.671 < 2e-16 ***
percentageexpenditure
schooling
adultmortality
bmi
1.245e-04 9.005e-05
1.383
0.167
< 2e-16 ***
< 2e-16 ***
7.316 3.44e-13 ***
9.418e-01 4.532e-02 20.781
-1.777e-02 8.769e-04 -20.268
4.099e-02 5.602e-03
Signif. codes: 0 ****
0.001 **' 0.01 *' 0.05 .' 0.1
1
Residual standard error: 4.165 on 2449 degrees of freedom
(480 observations deleted due to missingness)
Multiple R-squared: 0.8136,
F-statistic:
Adjusted R-squared: 0.813
1336 on 8 and 2449 DF, p-value: < 2.2e-16](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc3a1a2a1-eba7-4b54-b7a0-176f18e662d0%2Faf9bf7f7-c0fa-4b54-8804-2d34f861798e%2F608yh54q_processed.jpeg&w=3840&q=75)
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