Let's say you then decide to enter the variables age and age-squared. The following are the regression results after adding the age and age-squared (age2) variables. *see image* Question: Based on the output above, is it proven that age has an influence on teaching evaluation scores?
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.
Let's say you then decide to enter the variables age and age-squared. The following are the regression results after adding the age and age-squared (age2) variables.
*see image*
Question: Based on the output above, is it proven that age has an influence on teaching evaluation scores?
![Source |
df
MS
Number of obs
463
F (8, 454)
10.59
22.3710531
2.79638164
Model |
Residual |
8
Prob > F
0.0000
119.867567
454
.264025478
0.1573
R-squared
Adj R-squared
0.1424
--
Total |
142.23862
462
.307875801
Root MSE
.51383
course eval |
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
beauty |
.1596534
.0319688
4.99
0.000
.0968283
.2224785
age |
age2 |
intro |
onecredit |
female |
.0195252
.023067
0.85
0.398
-.0258062
.0648567
-.0002223
.0002371
-0.94
0.349
-.0006883
.0002437
.0024414
.0550216
0.04
0.965
-.1056872
.1105699
.6197589
.1123215
5.52
0.000
.3990243
.8404935
-.1881177
.0513407
-3.66
0.000
-.2890127
-.0872227
-.3312539
minority |
nnenglish |
-.1795689
.0771854
-2.33
0.020
-.0278839
-.2432153
.1070294
-2.27
0.024
-.4535498
-.0328809
cons |
3.677032
.5431252
6.77
0.000
2.609681
4.744383
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