List the regression equation for the output presented below. If someone has scores of 7 on X and 15 on Z, then =____. Is the regression of Y on X and Z significant (i.e., is R2 in the population greater than zero)? Cite statistics to support your answer.
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.
. List the regression equation for the output presented below.
If someone has scores of 7 on X and 15 on Z, then =____.
Is the regression of Y on X and Z significant (i.e., is R2 in the population greater than zero)? Cite statistics to support your answer.
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.445 |
.198 |
.148 |
.85763 |
|
Model |
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
1 |
Regression |
6.200 |
2 |
3.100 |
4.215 |
.023 |
|
|
Residual |
25.744 |
35 |
.736 |
||
|
|
Total |
31.944 |
37 |
|
| Model |
Unstandardized Coefficients |
Standardized Coefficients |
T | Sig | |
|
B Std. Error |
Beta |
||||
| 1 (Constant) | 2.911 .581 | 5.010 | .000 | ||
| X |
.075 .041 |
.307 |
1.840 |
.044 | |
|
z |
-.080 .062 |
-.213 |
-1.278 |
.209 |
From the output below, the regression equation in three variables (two independent and one dependent) is given as :
For the given values of X and Y,
The hypothesis for for a multiple linear regression model is :
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