Explore BrainMass

# Brief Lab Summary

This content was COPIED from BrainMass.com - View the original, and get the already-completed solution here!

Question 1
Group Statistics
HIGHEST YEAR OF SCHOOL COMPLETED N Mean Std. Deviation Std. Error Mean
RESPONDENTS INCOME 12 283 12.24 18.415 1.095
16 161 17.57 21.854 1.722

Independent Samples Test
Levene's Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
Lower Upper
RESPONDENTS INCOME Equal variances assumed 1.340 .248 -2.734 442 .007 -5.325 1.948 -9.153 -1.497
Equal variances not assumed -2.609 288.642 .010 -5.325 2.041 -9.342 -1.308

Question 2
Correlations
NUMBER OF CHILDREN RS HIGHEST DEGREE
NUMBER OF CHILDREN Pearson Correlation 1 -.111**
Sig. (2-tailed) .001
N 955 955
RS HIGHEST DEGREE Pearson Correlation -.111** 1
Sig. (2-tailed) .001
N 955 955
**. Correlation is significant at the 0.01 level (2-tailed).
Question 3

Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 RS HIGHEST DEGREEb . Enter
a. Dependent Variable: NUMBER OF CHILDREN
b. All requested variables entered.

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .111a .012 .011 1.666
a. Predictors: (Constant), RS HIGHEST DEGREE

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 32.852 1 32.852 11.837 .001b
Residual 2645.043 953 2.775
Total 2677.895 954
a. Dependent Variable: NUMBER OF CHILDREN
b. Predictors: (Constant), RS HIGHEST DEGREE
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 2.232 .089 25.152 .000
RS HIGHEST DEGREE -.153 .045 -.111 -3.440 .001
a. Dependent Variable: NUMBER OF CHILDREN
Talk about constant, slope and R2

https://brainmass.com/statistics/regression-analysis/brief-lab-summary-516360

#### Solution Preview

Let's first see what the ordinary least squared regression line is all about. The regression line determines a linear equation that best fits the values of x (predictor) and y (dependent).
In our case this line is 2.232 - 0.153x = y.
So what is the interpretation of this line?
2.232 (the constant) is called the y intercept and it's the value of y when the value of x is zero. i.e. it is the number of children when there is no RS Higher Degree.
-0.153 (the slope or gradient) is the rate of change of y with respect to a unit change in x. In ...

#### Solution Summary

A step by step explanation of all the statistical parameters of a simple linear regression analysis based on the least square estimate.

\$2.19