Correlation Between Family Income and Children's Number

Hnull: There is no significant linear relationship between annual family income and the respondents number of children at the 5% significance level

Halt: There is a significant linear relationship between annual family income and the respondents number of children at the 5% significance level

Dependent and independent variable:

Independent variable: Total Family Income

Dependent variable: Number of children

Results:

From the SPSS output below, the correlation coefficient between total family income and number of children is equal to -0.003. This correlation coefficient is weak and does not suggest a significant linear relationship between the two variables tested. Furthermore, the p-value is equal to 0.915 indicating that the correlation is not significant since the value is greater than alpha (0.05). Therefore, we fail to reject the null hypothesis.

From the regression model, it is evident that the Rsquare value is equal to 0.00. This implies that the independent variable cannot be used in predicting the dependent variable in this case. Furthremore, from the model summary it is evident that the coefficient for the dependent variable is not significant since its p value is to 0.915. Therefore, the regression model is not significant.

From the scatterplot, the visual relationship between the two-selected variable is also not evident. This is mainly because from the scatterplot it is not possible to tell the relationship between the two variables as well as the direction of the relationship.

SPSS output and syntax:

GET

FILE='C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav'.

DATASET NAME DataSet1 WINDOW=FRONT.

CORRELATIONS

/VARIABLES=INCOME CHILDS

/PRINT=TWOTAIL NOSIG

/MISSING=PAIRWISE.

Correlations

Notes

Output Created 21-JAN-2016 08:44:02

Comments Input Data C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav

Active Dataset DataSet1

Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 1500

Missing Value Handling Definition of Missing User-defined missing values are treated as missing.

Cases Used Statistics for each pair of variables are based on all the cases with valid data for that pair.

Syntax CORRELATIONS

/VARIABLES=INCOME CHILDS

/PRINT=TWOTAIL NOSIG

/MISSING=PAIRWISE.

Resources Processor Time 00:00:00.00

Elapsed Time 00:00:00.03

[DataSet1] C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav

Correlations

TOTAL FAMILY INCOME NUMBER OF CHILDREN

TOTAL FAMILY INCOME Pearson Correlation 1 -.003

Sig. (2-tailed) .915

N 1341 1339

NUMBER OF CHILDREN Pearson Correlation -.003 1

Sig. (2-tailed) .915 N 1339 1498

REGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT CHILDS

/METHOD=ENTER INCOME.

Regression

Notes

Output Created 21-JAN-2016 08:45:37

Comments Input Data C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav

Active Dataset DataSet1

Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 1500

Missing Value Handling Definition of Missing User-defined missing values are treated as missing.

Cases Used Statistics are based on cases with no missing values for any variable used.

Syntax REGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT CHILDS

/METHOD=ENTER INCOME.

Resources Processor Time 00:00:00.02

Elapsed Time 00:00:00.04

Memory Required 2020 bytes

Additional Memory Required for Residual Plots 0 bytes

[DataSet1] C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav

Variables Entered/Removeda

Model Variables Entered Variables Removed Method

1 TOTAL FAMILY INCOMEb . 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 .003a .000 -.001 1.661

a. Predictors: (Constant), TOTAL FAMILY INCOME

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1 Regression .031 1 .031 .011 .915b

Residual 3690.132 1337 2.760 Total 3690.163 1338 a. Dependent Variable: NUMBER OF CHILDREN

b. Predictors: (Constant), TOTAL FAMILY INCOME

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta 1 (Constant) 1.883 .215 8.748 .000

TOTAL FAMILY INCOME -.002 .019 -.003 -.106 .915

a. Dependent Variable: NUMBER OF CHILDREN

GRAPH

/SCATTERPLOT(BIVAR)=INCOME WITH CHILDS

/MISSING=LISTWISE.

Graph

Notes

Output Created 21-JAN-2016 08:46:44

Comments Input Data C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav

Active Dataset DataSet1

Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 1500

Syntax GRAPH

/SCATTERPLOT(BIVAR)=INCOME WITH CHILDS

/MISSING=LISTWISE.

Resources Processor Time 00:00:02.28

Elapsed Time 00:00:01.90

[DataSet1] C:\Users\PC\AppData\Local\Temp\gss04student_corrrected-2.sav