Homework Sourseq3 The data file provides data on age years of education und
q3. The data file provides data on age, years of education, undergraduate GPA, years in current job, and salary. Compute the correlation matrix for these variables. What conclusions can you draw about the strength of the linear relationship between each pair of variables?
| Gender | Age | Marital Status | Years Education | MBA | UG Concentration | Undergraduate GPA | Years in Current Job | Salary |
| M | 25 | Divorced | 15 | No | Liberal Arts | 2.9 | 4 | $28,260 |
| M | 28 | Divorced | 16 | No | Liberal Arts | 3.1 | 6 | $43,392 |
| F | 48 | Widowed | 17 | No | Sciences | 3 | 24 | $56,322 |
| F | 23 | Married | 14 | No | Engineering | 3.5 | 2 | $26,086 |
| F | 32 | Married | 16 | No | Engineering | 3.2 | 8 | $36,807 |
| M | 57 | Married | 18 | No | Engineering | 3.7 | 18 | $57,119 |
| M | 45 | Married | 15 | No | Other | 2.8 | 4 | $48,907 |
| M | 32 | Divorced | 16 | No | Sciences | 2.6 | 9 | $34,301 |
| M | 25 | Married | 17 | No | Liberal Arts | 3.3 | 3 | $31,104 |
| F | 57 | Married | 18 | No | Engineering | 3.3 | 16 | $60,054 |
| M | 42 | Married | 16 | No | Liberal Arts | 3.5 | 9 | $41,420 |
| F | 25 | Married | 16 | No | Business | 3.2 | 2 | $36,508 |
| F | 38 | Married | 16 | No | Liberal Arts | 2.9 | 7 | $40,015 |
| M | 47 | Married | 16 | No | Engineering | 4 | 2 | $48,329 |
| M | 38 | Married | 17 | No | Business | 4 | 4 | $39,849 |
| M | 31 | Married | 16 | No | Engineering | 3.6 | 5 | $31,985 |
| F | 54 | Married | 16 | No | Other | 3.3 | 15 | $59,160 |
| F | 59 | Married | 18 | Yes | Business | 2.9 | 12 | $60,335 |
| M | 32 | Single | 18 | No | Engineering | 3.4 | 7 | $35,911 |
| M | 55 | Married | 18 | Yes | Engineering | 3 | 13 | $57,814 |
| F | 36 | Divorced | 16 | No | Business | 3.2 | 14 | $42,377 |
| M | 60 | Married | 16 | No | Other | 4 | 20 | $62,430 |
| F | 49 | Divorced | 16 | No | Other | 3 | 2 | $46,928 |
| F | 35 | Married | 16 | No | Liberal Arts | 2.5 | 12 | $34,403 |
| F | 32 | Single | 16 | No | Other | 4 | 4 | $45,714 |
| M | 27 | Married | 18 | No | Sciences | 4 | 3 | $42,247 |
| F | 52 | Single | 16 | No | Engineering | 2.7 | 28 | $54,789 |
| F | 30 | Single | 18 | Yes | Business | 3.7 | 7 | $31,702 |
| F | 33 | Widowed | 16 | No | Sciences | 3.2 | 10 | $34,406 |
| F | 57 | Married | 18 | No | Business | 2.8 | 16 | $84,876 |
| M | 24 | Single | 14 | No | Business | 3.5 | 2 | $27,399 |
| M | 51 | Widowed | 16 | No | Business | 3.2 | 33 | $55,785 |
| F | 30 | Married | 18 | Yes | Sciences | 2.9 | 4 | $34,649 |
| M | 61 | Married | 20 | Yes | Business | 4 | 29 | $64,236 |
| F | 45 | Married | 16 | No | Other | 3.5 | 17 | $50,241 |
| M | 48 | Married | 17 | No | Other | 3.3 | 18 | $42,506 |
| M | 54 | Married | 16 | No | Other | 3.5 | 30 | $58,719 |
| F | 37 | Married | 16 | No | Liberal Arts | 3.2 | 17 | $35,669 |
| F | 29 | Married | 17 | No | Other | 2.9 | 5 | $42,356 |
| M | 64 | Married | 18 | Yes | Sciences | 4 | 26 | $66,621 |
| F | 58 | Married | 18 | Yes | Engineering | 2.9 | 28 | $47,689 |
| F | 33 | Married | 16 | No | Business | 3.4 | 4 | $41,523 |
| F | 47 | Married | 18 | No | Sciences | 3 | 16 | $48,099 |
| F | 35 | Single | 18 | Yes | Business | 3.2 | 6 | $35,124 |
| M | 27 | Married | 16 | No | Business | 4 | 4 | $29,879 |
| F | 32 | Divorced | 16 | No | Liberal Arts | 3 | 12 | $38,745 |
| M | 56 | Married | 16 | No | Liberal Arts | 2.5 | 24 | $65,245 |
| F | 47 | Divorced | 18 | Yes | Sciences | 4 | 19 | $54,245 |
| F | 49 | Married | 18 | Yes | Engineering | 3.4 | 21 | $49,780 |
| M | 42 | Single | 18 | Yes | Engineering | 3.6 | 9 | $42,645 |
| F | 39 | Married | 16 | No | Engineering | 3.2 | 8 | $29,889 |
| M | 34 | Single | 16 | No | Other | 3 | 4 | $34,687 |
| F | 25 | Single | 16 | No | Sciences | 2.9 | 3 | $34,445 |
| M | 56 | Widowed | 16 | No | Liberal Arts | 2.7 | 22 | $50,356 |
| M | 28 | Married | 16 | No | Engineering | 3.7 | 4 | $32,667 |
Solution
SPSS is used for computation( N=55)
Correlations
Age
Years Education
Undergraduate GPA
Years in Current Job
Salary
Age
Pearson Correlation
1
.431**
-.010
.778**
.876**
Years Education
Pearson Correlation
.431**
1
.198
.331*
.432**
Undergraduate GPA
Pearson Correlation
-.010
.198
1
-.076
.002
Years in Current Job
Pearson Correlation
.778**
.331*
-.076
1
.682**
Salary
Pearson Correlation
.876**
.432**
.002
.682**
1
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Correlation between Age and Years Education r = 0.431 is positive and significant.
Correlation between Age and Undergraduate GPA r = -0.010 is negative and not significant.
Correlation between Age and Years in Current Job r = 0.778 is positive and significant.
Correlation between Age and Salary r = 0.876 is positive and significant.
Correlation between Years Education and Undergraduate GPA r = 0.198 is positive and not significant.
Correlation between Years Education and Years in Current Job r = 0.331 is positive and significant.
Correlation between Years Education and Salary r = 0.432 is positive and significant.
Correlation between Undergraduate GPA and Years in Current Job r = -0.076 is negative and not significant.
Correlation between Undergraduate GPA and Salary r = 0.002 is positive and not significant.
Correlation between Years in Current Job and Salary r = 0.682 is positive and significant.
| Correlations | ||||||
| Age | Years Education | Undergraduate GPA | Years in Current Job | Salary | ||
| Age | Pearson Correlation | 1 | .431** | -.010 | .778** | .876** |
| Years Education | Pearson Correlation | .431** | 1 | .198 | .331* | .432** |
| Undergraduate GPA | Pearson Correlation | -.010 | .198 | 1 | -.076 | .002 |
| Years in Current Job | Pearson Correlation | .778** | .331* | -.076 | 1 | .682** |
| Salary | Pearson Correlation | .876** | .432** | .002 | .682** | 1 |
| **. Correlation is significant at the 0.01 level (2-tailed). | ||||||
| *. Correlation is significant at the 0.05 level (2-tailed). |
