SPSS 2 Poster
davlim768x
PosterJaylanParker1.pptxInfant Mortality
Jaylaan Parker
Tennessee State University
Hypotheses
In counties where there are a high volume of people with no insurance, infant mortality rates are high.
Infant mortality rates are high in states where there are failing scores on reproductive freedom.
Infant mortality rates are high in counties where high proportions of the population have food insecurity
Total number of counties: 1260
| Variable | Level of Measurement |
| Infant Mortality | Interval-ratio |
| No insurance | Interval-ratio |
| Food insecurity | Interval-ratio |
| Reproductive Rights | Nominal |
| Census division | Nominal |
| Variable | Mean | Standard deviation | C.I. (95%) |
| Infant mortality | 6.84 | 2.13 | 6.71 – 6.97 |
| No insurance | 0.10 | 0.05 | 0.10 – 0.11 |
| Food insecurity | 0.07 | 0.05 | 0.07 – 0.08 |
| Reproductive rights | 39.2% failing | N/A | N/A |
| New England | Mid Atlantic | East North Central | West North Central | Southeast | East South Central | West South Central | Mountain | Pacific | Total | |||
| Passing grade for women’s reproductive rights | Failing grade for reproductive freedom | Count | 0 | 0 | 114 | 68 | 105 | 86 | 98 | 23 | 0 | 494 |
| % within census division | 0.0% | 0.0% | 52.5% | 60.7% | 36.6% | 55.5% | 55.7% | 30.3% | 0.0% | 39.2% | ||
| Passing grade for reproductive freedom | Count | 38 | 111 | 103 | 44 | 182 | 69 | 78 | 53 | 88 | 766 | |
| % within census division | 100.0% | 100.0% | 47.5% | 39.3% | 63.4% | 44.5% | 44.3% | 69.7% | 100.0% | 60.8% | ||
| Total | Count | 338 | 111 | 217 | 112 | 287 | 155 | 176 | 76 | 88 | 1260 | |
| % within census division | 100.0% | 100.0% | 100.0% | 100.0% | 100.0% | 100.0% | 100.0% | 100.0% | 100.0% | 100.0% |
| Group Statistics | |||||
| passing grade for women's reproductive rights | N | Mean | Std. Deviation | Std. Error Mean | |
| infant mortality rate | Failing grade for reproductive freedom | 494 | 7.31482088500 | 2.170638617000 | .097661648500 |
| Passing grade for reproductive freedom | 766 | 6.52927138000 | 2.351413888000 | .084960037200 |
This relationship is significant at p < 0.001, therefore you can see that reproductive freedom has an effect on infant mortality
| Correlations | |||
| infant mortality rate | percentage of population with not insurance | ||
| infant mortality rate | Pearson Correlation | 1 | .262** |
| Sig. (2-tailed) | .000 | ||
| N | 1260 | 1260 | |
| percentage of population with not insurance | Pearson Correlation | .262** | 1 |
| Sig. (2-tailed) | .000 | ||
| N | 1260 | 1260 | |
| **. Correlation is significant at the 0.01 level (2-tailed). |
There is a positive relationship between infant mortality and no insurance. The correlation is weak, but significant.
Bristol County, Massachusetts was found to have a much higher infant mortality rate than predicted based on no insurance.
| Correlations | |||
| infant mortality rate | percentage population with food insecurity | ||
| infant mortality rate | Pearson Correlation | 1 | .236** |
| Sig. (2-tailed) | .000 | ||
| N | 1260 | 1259 | |
| percentage population with food insecurity | Pearson Correlation | .236** | 1 |
| Sig. (2-tailed) | .000 | ||
| N | 1259 | 1259 | |
| **. Correlation is significant at the 0.01 level (2-tailed). |
Limitations
There is no selection bias into the sample, meaning that counties with higher infant mortality rates are more likely to enter the sample.
We have two different levels for unit of analysis, which are counties and states. A more advanced analysis would use a multilevel model.
B
