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| dc.contributor.author | Carter, Mary Alex | |
| dc.date.accessioned | 2020-04-20T16:12:18Z | |
| dc.date.available | 2020-04-20T16:12:18Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | https://hdl.handle.net/10428/4201 | |
| dc.description.abstract | The question being posed in the study is “What factors predict the percentage of women in a state legislature?”. The units of analysis are the 50 states. The independent variables investigated are the percentage of votes for Trump in the 2016 election per state, population density per square mile, percentage population 65 and older per state, percentage with a bachelor’s degree or higher, 2018 per capita income, and the region of each state. The dependent value is the percentage of women elected in state legislatures. The relationship between the independent and dependent variables is expressed by five scatterplots and an analysis of variance (ANOVA). Among the independent variables, the percentage of votes for Trump in the 2016 election per state, percentage with a bachelor’s degree or higher, and 2018 per capita income were statistically significant. The percentage of votes for Trump in the 2016 election per state had a negative correlation while the other two had a positive correlation. The ANOVA showed that region explains 28% of the variance in the percentage of women elected into state legislatures. | en_US |
| dc.title | Factors that Lead to Women Being Elected to State Legislatures | en_US |
| dc.type | Presentation | en_US |
