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Assess and explain whether any of the violations are present and how they may be corrected in a new regression model. After estimating a corrected
Assess and explain whether any of the violations are present and how they may be corrected in a new regression model. After estimating a corrected model, report the final results and make recommendations for policies that your organization could promote to increase female life expectancy.
Pearson's Partial Correlations | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | urban | gdp | radio | phone | hospbed | docs | |||||||||
1. urban | Pearson's r | ||||||||||||||
p-value | |||||||||||||||
2. gdp | Pearson's r | 0.271 | |||||||||||||
p-value | 0.003 | ||||||||||||||
3. radio | Pearson's r | 0.238 | 0.473 | ||||||||||||
p-value | 0.009 | <.001> | |||||||||||||
4. phone | Pearson's r | 0.261 | 0.903 | 0.388 | |||||||||||
p-value | 0.005 | <.001> | <.001> | ||||||||||||
5. hospbed | Pearson's r | 0.116 | 0.400 | 0.227 | 0.418 | ||||||||||
p-value | 0.217 | <.001> | 0.015 | <.001> | |||||||||||
6. docs | Pearson's r | 0.311 | 0.428 | 0.184 | 0.499 | 0.579 | |||||||||
p-value | <.001> | <.001> | 0.044 | <.001> | <.001> | ||||||||||
Note. Conditioned on variables: lifeexpf. |
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