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Project D_Doctors for the Poor? Do the poor have access to doctors? We might expect states with more poverty to have fewer doctors. Would doctors

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Project D_Doctors for the Poor? Do the poor have access to doctors? We might expect states with more poverty to have fewer doctors. Would doctors be likely to start practice in an area where a good proportion of the population would be unable to pay for medical services? The table on the next page gives data on the percent of each state?s residents living below the poverty line and on the number of M.D.?s per 100,000 residents in each state. 1. Make a scatterplot and calculate a least squares regression line suitable for predicting M.D.?s per 100,000 from poverty rate. Draw another scatterplot with the regression line superimposed. Explain what you see. Are you surprised? 2. One ?state? is an outlier. Identify the ?state.? This ?state? has many M.D.?s and a high poverty rate. Identify this ?state? on your scatterplot, and explain why this point may strongly influence the least-squares regression line. 3. Calculate the regression for the remaining states, omitting the outlier. Add a new scatterplot with both lines. Identify the two regression lines. Was this point influential? What does it mean to say that a point is influential? 4. Comment on the scatterplot and the regression line for the data after omitting the outlier. REPORT: Write a report that summarizes your investigation. Refer to the Project guidelines and rubric for information on preparing your report. Write as if you are telling a story, but don?t be overly familiar. Try to keep graphs and your commentaries about these graphs together on the same page, if possible, so the reader won?t have to flip back and forth when reading your report. GRADING: The score awarded for this project will depend on the quality of your analyses, the clarity of your explanations, the appropriateness of your conclusions, and whether you adhered to the project guidelines and rubric. -Data Table and Rubric, please reference. -They are both provided via attachment.image text in transcribed

Poverty and M.D.'s in the states State Poverty % M.D.'s per 100,000 State Poverty % M.D.'s per 100,000 Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware D.C. Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri 15.1 8.6 15.2 16.4 15.3 8.6 8.4 10.1 19.7 13.3 13.7 11.9 13.9 10.4 8.3 8.7 10.5 13.8 18.2 10.4 7.6 10.9 10.3 9.1 16.8 11.1 198 167 202 190 247 238 354 234 737 238 211 265 154 260 195 173 203 209 246 223 374 412 224 249 163 230 Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming 15.9 11.0 11.0 8.9 8.5 20.8 15.7 13.0 13.9 11.4 13.5 13.1 10.6 11.4 12.8 11.7 13.2 15.6 7.9 9.6 9.8 9.2 16.7 8.5 11.9 190 218 173 237 295 212 387 232 222 235 169 225 291 338 207 184 246 203 200 305 241 235 215 227 171 Assessment Sheet_D General 1 1 1 1 1 1 2 2 2 2 2 2 3 4 Followed instructions for the investigation. 3 3 3 3 3 4 4 4 4 4 Report has all the required components: Introduction (state the problem/background information) Analysis Conclusions Report is grammatically correct and free of spelling errors. Report is clear and unambiguous. 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 Presented the data set Plotted a scatterplot of the data Discussed unusual observations; flagged any regression outliers Calculated the correlation and interpreted it Calculated descriptive statistics for the two distributions Performed least-squares regression and displayed LSRL equation Plotted the scatterplot with the LSRL Calculated the coefficient of determination (r2) and interpreted it Conclusions are reasonable/Summary is adequate Specific 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 Extra Credit 1 2 3 4 Constructed a side-by-side boxplots to visualize the groups OR did a comparable display 1 2 3 4 Explained concepts such as positive association, correlation, the least squares procedure, etc. 1 2 3 4 Constructed residual plots to assess linearity 1 2 3 4 Other: Score: ___________ STA 2023_Holmes

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