Using a data set and this data dictionary I need question 5(.1, .2, and .3) answered please. I NEED THE R CODE THAT WAS
Posted: Tue Nov 23, 2021 9:28 am
Using a data set and this data dictionary I need
question 5(.1, .2, and .3) answered please.
I NEED THE R CODE THAT WAS USED IN 5.1
Here is the data set:
Question I need answered using R
please use R and just include the
code::
Thank You
You will be asked to explore the determinants of income inequality—which is the dependent variable. The variable name is gini. This variable ranges between 0 and 1, with a 0 indicating perfect equality, where there is a proportional distribution of income. A Gini coefficient of 1 indicates perfect inequality, where one household has all the income.
You can pick three independent variables which you think have an influence on income in- equality. The variables available for selection are as follows: (1) unemp: numerical, Bureau of Labor Statistics’ unemployment rate estimates—the number of unem- ployed as the % of labor force. (2) femlegis: % of female legislators in statehouse, data are from the National Conference of State Legislatures (NCSL). (3) college: State-level population education attainment, measured as the proportion of state population who earned a college degree. (4) demlegis: % Democratic legislators in state legislatures, data are from NCSL. (5) demgov: Dummy variable coding Democratic governor as 1 and 0 otherwise. (6) minimumwage: States' statue minimum wage law, measure as hourly rate (dollar).
inequality state stcode year gini unemp college femlegis demgov demlegis minimumwage Alabama 1 2016 0.485 5.9 0.235 14.3 . 0 22.86 7.25 Alaska 2 2016 0.408 6.9 0.28 30 0 30 9.84 Arizona 4 2016 0.471 5.4 0.275 35.6 0 43.33 10.5 Arkansas 5 2016 0.472 3.9 0.211 19.3 0 31.43 8.5 California 6 2016 0.49 5.5 0.314 25 1 62.5 11 Colorado 8 2016 0.459 3.3 0.381 42 1 48.57 10.2 Connecticut 9 2016 0.495 5.1 0.376 27.8 1 55.56 10.1 Delaware 10 2016 0.452 4.5 0.3 24.2 1 57.14 8.25 Florida 12 2016 0.485 4.8 0.273 25 0 35 8.25 Georgia 13 2016 0.481 5.4 0.288 24.6 0 30.36 7.25 Hawaii 15 2016 0.442 2.9 0.308 28.9 1 96 10.1 Idaho 16 2016 0.45 3.8 0.259 27.6 0 20 7.25 Illinois 17 2016 0.481 5.8 0.323 32.2 0 66.1 8.25 Indiana 18 2016 0.453 4.4 0.241 20.7 0 20 7.25 lowa 19 2016 0.445 3.6 0.267 22.7 0 52 7.25 Kansas 20 2016 0.455 4 0.31 24.2 0 20 7.25 Kentucky 21 2016 0.481 5.1 0.223 15.9 0 28.95 7.25 Louisiana 22 2016 0.499 6 0.225 15.3 1 35.9 7.25 Maine 23 2016 0.452 3.8 0.29 29.6 0 42.86 10 Maryland 24 2016 0.45 4.4 0.379 31.4 0 70.21 10.1 Massachusetts 25 2016 0.479 3.9 0.405 25 0 82.5 11 Michigan 26 2016 0.47 5 0.269 20.3 0 28.95 9.25 Minnesota 27 2016 0.45 3.9 0.337 33.3 1 58.21 9.65 Mississippi 28 2016 0.483 5.8 0.207 13.2 38.46 7.25 Missouri 29 2016 0.465 4.6 0.271 24.9 1 26.47 7.85 Montana 30 2016 0.467 4.1 0.249 31.3 1 42 8.3 Nebraska 31 2016 0.448 3.1 0.293 22.4 o 0 9 Nevada 32 2016 0.458 5.7 0.23 30.2 0 47.62 8.25 New Hampshire 33 2016 0.43 2.9 0.349 28.5 1 41.67 7.25 New Jersey 34 2016 0.481 5 0.368 30 0 60 8.6 New Mexico 35 2016 0.477 6.7 0.263 25.9 0 59.52 7.5 New York 36 2016 0.513 4.8 0.342 25.4 1 49.21 10.4 North Carolina 37 2016 0.478 5.1 0.284 22.9 0 32 7.25 North Dakota 38 2016 0.453 3.1 0.277 19.1 o od 31.91 7.25 Ohio 39 2016 0.468 5 0.261 25.8 0 30.3 8.3 Oklahoma 40 2016 0.465 4.8 0.241 14.1 0 18.75 7.25 Oregon 41 2016 0.458 4.8 0.308 31.1 1 60 10.75 Pennsylvania 42 2016 0.469 5.4 0.286 18.6 1 38 7.25 Rhode Island 44 2016 0.478 5.2 0.319 27.4 1 84.21 10.1 South Carolina 45 2016 0.474 5 0.258 14.7 0 36.96 7.25 South Dakota 46 2016 0.45 3 0.27 21 0 22.86 8.65 Tennessee 47 2016 0.479 4.7 0.295 16.7 0 15.15 7.25 Texas 48 2016 0.48 4.6 0.276 19.9 0 35.48 7.25 Utah 49 2016 0.426 3.4 0.311 15.4 0 17.24 7.25 Vermont 50 2016 0.454 3.2 0.36 41.1 1 70 10.5 Virginia 51 2016 0.471 4.1 0.363 19.3 1 47.5 7.25 Washington 53 2016 0.459 5.3 0.329 34 1 48.98 11.5 West Virginia 54 2016 0.471 6.1 0.192 14.9 47.06 8.75 Wisconsin 55 2016 0.45 4 0.278 25 ooo 42.42 7.25 Wyoming 56 2016 0.436 5 0.257 13.3 13.33 7.25
5.Regression analysis. 5.1 Estimate a multiple regression model and present regression results in a table. (5 points) 5.2 Are the regression coefficients significant or not? Why? (10 points) 5.3 Interpret the regression coefficient substantively. (10 points)
question 5(.1, .2, and .3) answered please.
I NEED THE R CODE THAT WAS USED IN 5.1
- Using A Data Set And This Data Dictionary I Need Question 5 1 2 And 3 Answered Please I Need The R Code That Was 1 (41.62 KiB) Viewed 90 times
- Using A Data Set And This Data Dictionary I Need Question 5 1 2 And 3 Answered Please I Need The R Code That Was 2 (251.16 KiB) Viewed 90 times
please use R and just include the
code::
- Using A Data Set And This Data Dictionary I Need Question 5 1 2 And 3 Answered Please I Need The R Code That Was 3 (38.01 KiB) Viewed 90 times
You will be asked to explore the determinants of income inequality—which is the dependent variable. The variable name is gini. This variable ranges between 0 and 1, with a 0 indicating perfect equality, where there is a proportional distribution of income. A Gini coefficient of 1 indicates perfect inequality, where one household has all the income.
You can pick three independent variables which you think have an influence on income in- equality. The variables available for selection are as follows: (1) unemp: numerical, Bureau of Labor Statistics’ unemployment rate estimates—the number of unem- ployed as the % of labor force. (2) femlegis: % of female legislators in statehouse, data are from the National Conference of State Legislatures (NCSL). (3) college: State-level population education attainment, measured as the proportion of state population who earned a college degree. (4) demlegis: % Democratic legislators in state legislatures, data are from NCSL. (5) demgov: Dummy variable coding Democratic governor as 1 and 0 otherwise. (6) minimumwage: States' statue minimum wage law, measure as hourly rate (dollar).
inequality state stcode year gini unemp college femlegis demgov demlegis minimumwage Alabama 1 2016 0.485 5.9 0.235 14.3 . 0 22.86 7.25 Alaska 2 2016 0.408 6.9 0.28 30 0 30 9.84 Arizona 4 2016 0.471 5.4 0.275 35.6 0 43.33 10.5 Arkansas 5 2016 0.472 3.9 0.211 19.3 0 31.43 8.5 California 6 2016 0.49 5.5 0.314 25 1 62.5 11 Colorado 8 2016 0.459 3.3 0.381 42 1 48.57 10.2 Connecticut 9 2016 0.495 5.1 0.376 27.8 1 55.56 10.1 Delaware 10 2016 0.452 4.5 0.3 24.2 1 57.14 8.25 Florida 12 2016 0.485 4.8 0.273 25 0 35 8.25 Georgia 13 2016 0.481 5.4 0.288 24.6 0 30.36 7.25 Hawaii 15 2016 0.442 2.9 0.308 28.9 1 96 10.1 Idaho 16 2016 0.45 3.8 0.259 27.6 0 20 7.25 Illinois 17 2016 0.481 5.8 0.323 32.2 0 66.1 8.25 Indiana 18 2016 0.453 4.4 0.241 20.7 0 20 7.25 lowa 19 2016 0.445 3.6 0.267 22.7 0 52 7.25 Kansas 20 2016 0.455 4 0.31 24.2 0 20 7.25 Kentucky 21 2016 0.481 5.1 0.223 15.9 0 28.95 7.25 Louisiana 22 2016 0.499 6 0.225 15.3 1 35.9 7.25 Maine 23 2016 0.452 3.8 0.29 29.6 0 42.86 10 Maryland 24 2016 0.45 4.4 0.379 31.4 0 70.21 10.1 Massachusetts 25 2016 0.479 3.9 0.405 25 0 82.5 11 Michigan 26 2016 0.47 5 0.269 20.3 0 28.95 9.25 Minnesota 27 2016 0.45 3.9 0.337 33.3 1 58.21 9.65 Mississippi 28 2016 0.483 5.8 0.207 13.2 38.46 7.25 Missouri 29 2016 0.465 4.6 0.271 24.9 1 26.47 7.85 Montana 30 2016 0.467 4.1 0.249 31.3 1 42 8.3 Nebraska 31 2016 0.448 3.1 0.293 22.4 o 0 9 Nevada 32 2016 0.458 5.7 0.23 30.2 0 47.62 8.25 New Hampshire 33 2016 0.43 2.9 0.349 28.5 1 41.67 7.25 New Jersey 34 2016 0.481 5 0.368 30 0 60 8.6 New Mexico 35 2016 0.477 6.7 0.263 25.9 0 59.52 7.5 New York 36 2016 0.513 4.8 0.342 25.4 1 49.21 10.4 North Carolina 37 2016 0.478 5.1 0.284 22.9 0 32 7.25 North Dakota 38 2016 0.453 3.1 0.277 19.1 o od 31.91 7.25 Ohio 39 2016 0.468 5 0.261 25.8 0 30.3 8.3 Oklahoma 40 2016 0.465 4.8 0.241 14.1 0 18.75 7.25 Oregon 41 2016 0.458 4.8 0.308 31.1 1 60 10.75 Pennsylvania 42 2016 0.469 5.4 0.286 18.6 1 38 7.25 Rhode Island 44 2016 0.478 5.2 0.319 27.4 1 84.21 10.1 South Carolina 45 2016 0.474 5 0.258 14.7 0 36.96 7.25 South Dakota 46 2016 0.45 3 0.27 21 0 22.86 8.65 Tennessee 47 2016 0.479 4.7 0.295 16.7 0 15.15 7.25 Texas 48 2016 0.48 4.6 0.276 19.9 0 35.48 7.25 Utah 49 2016 0.426 3.4 0.311 15.4 0 17.24 7.25 Vermont 50 2016 0.454 3.2 0.36 41.1 1 70 10.5 Virginia 51 2016 0.471 4.1 0.363 19.3 1 47.5 7.25 Washington 53 2016 0.459 5.3 0.329 34 1 48.98 11.5 West Virginia 54 2016 0.471 6.1 0.192 14.9 47.06 8.75 Wisconsin 55 2016 0.45 4 0.278 25 ooo 42.42 7.25 Wyoming 56 2016 0.436 5 0.257 13.3 13.33 7.25
5.Regression analysis. 5.1 Estimate a multiple regression model and present regression results in a table. (5 points) 5.2 Are the regression coefficients significant or not? Why? (10 points) 5.3 Interpret the regression coefficient substantively. (10 points)