1. According to the correlation analysis output, what is the correlation between percent of smokers and...
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1. According to the correlation analysis output, what is the correlation between percent of smokers and percent of unhealthy residents? a. 0.65 b. -0.87 c. 0.48 d. 0.72 2. Interpret the coefficient for smoking under the simple linear regression analysis? a. An additional smoke per day is associated with an increase in the status of unhealthy people by 0.53% b. Compared to those that do not smoke, states that have smokers are 0.53% more likely to be unhealthy c. An additional increase in the percent of self-reported smokers increases the percent of self-reported unhealthy individuals by 0.53% d. Smoking status is associated with 0.53% of unhealthy states 3. At the 95% level, the coefficient for smoking statistically significant in the simple linear regression and/or the multiple regression? a. Simple regression: yes; Multiple regression: yes b. Simple regression: yes; Multiple regression: no c. Simple regression: no; Multiple regression: yes d. Simple regression: no; Multiple regression: no 4. Using the muitiple regression model, how much of a state can we expect to self-report that they are unhealthy if: 17% are smokers, 56% have a high school diploma, 82% are obese, and 34% have insurance. a. 38.76 b. 77.45 c. 52.34 d. 45.92 5. Assuming a 95% level, what does the analysis of variance Pr > F statistics tell us about the coefficients of the multiple regression analysis? a. That all coefficients are statistically significant b. That none of the coefficients are statistically significant c. That the independent variables do not explain any of the variation in the dependent variable d. That at least one coefficient is not statistically significant Correlation Analysis: Health State Dataset Variables Simple Linear Regression: Not Healthy - Smoking The CORR Procedure The REG Procedure Model: MODEL1 S Variables: Noliealthy Obesty HighSchool Smoking Insurance Dependent Variable: NotHealthy NotiHealthy Number of Observations Read 51 Simpie Statistice Number of Observations Used 51 Variable Mean Std Dev Sum Minimum Maximum Label NotHealthy 51 15.10020 3.27080 774.70000 10.90000 23.10000 NotHealthy Obesity 51 23.72041 2.83708 1210 17.00000 30.10000 Obesity Analysis of Variance Sum of Squares 1 126.00425 126.00425 HighSchool 51 85.84002 3.81030 4368 78.50000 01.30000 HighSchool Mean Source DF Square F Value Pr>F Smoking 61 23.300u7 2.97016 1192 13.60000 30.70000 Smoking Model 15.10 0.0003 Insurance 51 1732157 484187 883.40000 B.40000 30.90000 Insurance Error 49 408.90085 8.34492 Corrected Total 50 534.90510 Pearson Correlation Coefficients, N= 51 Prob > Irl under HO: Rho-0 NotHealthy Obesity HighSchool Smoking Insurance Root MSE 2.88876 R-Square 0.2356 NotHealthy NotHealthy 1.00000 0.05854 <.0001 -0.87821 0.48535 0.71241 Dependent Mean 15.19020 Adj R-Sq 0.2200 <.0001 0.0003 <0001 Coeff Var 19.01724 Obesity Obesity 1.00000 0.54616 <0001 0.52477 <0001 0.31512 0.0243 0.65854 <0001 HighSchool HighSchool O.87821 -0.54516 <.0001 1.00000 -0.37452 0.0068 -0 56554 Parameter Estimates <0001 <0001 Smoking Smoking 0.48536 0.0003 0.52477 <0001 0.37452 0.0068 Parameter Standard Estimate 1.00000 021893 Variable Error t Value Pr> It| Label DF 0.1227 Intercept Intercept 2.70130 3.23933 0.83 0.4084 Insurance Insurance 0.31512 0.0243 0.71241 -0.56554 0.21893 1.00000 <0001 <.0001 0.1227 Smoking Smoking 1 0.53447 0.13755 3.89 0.0003 Multiple Regression: Not Healthy - Smoking, High School, Obesity, Insurance The REG Procedure Model: MODEL1 Dependent Variable: NotHealthy NotHealthy Number of Observations Read 51 Number of Observations Used 51 Analysis of Variance Sum of Squares Mean Source DF Square F Value Pr >F Model 4 477.18081 119.29520 95.07 <0001 Error 46 57.72429 1.25488 Corrected Total 50 534.90510 Root MSE 1.12021 R-Square 0.8921 Dependent Mean 15.19020 Adj R-Sq 0.8827 Coeff Var 7.37457 Parameter Estimates Parameter Standard Estimate Error tValue Pr> 95% Confidence Limits Variable Label DF Intercept Intercept 1 45.91250 6.51424 7.05 <.0001 32.80002 59.02499 Smoking Smoking 0.11293 0.06315 1.79 0.0803 -0.01417 0.24004 HighSchool HighSchool 1 -0.49818 0.06057 -8.22 <.0001 -0.62011 -0.37626 Obesity Obesity 0.23738 0.07310 3.25 0.0022 0.09025 0.38452 Insurance Insurance 0.21215 0.03968 5.35 <.0001 0.13229 0.29201 1. According to the correlation analysis output, what is the correlation between percent of smokers and percent of unhealthy residents? a. 0.65 b. -0.87 c. 0.48 d. 0.72 2. Interpret the coefficient for smoking under the simple linear regression analysis? a. An additional smoke per day is associated with an increase in the status of unhealthy people by 0.53% b. Compared to those that do not smoke, states that have smokers are 0.53% more likely to be unhealthy c. An additional increase in the percent of self-reported smokers increases the percent of self-reported unhealthy individuals by 0.53% d. Smoking status is associated with 0.53% of unhealthy states 3. At the 95% level, the coefficient for smoking statistically significant in the simple linear regression and/or the multiple regression? a. Simple regression: yes; Multiple regression: yes b. Simple regression: yes; Multiple regression: no c. Simple regression: no; Multiple regression: yes d. Simple regression: no; Multiple regression: no 4. Using the muitiple regression model, how much of a state can we expect to self-report that they are unhealthy if: 17% are smokers, 56% have a high school diploma, 82% are obese, and 34% have insurance. a. 38.76 b. 77.45 c. 52.34 d. 45.92 5. Assuming a 95% level, what does the analysis of variance Pr > F statistics tell us about the coefficients of the multiple regression analysis? a. That all coefficients are statistically significant b. That none of the coefficients are statistically significant c. That the independent variables do not explain any of the variation in the dependent variable d. That at least one coefficient is not statistically significant Correlation Analysis: Health State Dataset Variables Simple Linear Regression: Not Healthy - Smoking The CORR Procedure The REG Procedure Model: MODEL1 S Variables: Noliealthy Obesty HighSchool Smoking Insurance Dependent Variable: NotHealthy NotiHealthy Number of Observations Read 51 Simpie Statistice Number of Observations Used 51 Variable Mean Std Dev Sum Minimum Maximum Label NotHealthy 51 15.10020 3.27080 774.70000 10.90000 23.10000 NotHealthy Obesity 51 23.72041 2.83708 1210 17.00000 30.10000 Obesity Analysis of Variance Sum of Squares 1 126.00425 126.00425 HighSchool 51 85.84002 3.81030 4368 78.50000 01.30000 HighSchool Mean Source DF Square F Value Pr>F Smoking 61 23.300u7 2.97016 1192 13.60000 30.70000 Smoking Model 15.10 0.0003 Insurance 51 1732157 484187 883.40000 B.40000 30.90000 Insurance Error 49 408.90085 8.34492 Corrected Total 50 534.90510 Pearson Correlation Coefficients, N= 51 Prob > Irl under HO: Rho-0 NotHealthy Obesity HighSchool Smoking Insurance Root MSE 2.88876 R-Square 0.2356 NotHealthy NotHealthy 1.00000 0.05854 <.0001 -0.87821 0.48535 0.71241 Dependent Mean 15.19020 Adj R-Sq 0.2200 <.0001 0.0003 <0001 Coeff Var 19.01724 Obesity Obesity 1.00000 0.54616 <0001 0.52477 <0001 0.31512 0.0243 0.65854 <0001 HighSchool HighSchool O.87821 -0.54516 <.0001 1.00000 -0.37452 0.0068 -0 56554 Parameter Estimates <0001 <0001 Smoking Smoking 0.48536 0.0003 0.52477 <0001 0.37452 0.0068 Parameter Standard Estimate 1.00000 021893 Variable Error t Value Pr> It| Label DF 0.1227 Intercept Intercept 2.70130 3.23933 0.83 0.4084 Insurance Insurance 0.31512 0.0243 0.71241 -0.56554 0.21893 1.00000 <0001 <.0001 0.1227 Smoking Smoking 1 0.53447 0.13755 3.89 0.0003 Multiple Regression: Not Healthy - Smoking, High School, Obesity, Insurance The REG Procedure Model: MODEL1 Dependent Variable: NotHealthy NotHealthy Number of Observations Read 51 Number of Observations Used 51 Analysis of Variance Sum of Squares Mean Source DF Square F Value Pr >F Model 4 477.18081 119.29520 95.07 <0001 Error 46 57.72429 1.25488 Corrected Total 50 534.90510 Root MSE 1.12021 R-Square 0.8921 Dependent Mean 15.19020 Adj R-Sq 0.8827 Coeff Var 7.37457 Parameter Estimates Parameter Standard Estimate Error tValue Pr> 95% Confidence Limits Variable Label DF Intercept Intercept 1 45.91250 6.51424 7.05 <.0001 32.80002 59.02499 Smoking Smoking 0.11293 0.06315 1.79 0.0803 -0.01417 0.24004 HighSchool HighSchool 1 -0.49818 0.06057 -8.22 <.0001 -0.62011 -0.37626 Obesity Obesity 0.23738 0.07310 3.25 0.0022 0.09025 0.38452 Insurance Insurance 0.21215 0.03968 5.35 <.0001 0.13229 0.29201
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