You're a social researcher interested in how a person's education level is related to their Father's education level. The following data were obtained from a sample of 4 respondents: X - Father's Education Level Y - Respondent's Education Level (in years) (in years) 1 20 18 2 12 16 3 10 13 4 14 10 Mean 14.00 14.25 Sx = 4.32 Sy = 3.5 Respondent ID b = 0.43 Syx = 8 I have computed most of the statistics to help you along here. You will not need to write-out a full computation table for this problem. Show moderate work when necessary, we don't need to see your computation tables, but final equations will help. 1. 2. 3. 4. 3 Points. Calculate the y-intercept (a) if the slope is b= 0.43 and report the linear regression prediction equation. Round to the nearest hundredth place (i.e., the second decimal place). 3 Points. Using that prediction equation, calculate the predicted number of years of school for a respondent who's Father completed 16 years of schooling. Round to the nearest hundredth, the second decimal place. 4 Points. Using the appropriate measures reported above, compute and report the statistic that describes the strength and direction of the relationship between Father's education level and the respondent's education level. Round to the nearest hundredth place (i.e., the second decimal place). In 1-2 sentences, describe what this figure indicates. 5 Points. Compute and report the statistic that describes the proportion of the variation in respondent's education level explained by Father's education level. Round to the nearest hundredth place (i.e., the second decimal place). In 1-2 sentences, make an assessment of what this number means and how well the regression line fits the data. You're a social researcher interested in how a person's education level is related to their Father's education level. The following data were obtained from a sample of 4 respondents: Respondent ID X Father's Y Respondent's Education Level Education Level (in years) (in years) 1 20 18 2 12 16 3 10 13 4 14 10 Mean 14.00 14.25 Sx = 4.32 Sy = 3.5 b = 0.43 Syx = 8 I have computed most of the statistics to help you along here. You will not need to write-out a full computation table for this problem. Show moderate work when necessary, we don't need to see your computation tables, but final equations will help. 1. 3 Points. . Intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 2. 3 Points. . y = 8.23 + .43*x When, x = 16; Predicted y = =14.25-0.43*16 = 7.37 3. 4 Points. . Correlation coefficient, r = 0.53 There is a moderate positive linear relationship between Father's Education Level and Respondent's Education Level. That is as the value of father's Education Level increases, the value of Respondent's Education Level also increases 4. 5 Points. .. Coefficient of determination, R^2 = r^2 =.52904^2 0.28 This implies only 27.9% variation in Respondent's Education Level is explained by fathers Education Level Responden t ID 1 2 3 4 Mean b = 0.43 Syx = 8 X - Father's Education Level (in years) 20 12 10 14 14 Y - Respondent's Education Level (in years) 18 16 13 10 14.25 Sx = 4.32 Sy = 3.5 a) intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 b) y = 8.23 + .43*x when, x = 16 predicted y = =14.25-0.43*16 7.37 c) correlation coefficient, r = r= 0.52904 there is a moderate positive linear relationship between Father's E Respondent's Education Level. That is as the value of father's Educ increases, the value of Respondent's Education Level also increase d) coefficient of determination, R^2 = r^2 =.52904^2 0.279883 this implies only 27.9% variation in Respondent's Education Level fathers Education Level ship between Father's Education Level and e value of father's Education Level ation Level also increases dent's Education Level is explained by You're a social researcher interested in how a person's education level is related to their Father's education level. The following data were obtained from a sample of 4 respondents: Respondent ID X Father's Y Respondent's Education Level Education Level (in years) (in years) 1 20 18 2 12 16 3 10 13 4 14 10 Mean 14.00 14.25 Sx = 4.32 Sy = 3.5 b = 0.43 Syx = 8 I have computed most of the statistics to help you along here. You will not need to write-out a full computation table for this problem. Show moderate work when necessary, we don't need to see your computation tables, but final equations will help. 1. 3 Points. . Intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 2. 3 Points. . y = 8.23 + .43*x When, x = 16; Predicted y = =14.25-0.43*16 = 7.37 3. 4 Points. . Correlation coefficient, r = 0.53 There is a moderate positive linear relationship between Father's Education Level and Respondent's Education Level. That is as the value of father's Education Level increases, the value of Respondent's Education Level also increases 4. 5 Points. .. Coefficient of determination, R^2 = r^2 =.52904^2 0.28 This implies only 27.9% variation in Respondent's Education Level is explained by fathers Education Level Responden t ID 1 2 3 4 Mean b = 0.43 Syx = 8 X - Father's Education Level (in years) 20 12 10 14 14 Y - Respondent's Education Level (in years) 18 16 13 10 14.25 Sx = 4.32 Sy = 3.5 a) intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 b) y = 8.23 + .43*x when, x = 16 predicted y = =14.25-0.43*16 7.37 c) correlation coefficient, r = r= 0.52904 there is a moderate positive linear relationship between Father's E Respondent's Education Level. That is as the value of father's Educ increases, the value of Respondent's Education Level also increase d) coefficient of determination, R^2 = r^2 =.52904^2 0.279883 this implies only 27.9% variation in Respondent's Education Level fathers Education Level ship between Father's Education Level and e value of father's Education Level ation Level also increases dent's Education Level is explained by You're a social researcher interested in how a person's education level is related to their Father's education level. The following data were obtained from a sample of 4 respondents: Respondent ID X Father's Y Respondent's Education Level Education Level (in years) (in years) 1 20 18 2 12 16 3 10 13 4 14 10 Mean 14.00 14.25 Sx = 4.32 Sy = 3.5 b = 0.43 Syx = 8 I have computed most of the statistics to help you along here. You will not need to write-out a full computation table for this problem. Show moderate work when necessary, we don't need to see your computation tables, but final equations will help. 1. 3 Points. . Intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 2. 3 Points. . y = 8.23 + .43*x When, x = 16; Predicted y = =14.25-0.43*16 = 7.37 3. 4 Points. . Correlation coefficient, r = 0.53 There is a moderate positive linear relationship between Father's Education Level and Respondent's Education Level. That is as the value of father's Education Level increases, the value of Respondent's Education Level also increases 4. 5 Points. .. Coefficient of determination, R^2 = r^2 =.52904^2 0.28 This implies only 27.9% variation in Respondent's Education Level is explained by fathers Education Level Responden t ID 1 2 3 4 Mean b = 0.43 Syx = 8 X - Father's Education Level (in years) 20 12 10 14 14 Y - Respondent's Education Level (in years) 18 16 13 10 14.25 Sx = 4.32 Sy = 3.5 a) intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 b) y = 8.23 + .43*x when, x = 16 predicted y = =14.25-0.43*16 7.37 c) correlation coefficient, r = r= 0.52904 there is a moderate positive linear relationship between Father's E Respondent's Education Level. That is as the value of father's Educ increases, the value of Respondent's Education Level also increase d) coefficient of determination, R^2 = r^2 =.52904^2 0.279883 this implies only 27.9% variation in Respondent's Education Level fathers Education Level ship between Father's Education Level and e value of father's Education Level ation Level also increases dent's Education Level is explained by You're a social researcher interested in how a person's education level is related to their Father's education level. The following data were obtained from a sample of 4 respondents: Respondent ID X Father's Y Respondent's Education Level Education Level (in years) (in years) 1 20 18 2 12 16 3 10 13 4 14 10 Mean 14.00 14.25 Sx = 4.32 Sy = 3.5 b = 0.43 Syx = 8 I have computed most of the statistics to help you along here. You will not need to write-out a full computation table for this problem. Show moderate work when necessary, we don't need to see your computation tables, but final equations will help. 1. 3 Points. . Intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 2. 3 Points. . y = 8.23 + .43*x When, x = 16; Predicted y = =14.25-0.43*16 = 7.37 3. 4 Points. . Correlation coefficient, r = 0.53 There is a moderate positive linear relationship between Father's Education Level and Respondent's Education Level. That is as the value of father's Education Level increases, the value of Respondent's Education Level also increases 4. 5 Points. .. Coefficient of determination, R^2 = r^2 =.52904^2 0.28 This implies only 27.9% variation in Respondent's Education Level is explained by fathers Education Level Responden t ID 1 2 3 4 Mean b = 0.43 Syx = 8 X - Father's Education Level (in years) 20 12 10 14 14 Y - Respondent's Education Level (in years) 18 16 13 10 14.25 Sx = 4.32 Sy = 3.5 a) intercept, a = ybar - b*xbar =14.25-0.43*14 8.23 b) y = 8.23 + .43*x when, x = 16 predicted y = =14.25-0.43*16 7.37 c) correlation coefficient, r = r= 0.52904 there is a moderate positive linear relationship between Father's E Respondent's Education Level. That is as the value of father's Educ increases, the value of Respondent's Education Level also increase d) coefficient of determination, R^2 = r^2 =.52904^2 0.279883 this implies only 27.9% variation in Respondent's Education Level fathers Education Level ship between Father's Education Level and e value of father's Education Level ation Level also increases dent's Education Level is explained by