PART Two: SIMPLE LINEAR REGRESSION Suppose a researcher is interested in studying whether a mother's systolic blood pressure (SBP) is predictive of her rst- born child's SBP in an effort to determine if hypertension is a genetic phenomenon. This issue was examined in 20 families by measuring SBP (in mmHg) of the mother and the rst-born child in each family. We analyze the data using SAS's REG procedure and observe the results shown in Table 2 (see page 7). Based on those ndings, answer the following questions. 1) Identify the dependent variable and the independent or explanatory variable(s) in this study. Also, state the Null and Alternative hypotheses. 2) Report the test statistic and P-value that should be used to test the Omnibus (or Overall) Null hypothesis. What is your conclusion about the Orrmibus Null hypothesis? 3) Report and interpret the parameter estimate for mother's SBP from the SAS output. 4) Using the regression equation (Y = a + bX), calculate the predicted a rst-born child's SBP when the mother's SBP is 120 mmHg. D 5) What is your interpretation of the R-square value? 6) Interpret these ndings (3 -4 sentences max). Your answer should (1) restate the ndings; (2) note the generalizability of these results; and (3) state what these ndings mean from clinical perspective. Table 2: Output for Part Two Simple Linear Regression The REG Procedure Model: MODEL 1 Dependent Variable: Child_SBP Number of Observations Read 20 Number of Observations Used 20 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 1 1611 85732 1611.85732 9.09 0.0074 Error 18 3193. 14268 177.39682 Corrected Total 19 4805.00000 Root MSE 13.31904 R-Square 0.3355 Dependent Mean 101.50000 Adj R-Sq 0.2985 Coeff Var 13.12221 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > It) Intercept 43.17036 19.57864 2.20 0.0407 Mom SBP 1 0.44526 0. 14772 3.01 0.0074