**Data Analysis on Infant Blood Pressure, Age, and Birth Weight****Dataset Overview:**The table below presents data collected on infant blood pressure, age, and birth weight.| i | Birth weight in oz. (x₁) | Age in days (x₂) | Systolic Blood Pressure mmHg (y) ||----|--------------------------|-----------------|----------------------------------|| 1 | 135 | 3 | 89 || 2 | 120 | 4 | 90 || 3 | 100 | 3 | 83 || 4 | 105 | 2 | 77 || 5 | 130 | 4 | 92 || 6 | 125 | 5 | 98 || 7 | 125 | 2 | 82 || 8 | 105 | 3 | 85 || 9 | 120 | 5 | 96 || 10 | 90 | 4 | 95 || 11 | 120 | 2 | 80 || 12 | 95 | 3 | 79 || 13 | 120 | 3 | 86 || 14 | 150 | 4 | 97 || 15 | 160 | 3 | 92 || 16 | 125 | 3 | 88 |**Data Analysis Tasks:**a. **Fit a Predictive Model:** - Develop a model to predict systolic blood pressure (SBP) based on birth weight and age. Use the least-squares method to determine the regression line equation.b. **Interpret Beta Coefficients:** - Explain the meaning of the beta coefficients for birth weight and age in the context of predicting SBP.c. **Significance Testing:** - Determine if birth weight and/or age are significantly associated with SBP at the 0.05 significance level.d. **Confidence Intervals:** - Interpret the 95% confidence intervals for the coefficients of both birth weight and age.**Graphical or Diagram Explanation:**(Not applicable as there

Since you have posted a question with multiple subparts, we will solve first three subparts for you. To get remaining subparts solved, please repost the question and mention the subparts to be solved. Regression equation are used to predict the variable. It determine the relationship between the independent and dependent variable. The number of independent variable can be varies in the regression equation. But the regression line has only one dependent variable. a) Given : Systolic blood pressure based on age and height. Enter the data in excel Click Data - Click Data Analysis Click Input Y and X Click output - Ok Now, Output will be : From the output, The regression equation will be : y^=53.4502+0.1256x1+5.8877x2b) From part (a), The regression equation will be y^=53.4502+0.1256x1+5.8877x2 Slope of weight : As weight in oz increase by then systolic blood pressure increased 0.1256 times Slope of age : As age increased by one day then systolic blood pressure increased 5.8877 timesc) Given : Claim : There is significant association with SBP with weight. Null hypothesis : There is no association with SBP with weight. Alternate hypothesis : There is significant association with SBP with weight. From the output, Test statistic value corresponds to the weight is 3.6575 P value is 0.0029 Level of significance is 0.05 Here, the p value is less than 0.05. Null hypothesis is rejected. i.e. There is significant association with SBP with weight. Claim : There is significant association with SBP with age. Null hypothesis : There is no association with SBP with age. Alternate hypothesis : There is significant association with SBP with age. From the output, Test statistic value corresponds to the age is 8.6558 P value is 0.0000 Level of significance is 0.05 Here, the p value is less than 0.05. Null hypothesis is rejected. i.e. There is significant association with SBP with age.