Kindly help me solve d) e) f) g). Answers for a) b) c) are in the picture attached I am aware as per policy you would solve only three, however only g) then would be remaining. So, I insist if you could help me solve all the four. Thank you! ### Study on Corrosion Impact on Reinforced Concrete Structures#### IntroductionCorrosion of steel reinforcing bars is a critical issue affecting the durability of reinforced concrete structures. Carbonation of concrete, resulting from a chemical reaction that lowers the pH to corrosive levels, is a key factor in this degradation process. Below, we present a data table that examines the relationship between concrete strength (in MPa) and carbonation depth (in mm) from a specific building sample.#### Data Table| Carbonation Depth (x) [mm] | Strength (y) [MPa] ||----------------------------|--------------------|| 8.0 | 22.8 || 15.0 | 27.2 || 16.5 | 23.7 || 20.0 | 17.1 || 20.0 | 21.5 || 27.5 | 18.6 || 30.0 | 16.1 || 30.0 | 23.4 || 35.0 | 13.4 || 38.0 | 19.5 || 40.0 | 12.4 || 45.0 | 13.2 || 50.0 | 11.4 || 50.0 | 10.3 || 55.0 | 14.1 || 55.0 | 9.7 || 59.0 | 12.0 || 65.0 | 6.8 |#### Analysis**a) Linear Regression Model**Fit a linear regression model to the data provided. Estimate the expected value of the concrete strength when the carbonation depth is 25.0 mm.**b) Significance of Regression**Examine the significance of the regression using the t-test with a significance level of \(\alpha = 0.01\). Report the corresponding P-value.**c) Analysis of Variance (ANOVA)**Use the ANOVA approach to evaluate the significance of the regression. Find and report the P-value. Compare the results with those from part (b).**d) Validation of Model**Test one additional sample with a carbonation depth of 25.0 ### Linear Regression Analysis Summary#### Summary Output**Regression Statistics:**- Multiple R: 0.874973816- R Square: 0.76559179- Adjusted R Square: 0.750927877- Standard Error: 2.864026013- Observations: 18**ANOVA Table:**| Source | df | SS | MS | F | Significance F ||--------------|----|--------------|---------------|-------------|------------------|| Regression | 1 | 428.6154577 | 428.6154577 | 52.25332287 | 2.01347E-06 || Residual | 16 | 131.24232 | 8.202645003 | | || Total | 17 | 559.8577778 | | | |**Coefficients Table:**| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% ||--------------|----------------|--------------|---------------|------------------|------------------|------------------|------------------|| Intercept | 27.18293605 | 1.653148135 | 16.46105716 | 1.88128E-11 | 23.68223439 | 30.68363772 | 23.68223439 | 30.68363772 || x | -0.297561228 | 0.041164172 | -7.228645991 | 2.01347E-06 | -0.384825374 | -0.210297081 | -0.384825374 | -0.210297081 |#### Analysis:**(a)** The fitted linear regression model is: \(\hat{y} = 27.18 - 0.2976x\)For a carbonation depth of 25.0 mm, substitute \(x = 25\) in the above equation:\[ \hat{y} = 27.18 - 0.2976 \times (25) = 19.74 \text{ MPa}

Name: Kindly help me solve d) e) f) g). Answers for a) b) c) are in the pict
Uploaded: 2024-03-20T06:38:44.000Z
Channel: Bartleby
Description: Kindly help me solve d) e) f) g). Answers for a) b) c) are in the picture attached I am aware as per policy you would solve only three, however only g) then would be remaining. So, I insist if you could help me solve all the four. Thank you! ### Stud