The Malaysian bakery industry in Malaysia is a fast-moving industry with an estimated total of several thousands of baked goods suppliers in the country. The Malaysian market has seen a positive growth of baked goods due to the products being consumed at any meal serve on the plate. It's versatile and accepted by the majority of Malaysian population. At one time, during Movement Control Order (MCO), we had an experienced when it has become one of a necessity. A study has been designed by one of well-known industrial player in confectionary to assess the moisture content and sweetness of a pastry product will affect a tester's rating of the product. In the studied, the eight possible combinations of four moisture levels and two sweetness levels were studied. Two pastries are prepared and rated for each of the eight combinations, so the total sample size is sixteenth. The dependent variable is the rating of the pastry. The two independents variable are moisture and sweetness. The values and the sample sizes of both independents' variables were designed so that it was not correlated. The researcher found that there is a linear relationship between rating and moisture and there is also a sweetness difference. The results are given in the next page. You are required to write a report on the following matters: a) Conduct model assessment. Use a = 0.05 for any relevant test exercise(s). b) Additionally, discuss the following arising issues: i. the reason for sample coefficient that multiplies the independent variables in both simple and multiple regression appear to be the same; ii. the R2 for the multiple regression, is the sum of the R2 values for the simple regressions, and iii. the variable of Sweetness has proven to be not statistically significant in the simple regression but it is significant in the multiple regression. Justified. SUMMARY OUTPUT: RATING VS MOISTURE Regression Statistics R Square Adjusted R Standard Error Observation 0.7964 0.7818 5.3489 16 ANOVA F Significance F 54.75 0.0000 Regression Residual Total df 1 14 15 SS 1566.45 400.55 1967.00 MS 1566.45 28.61 Intercept Moisture Coefficients Standard Error 50.77 4.39 4.425 0.598 t Star 11.55 7.4 P-value 0.0000 0.0000 SUMMARY OUTPUT: RATING VS SWEETNESS Regression Statistics R Square Adjusted R Standard Error Observation 0.1575 0.0954 10.8915 16 ANOVA F Significance F 2.58 0.1300 Regression Residual Total df 1 14 15 SS 306.3 1660.7 1967.0 MS 306.3 118.6 Intercept Sweetness Coefficients Standard Error 68.63 8.61 4.38 2.72 Stat 7.97 1.61 P-value 0.0000 0.1300 SUMMARY OUTPUT: RATING VS MOISTURE, SWEETNESS Regression Statistics R Square Adjusted R Standard Error Observation 0.9521 0.9474 2.6933 16 ANOVA F Significance F 129.15 0.0000 Regression Residual Total df 2 13 15 SS 1872.70 94.30 1967.00 MS 936.35 7.25 Intercept Moisture Sweetness Coefficients Standard Error 37.65 3.000 4.425 0.301 4.375 0.673 t Stat 12.57 14.7 6.5 P-value 0.0000 0.0000 0.0000