I need help finding the age p value Using the accompanying Home Market Value data, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. State the model and explain R?, Significance F, and p-values, with an alpha of 0.05.E Click the icon to view the Home Market Value dataState the hypotheses for the multiple linear regression test.Họ: B1 = B2 = • •• = Pk = 0H: at least one B; is not 0State the model for predicting MarketValue as a function of Age and Size, where Age is the age of the house, and Size is the size of the house in square feet.MarketValue = 44843.25 + (- 417.818) Age + (35.130) Size(Type integers or decimals rounded to three decimal places as needed.)The value of R2, 0.452 , indicates that 45.2 % of the variation in the dependent variable(Type integers or decimals rounded to three decimal places as needed.)is explained by these independent variables.The Significance F is 0(Type an integer or decimal rounded to three decimal places as needed.)The Significance F isless thanthe chosen level of significance. Therefore,rejectthe null hypothesis. The results suggest that at least one slope is not 0.The Age p-value is(Type an integer or decimal rounded to three decimal places as needed.) varlvar2var3House AgeSquare Feet Market Value33189791239321846101567331815966223318438998033189397869312069110608301702876233117749621634175788650321689853783118521019413115751008663016628346332237811166034248911240834173690292342163119169301604987063317048665134173287294271510801562614617773329159785082281656888482915118425328141277624271504885612816289028729142578669271506890072714459034527151686358261541729522715128774927163289622271664827232817948676026146184654271548962502915668841926166498263281623126230

Consider the provided data which is used to predict the Home Market value based on the other variables age and house size. The step by step procedure to fit the multiple regression model using Excel is given below: 1. Enter the data into the Excel worksheet. 2. Go to Data then choose the “Data Analysis” tab 3. The window will pop up along with the various statistical tests 4. Scroll down to find the regression option and click ok. 5. The window will pop up then select the variable “Market value" in the Input Y range and the variable “Age” and "Size" in the Input X range. 6. Click Ok. The summary output is given below: 1. From the above output, the regression equation that is used to predict the Market value is, Market Value = 44843.25-417.818×Age+35.130×Size 2. From the Excel output, the value of the coefficient of determination is 0.452. This means that the value of R2 indicates that 45.2% of the variation in the dependent variable Market value is explained by the independent variables "Age" and "Size". 3. From the Excel output, the value of Significance F is 0 which is less than the significance level of 0.05. Hence, the null hypothesis gets rejected. Therefore, there is a significant relationship between the variable Market Value and the independent variables. 4. From the regression coefficient table above, the test statistics for the independent variable age is -0.626 and the P-value for the independent variable age is 0.535 which is greater than the significance level of 0.05. Hence, we can conclude that there is not a significant effect of age on the variable Market value. This means that the variable "Age" does not contribute significantly to the regression model. Similarly, the test statistic for the independent variable Size is 4.542 and the P-value is 0.00 which is less than the significance level of 0.05. Hence, we can conclude that there is a significant effect of size on the variable Market value. This means that the variable "size" contributes significantly to the regression model.