can someone please explain these step by step and give any tips to help better understand (chapter 15 bnad 277)

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A real estate analyst believes that the three main factors that inuence an df SS MS F apartment's rent in a college town are the mnnber of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she _ collects data on the rent (y, in $), the number of bedrooms (x1), the number of Regressnon 3 5,694 1,393 51 bathrooms (x2), and its square footage (x3). She estimates the following model: Rent = [30 + [91 Bedroom + [92 Bath + 3Sqft + s. The following table shows a portion of the regression results. Resndual 36 L343 37 Total 39 7,037 What is conclusion can be reached regarding Joint Signicance of entire model at 5% signicance? Can reject Ho b/c F-test > F-crit, thus can df SS MS conclude joint signicance. All variables stay in the model. Regression 3 5,694 1,898 Residual 36 1,343 37 Total 39 7,037 A real estate analyst believes that the three main factors that inuence an Coefcients Standard tstat apartment's rent in a college town are the number of bedrooms, the number Error of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in 55), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (x3). She estimates the following Intercept 300 84-0 357 model: Rent = 0 + l Bedroom + [2'2 Bath + 1335'qu + e. The following table shows a pornon of the regresslon results. Bedroom 2 2 6 60.3 3.75 When testing whether Bath is signicant at the 5% signicance level, what Bath 89 55'9 159 can be concluded? Cannot reject H o:2 = 0 as It-testl