Question

Question 3 (5 points) Question 1(C): You have performed a simple linear regression model to understand the effect of Number of Bedrooms on House Price House Price is in Thousand S and Number of Bedrooms is in number of bedrooms Coefficient t-statistic p-value Intercept 28.77 6.52 <0.000 Number of Bedrooms 13.27 9.18 <0.000 Which of the below statement is true. Select one option from below: O p-value<0.001 implies that we cannot reject the null hypothesis. O p-value<0.001 implies that the effect of number of bedrooms on house price cannot be determined. O p-value<0.001 implies that the effect of number of bedrooms on house price is not significant O p-value<0.001 implies that the effect of number of bedrooms on house price is significant

Answer 1

Q3) Since the pvalue is small, the slope is significant. Thus, the effect of number of bedrooms on house price is significant.

Ans: Option 4

Q4) R-squared (R2) is a statistical measure that represents the proportion of the variance for a dependent variable(price of house) that's explained by an independent variable(number of bedrooms) or variables in a regression model.

Ans: Option 4