\begin{tabular}{|c|c|}
\hline $\begin{array}{c}\text { House Price } \\
\text { in } \$ 1000 s \\
(y)\end{array}$ & $\begin{array}{c}\text { Square Feet } \\
(x)\end{array}$ \\
\hline 245 & 1400 \\
\hline 312 & 1600 \\
\hline 279 & 1700 \\
\hline 308 & 1875 \\
\hline 199 & 1100 \\
\hline 219 & 1550 \\
\hline 405 & 2350 \\
\hline 324 & 2450 \\
\hline 319 & 1425 \\
\hline 255 & 1700 \\
\hline
\end{tabular}
Estimated Regression Equation:
house price $=98.25+0.1098$ (sq.ft.)
The slope of this model is 0.1098
Does square footage of the house significantly affect its sales price?
Answer
\(\boxed{\text{Final Answer: Since the p-value is less than the significance level of 0.05, we reject the null hypothesis. Therefore, the square footage of the house significantly affects its sales price.}}\)
Step 1 ：\(H_0: \beta_1 = 0\) (Square footage does not significantly affect the house price)
Step 2 ：\(H_1: \beta_1 \neq 0\) (Square footage significantly affects the house price)
Step 3 ：Significance level: \(\alpha = 0.05\)
Step 4 ：Calculate the standard error of the slope (SE): \(SE = 0.03297\)
Step 5 ：Calculate the t-statistic: \(t = 3.3304\)
Step 6 ：Calculate the p-value: \(p = 0.0104\)
Step 7 ：\(\boxed{\text{Final Answer: Since the p-value is less than the significance level of 0.05, we reject the null hypothesis. Therefore, the square footage of the house significantly affects its sales price.}}\)
