Suppose you estimate restaurant sales as a function of the quality of SERVICE,PRICE,and consumer INCOME and you get the following results (p-values in parentheses) $\begin{array} { lllll }
\text { Sales } _ { i } = & 4,567.29 + &1,245.77 \text { Service } _ { i } + &849.36 \text { Price } _ { i } +& 72.81 \text { Income } _ { i } \
&( 0.003 ) & ( 0.096 ) & ( 0.103 ) & ( 0.047 )
\end{array}$
Given our usual language,we would conclude that
A)SERVICE,PRICE,and INCOME are all statistically significant.
B)INCOME and SERVICE are statistically significant;PRICE is marginally significant.
C)INCOME is statistically significant;SERVICE and PRICE are marginally significant.
D)INCOME is statistically significant;SERVICE are marginally significant;PRICE is statistically insignificant.

Question

Suppose you estimate restaurant sales as a function of the quality of SERVICE,PRICE,and consumer INCOME and you get the following results (p-values in parentheses) $\begin{array} { lllll } 
\text { Sales } _ { i } = & 4,567.29 + &1,245.77 \text { Service } _ { i } + &849.36 \text { Price } _ { i } +& 72.81 \text { Income } _ { i } \
&( 0.003 ) & ( 0.096 ) & ( 0.103 ) & ( 0.047 )
\end{array}$
Given our usual language,we would conclude that
A)SERVICE,PRICE,and INCOME are all statistically significant.
B)INCOME and SERVICE are statistically significant;PRICE is marginally significant.
C)INCOME is statistically significant;SERVICE and PRICE are marginally significant.
D)INCOME is statistically significant;SERVICE are marginally significant;PRICE is statistically insignificant.

Quizplus · Accepted Answer

In statistical analysis, variables with p-values less than 0.05 are considered statistically significant. In this case, INCOME (p = 0.047) is statistically significant. SERVICE (p = 0.096) is marginally significant because its p-value is close to but greater than 0.05, indicating weak evidence against the null hypothesis. PRICE (p = 0.103) is statistically insignificant because its p-value is greater than 0.05, indicating insufficient evidence to reject the null hypothesis.

Suppose You Estimate Restaurant Sales as a Function of the Quality