Step 1: Identifying the dependent variable.
The dependent variable is the one that depends on other variables and is the outcome of the model. Here, the model predicts the number of trips generated from a particular area. Thus, the number of trips is the variable that is being modeled based on various independent factors like population, household size, employment, and land use types.
Step 2: Clarifying the options.
- (A) Population of Traffic Analysis Zone: This is an independent variable, not the dependent variable.
- (C) Number of employees: This could be a predictor variable in the model, but not the dependent variable.
- (D) Number of households: Similarly, this can be an independent variable, but not the dependent one.
- (B) Number of trips: This is the correct choice since it is the outcome being predicted based on the other variables.
Final Answer: (B)
Match the items in Group-I with the most appropriate stages of travel demand modelling in Group-II.
\[\begin{array}{|c|c|} \hline \textbf{Group I} & \textbf{Group II} \\ \hline (P)\ \text{US-EPA's MOVES} & (1)\ \text{Trip Assignment} \\ (Q)\ \text{Fratar Model} & (2)\ \text{Trip Production} \\ (R)\ \text{Growth Factor Model} & (3)\ \text{Trip Distribution} \\ (S)\ \text{User Equilibrium} & (4)\ \text{Mobile source emission estimation} \\ & (5)\ \text{Destination Choice} \\ \hline \end{array} \]
P and Q play chess frequently against each other. Of these matches, P has won 80% of the matches, drawn 15% of the matches, and lost 5% of the matches.
If they play 3 more matches, what is the probability of P winning exactly 2 of these 3 matches?