Bus and subway ridership for the summer months in London, England, is believed to be tied heavility to the number of tourists visiting the city. DUring the past 12 years, the data on the next page have been obtained.

Year (Summer Months) Number of Tourists (In Millions) Ridership In Millions)
1 7 1.5
2 2 1.0
3 0 1.3
4 4 1.5
5 14 2.5
6 15 14
7 16 24
8 12 2.0
9 14 10
10 20 4.4
11 15 3.4
12 7 1.7

Plot these data and decide if a linear model is reasonable.

The data can be represented as a linear model.

Step-by-step explanation:

The data is provided for the Bus and subway ridership for the summer months in London, England for 12 years.

The data can be plotted as follows:

Step 1:

Mark the x-axis as the number of tourists and y-axis as the Ridership (in millions).

Step 2:

Take the scale as follows:

x-axis: 1 unit = 5 tourists

y-axis: 1 unit = 5 million

Step 3:

Plot the points corresponding to the x and y axis.

For example, for year 1 the point to marked is (7, 1.5), for year 2 the point to be marked is (2, 1) and so on.

The graph for the data is provided below.

A linear model is used to predict the values of the response variable based on one or more than one predictor variable.

The response and predictor variables has a straight line relationship.

In this case the response variable is Ridership and the predictor variable is the Number of tourists.

As the ridership value can be estimated from the number of tourists value the data can be represented as a linear model.

a framing bias

step-by-step explanation:

rodrigo is subject to a framing bias i believe.