Question Please assist me with the attached. There are two documents posted. The.xls has the data and theregression- see

02 Jun Question Please assist me with the attached. There are two documents posted. The.xls has the data and theregression- see

Question
Please assist me with the attached.

There are two documents posted. The.xls has the data and theregression- see tabs at bottom left. The.doc has the actual problem. The question and background is in black, my answers so far are in blue and the questions I need answered are highlighted in yellow ? they are 6,7,8,9.

Demand estimation
Early in 1993, the Southeastern Transportation Authority (STA), a public agency responsible for serving the commuter rail transportation needs of a large Eastern city, was faced with rising operating deficits on its system. Also, because of a fiscal austerity program at both the federal and state levels, the hope of receiving additional subsidy support was slim.

The board of directors of STA asked the system manager to explore alternatives to alleviate the financial plight of the system. The first suggestion made by the manager was to institute a major cutback in service. This cutback would result in no service after 7:00 pm, no service on weekends, and a reduced schedule of service during the midday period Monday through Friday. The board of STA indicated that this alternative was not likely to be politically acceptable and could only be considered as a last resort

The board suggested that because it had been over five years since the last basic fare increase, a fare increase from the current level of $1 to a new level of $1.50 should be considered. Accordingly, the board ordered the manager to conduct a study of the likely impact of this proposed fare hike.

The system manager has collected data on important variables thought to have a significant impact on the demand for rides on STA. These data have been collected over the past 24 years and include the following variables:

1. Price per ride (in cents) – This variable is designated P in Table 1. Price is expected to have a negative impact on the demand for rides on the system.

2. Population in the metropolitan area serviced by STA – It is expected that this variable has a positive impact on the demand for rides on the System. This variable is designated T in Table 1

3. Disposable per capita income – This variable was initially thought to have a positive impact on the demand for rides on STA This variable is designated I in Table 1

4. Parking rate per hour in the downtown area (in cents) this variable is expected to have a positive impact on demand for rides on the STA. It is designated H in Table 1.

Table 1

Year

Weekly Riders (Y) (X1,000)

Price (P) per Ride

Population (T) (X1,000)

Income (I)

Parking Rate (H) (Cents)

1966

1,200

15

1,200

2,900

50

1967

1,190

15

1,790

3,100

50

1968

1,195

15

1,780

3,200

60

1969

1,110

25

1,778

3,250

60

1970

1,105

25

1,750

3,275

60

1971

1,115

25

1,740

3,290

70

1972

1,130

25

1,725

4,100

75

1973

1,095

30

1,725

4,300

75

1974

1,090

30

1,720

4,400

75

1975

1,087

30

1,705

4,600

80

1976

1,080

30

1,710

4,815

80

1977

1,020

40

1,700

5,285

80

1978

1,010

40

1,695

5,645

85

1979

1,010

40

1,695

5,800

100

1980

1,005

40

1,690

5,900

105

1981

995

40

1,630

5,915

105

1982

930

75

1,640

6,325

105

1983

915

75

1,635

6,500

110

1984

920

75

1,630

6,612

125

1985

940

75

1,620

6,883

130

1986

950

75

1,615

7,005

150

1987

910

100

1,605

7,234

155

1988

930

100

1,590

7,500

165

1989

933

100

1,595

7,600

175

1990

940

100

1,590

7,800

175

1991

942

100

1,600

8,000

190

1992

955

100

1,610

8,100

200

The transit manager has decided perform a multiple regression on the data to deter mine the impact of the rate