QUANTITATIVE METHODS PROJECT REPORT SUBMITTED BY DEEPTHI THOMAS GAYATHRI SHARMA CHITHRA R.

OBJECTIVE compare thirty three airlines from different countries in Asia, including India. This data is used to make comparisons and understand more on the basic concepts in Statistics

DATA COLLECTION Data is collected on thirty three randomly selected airlines from different countries in Asia, including India. It is ranked and arranged on the basis of number of passengers traveled in each airline during a particular period. The number of hubs, number of destinations, fleet size, the country to which the airline belongs to, the year of origin, years of operations, etc. for a particular period is taken into consideration for the computations. Source:

VARIABLES USED FOR MEASUREMENT Nominal Variable Nominal Variable In nominal scaling, we check for equalities. That is, the data can only be a qualitative one, and cannot be quantified. We can only label the data but cannot be ranked. In nominal scaling, we check for equalities. That is, the data can only be a qualitative one, and cannot be quantified. We can only label the data but cannot be ranked. Here in our example, name of the airlines and the country to which the airlines belong to, can be considered as nominal data. Here in our example, name of the airlines and the country to which the airlines belong to, can be considered as nominal data. Ordinal Variable Ordinal Variable It is a qualitative data and it can be ranked. But the differences between each rank cannot be determined. In ordinal data, the values are arranged in an order but the interval is not taken into consideration. It is a qualitative data and it can be ranked. But the differences between each rank cannot be determined. In ordinal data, the values are arranged in an order but the interval is not taken into consideration. In our example, the airlines are graded in the basis of the number of destinations as very low, low, medium, high and very high. In our example, the airlines are graded in the basis of the number of destinations as very low, low, medium, high and very high. Interval Variable Interval Variable Here the data can be ranked and the difference between each rank (interval) can be determined. But the interval may not be proportional. Here the data can be ranked and the difference between each rank (interval) can be determined. But the interval may not be proportional. In case of airlines, the airlines are ranked on the basis of number of passengers; and this can be considered as an interval variable. In case of airlines, the airlines are ranked on the basis of number of passengers; and this can be considered as an interval variable. The other variables used are number if hubs, fleet size, year of origin, number of years of operation, etc. The other variables used are number if hubs, fleet size, year of origin, number of years of operation, etc.

DATABASE AND MEASURES OF CENTRAL TENDENCY AIRLINES IN ASIA CountryNameTotalRank-pass No of hubs Fleet Size Destinations Year of Origin Years of Operation Grade Japan Japanese Group 56,736, ,99017high China China Southern Airlines 54,372, high Japan All Nippon Airways 50,750, ,95255low China Air China 34,003, ,98819 very high China China Eastern Airlines 24,285, ,98819medium Korea Korean Air 22,353, ,96938medium Thailand Thai Airways International 19,376, ,96047low Singapore Singapore Airlines 18,703, ,94760low UAE Saudi Arabian Airlines 17,571, ,94562low UAEEmirates17,544, ,98522medium Honkong Cathay Pacific 16,727, ,94661medium

China Hainan Airlines 14,390, ,98918medium Malaysia Air Asia Group 13,992, ,99314 very low Malaysia Malaysia Airlines 13,928, ,94760low South Korea Asiana Airlines 11,907, ,98819low China China Airlines 9,731, ,95948low Philippines Philippine Airlines 9,010, ,94166low India Jet Airways 9,000, ,99314low Indonesia Garuda Indonesia 8,678, ,94958low India Indian Airline 7,500, ,95354low Vietnam Vietnam Airlines 6,800, ,95651 very low Taiwan Eva Air 6,126, ,98918low India Air Deccan 5,900, ,0034low Pakistan Pakistan International Airlines 5,499, ,94661low Hongkong Dragon Air 5,476, ,98522 very low India Air India 4,860, ,93275medium Israel El Al 3,593, ,94859low Philippines Cebu Pacific 3,500, ,99611 very low Thailand Thai Air Asia 3,303, ,0034 very low China Air Macau 2,360, ,99413 very low Indonesia Indonesia Air Asia 1,950, ,0043 very low Singapore Silk Air 1,560, ,98918 very low Singapore Tiger Airways 1,200, ,0034 very low

MEAN 14,626, ,97334 MEDIAN 9,010, ,98522 STD DEV VARIANCE E MODE

BAR CHART PASSENGER PER AIRLINES This bar chart shows the number of passengers per airline in different countries. From this chart we can understand that the number of passengers per airline is more in the countries like Japan, China, Korea, etc. And based on this the airline companies can compare the prospects of running an airline company in the following countries; whether it will be profitable or not.

PIE CHART NUMBER OF AIRLINES PER COUNTRY

NUMBER OF PASSENGERS PER COUNTRY

This pie diagram shows the ratio between the numbers of airlines in each country. China has the highest percentage of airlines (19%) and India with the second highest percentage of 12. Even though China and India has the highest percentages of number of airlines, Japan has the highest number of passengers per airline. China is the second highest in the number of passengers per airline. So from this, we can conclude that Despite the fact that China has the highest number of airlines, they still have sufficient number of passengers per airline. But Japan, even though they have highest number of passengers per airline, the number of airlines in Japan is very less. But in India, the proportion between the number of airlines and the number of passengers per airline is less compared to. So, it is advisable for the airline companies to start new airlines or extend their existing services to Japan, China, Korea, and UAE. India, even though the number of airlines is more, passenger per airline is less and we can conclude that the passengers traveling through air are much less in India compared to Japan, China and Korea.

CORRELATION CORRELATION BETWEEN NUMBER OF DESTINATIONS AND FLEET SIZE The above scatter diagram shows the correlation between number of destinations and fleet size. There is a high positive correlation of This means that there is a strong relationship between the number of destinations and fleet size.

CORRELATION BETWEEN NUMBER OF PASSENGERS AND FLEET SIZE This is the scatter diagram showing the correlation between number of passengers and fleet size. There is a positive correlation of This shows that there is a very strong relationship between number of passengers and the number of fleets.

PIE CHART BASED ON ORDINAL DATA GRADES BASED ON NUMBER OF DESTNATIONS This pie chart is based on the grades assigned to airlines based on the number of destinations. The grades assigned are very low, low, medium, high and very high. Out of thirty three airlines, nine airlines comes under very low category, fifteen comes under low, six under medium, two under high and only one under very high category. Just by observing the pie chart we can know that majority of the airline have number of destinations which comes under low and very low; and there are only three airlines out of thirty three, that comes under high and very high category, which is a very low percentage.

PROBABILITY BINOMIAL DISTRIBUTION Probability of a randomly selected airline is from China. p0.18 n5 mean X P(x) Probability of getting two airlines from China in five trials is

NORMAL DISTRIBUTION The probability of getting an airline with fleet size less than 50 mean81 std dev X

CONDITIONAL PROBABILITYPass(1000,s)InternationalBothDomesticTotal Total Probability of randomly choosing an international airline=8/31 Probability of choosing a domestic airline having less than 300 passengers=6/31 Probability of choosing an airline which has both international and domestic carriers=16/31 *Here the data taken (domestic passengers and international passengers) are not actual figures. They are merely numbers used for computations.

FREQUENCY DISTRIBUTION CHART Number of airlines with total number of passengers less than ten thousand (in thousands) is eighteen.And number of airlines with total number of passengers between fifty thousand and sixty thousand are only three. From this frequency distribution, we can understand that the majority of the airlines have passengers less than twenty thousand or less than or equal to the average (14,626).

CUMULATIVE FREQUENCY CURVE This is the cumulative frequency chart showing number of airlines having total number of passengers under each class of , and so on till

SUMMARY The important points we can arrive at from this project are listed below. The important points we can arrive at from this project are listed below. It is advisable for airline companies to start new airlines in countries like Japan, China, Korea, etc. which have highest number of passengers per airline. It is advisable for airline companies to start new airlines in countries like Japan, China, Korea, etc. which have highest number of passengers per airline. Even though the number of airlines in India is more, the passengers traveling through air are much less in India when compared to Japan, China, Korea, UAE, Malaysia, etc. Even though the number of airlines in India is more, the passengers traveling through air are much less in India when compared to Japan, China, Korea, UAE, Malaysia, etc. As the fleet size increases, the number of destinations increases; and as the number of passengers increases, fleet size increases and both have a strong correlation. As the fleet size increases, the number of destinations increases; and as the number of passengers increases, fleet size increases and both have a strong correlation. Most of the airlines have passengers less than twenty thousand which is more or less equal to the average (14,626). Most of the airlines have passengers less than twenty thousand which is more or less equal to the average (14,626).