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\title{ICICI Bank: A Multivariate Analysis of Customers' Acceptability}
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             \author[1]{Sangeeta  Mohanty}

             \affil[1]{  Academy of Business Administration, Balasoe}

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\date{\small \em Received: 21 July 2011 Accepted: 10 August 2011 Published: 25 August 2011}

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\begin{abstract}
        


The explosive growth of the economy and the favorable demographic profile continue to drive consumption demand. This will lead to a market for a wide range of financial products and services for consumers. Many financial institutions have clearly embarked on the development of technology driven strategies, which will be translated in terms of customer preferences, and consequently, higher returns and market penetrations. New formats such as ATMs, telephone banking, e-banking can encourage customers to carry out more transactions. This increased usage can increase banks? customer. New technologies have been emerged inorder to attract the customer as well as there is deadly competition among the private and the public banks to capture the market and the customer. Increasing competition is forcing the banks to pay much more attention to satisfy the customers. The existence of the bank is dependant on the customer?s acceptability only. This paper is intended to study ICICI Bank-thelargest private bank in India and the second largest in the entire banking sector, on the ground of customer?s acceptability.

\end{abstract}


\keywords{ICICI Bank, Acceptability, Banking sector.}

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\let\tabcellsep& 	 	 		 
\section[{INTRODUCTION}]{INTRODUCTION}\par
he banking sector has witnessed a dramatic change during the last few years. The emergence of NPSBs, expansion by the foreign banks, the changing business model transformed the ways banks in India. The government-owned commercial banks today have a market share of around 75\% (down from the earlier 95\%), the private sector banks about 20\% and the foreign banks about 5\% .In the wake of the liberalization policies, the traditional and the conservative face of the Indian banking has undergone a virtual change. The Indian banking industry is undergoing a paradigm shift in scope, context, structure, functions and governance. The information technology revolution is radically changing the operational environment of the banks. Universal banking, virtual banking and Merger \&Acquisition are increasingly emerging as the order of the day. For the banks, technology has emerged as a strategic resource for achieving higher efficiency, control of the operation, productivity and the profitability. The Indian banking industry is on a major technology upgradation drive after having successfully absorbed international standards in its operating norms. The country's financial markets are now characterized by financial liberalization and technological advancement.\par
Author: Assistant Professor, Academy of Business Administration, Industrial Estate (S1/25) Angaragadia, Balasore, Orissa (756001).\par
When companies invest in new technology for customers, its success should be evaluated not only according to how efficiently it lowers the cost of operations, but also whether customers see it as delivering real benefits. There is a growing understanding among banks that to survive in the future, they not only need to be organized around information and knowledge but should also be customer-centric, market-driven, highly networked, on the constant look out for global opportunities and flexible in their ability to deliver superior value to the customer. Because of the converging pressure of the changing demographics, global politics, technology, the banks are forced to know the business opportunities from the customers' point of view and also to redefine the facilities provided by them accordingly. 
\section[{II.}]{II.} 
\section[{BANKING SERVICES IN INDIA}]{BANKING SERVICES IN INDIA}\par
Banking in India has been dominated by the offices/branches of the public sector banks. However, with the liberalization of the financial sector in the 1990's, the private-sector banks and the foreign banks have also set up their shops all over the country. These newly set up commercial banks are offering aggressive and technology -savvy competition to the public sector banks in the form of innovative products and services. With years, banks are also adding services to their customers. The Indian banking industry is passing through a phase of customers market. The customers have more choices in choosing their banks. A competition has been established within the banks operating in India. With stiff competition and advancement of technology, the services provided by banks have become more easy and convenient.\par
Traditionally, banking players relied extensively on their reach to effectively put emerging banks out of competition. To describe the new potential scenario we must create a vision of what might constitute the new potential business concept. If we start a new bank from scratch, independent of history and based on a perception of the consequences of the rapid on-going change for the coming five years then we think of the different service channels and their range of services. Any channel, at the choice of the customer is always accepted. This forced new banks to develop strategies, that could help them reach out to end-customers cost effectively. The solution came in the form of a delivery T E -mail : sangeeta\textunderscore mohanty@rediffmail.com. channel known as Automated Teller Machines or ATMs, mobile banking, e-banking system etc. This turned out to be one of the biggest growth drivers for private banks in India. All these facts automatically encourage the banks to expand in the field keeping in mind the acceptability of the customers'. 
\section[{III.}]{III.} 
\section[{ICICI BANK IN INDIA}]{ICICI BANK IN INDIA}\par
ICICI Bank India is the largest private bank in India and the second largest in the entire banking sector. Only State Bank of India (SBI), controlled entirely by the Government of India has a bigger business than ICICI Bank. ICICI Bank, founded in 1955 as Industrial Credit and Investment Corporation of India, ICICI Limited was established by the Government of India in the 1960s as a Financial Institution like Industrial Development Bank of India (IDBI) to finance large industrial projects. ICICI then, was not a bank and hence could not take retail deposits and was not required to comply with Indian banking requirements for liquid reserves. ICICI borrowed funds from various agencies like the World Bank, often at concessional rates. These funds were deployed in large corporate loans. However, the scenario changed drastically in1990s when ICICI founded a separate legal entity and named it "ICICI Bank".ICICI Bank, as the name would suggest, undertook normal banking operations like accepting deposits, issuing credit cards, providing car loans etc. The experiment was so successful that ICICI merged into ICICI Bank and this "reverse merger" happened in 2002. In 2001, ICICI bank acquired Bank of Madura Limited. ICICI Bank set up its international banking group in fiscal 2002 to cater to the cross border needs of clients and leverage on its domestic banking strengths to offer products internationally. ICICI Bank currently has subsidiaries in the United Kingdom, Canada and Russia, branches in Singapore and Bahrain and representative offices in the United States, China, United Arab Emirates, Bangladesh and South Africa. Today, ICICI Bank offers a wide range of banking products and financial services to corporate and retail customers through a variety of delivery channels and through its specialized subsidiaries and affiliates in the areas of investment banking, life and non-life insurance, venture capital and asset management.\par
IV. 
\section[{FRAMEWORK OF ANALYSIS}]{FRAMEWORK OF ANALYSIS}\par
If a bank already has a reputation for technical innovation, its customers are more likely to feel comfortable with more technology. Bank marketing managers need to continuously assess the customer's decisions-making process as well as the formation of attitudes, preferences and satisfaction of the different delivery channels. The banking industry has tried to take advantage of the productivity and customers service gains associated with technology by provisions of ATMs, mobile banking, Credit card payment and Debit card payment system etc However, while these new technologies may offer significant advantages to the consumers, many are unwilling to adopt them. It is very important to understand the customer's preferences, attitudes and adaptations of these services to properly use them as marketing tools to attract new clients and retain the existing clients. As ICICI Bank India is the largest private bank in India and the second largest in the entire banking sector, we need to know the customers acceptability of the said bank.\par
V. 
\section[{OBJECTIVE OF THE STUDY}]{OBJECTIVE OF THE STUDY}\par
The study is aimed at evaluating and appraising customer's priorities in regard to access the ICICI bank. In order to examine these, this paper has the following objectives before it: VI. 
\section[{COLLECTION OF DATA}]{COLLECTION OF DATA}\par
In order to achieve the identified objective pertaining to the priorities and preferences and views, a sample of 125 investors was taken randomly from Sahid Nagar, Acharya Vihar, Vanivihar, Ram Mandir in the city Bhubaneswar, Balasore. A pre-tested questionnaire was administered to the ICICI bank customers. The data have been collected by personal interviews with the help of the pre-defined interview schedule. A structured questionnaire was used as a data collection tool, and the statistical random sampling was used for the purpose of the study. The survey was conducted during August, September 2010, among 125 geographically dispersed ICICI bank customers spread over the city. 
\section[{VII.}]{VII.} 
\section[{TOOLS AND TECHNIQUES USED}]{TOOLS AND TECHNIQUES USED}\par
Tables' bar diagram and structures are used in explanations to bring out the point more clearly. Tabulation of the primary data was done. On the basis of these tables, trends came out more visibly. Other statistical techniques those used are,\par
? Percentage method -it shows the trend of the variable.\par
? Chi-square -it is used to test the independence of the attributes. 
\section[{IX September}]{IX September}\par
1. To find out the most preferable type of the bank account. 2. To find out the Period of association of the people with the bank. 3. To know the relationship between the frequency of visits and Income level, occupation, Education level.\par
To ascertain the relationship between the preferred choice of banking services and the educational level. 4. To find out the factors influencing the opening of a bank account among the respondents. 5. To find out the relationship between the rank and the factors influencing the opening of a bank account among the respondents. 6. To find out the relation of tracking transaction, credit card payment and demat services with the frequency of visits.\par
? Anova-it is used to test the variability of the different groups.\par
? Ranking method-its basic property is to arrange a number of attributes in a particular order.\par
? Kolmogorov-Smirnov test -It is used to test the relationship between the rank and the factors influencing the attributes.\par
? Multiple Regression technique -This statistical technique explores linear relationships between the predictor and criterion variable VIII. 
\section[{ANALYSIS AND INTERPRETATION a) Type of the Bank Account}]{ANALYSIS AND INTERPRETATION a) Type of the Bank Account}\par
The nature of the respondents' transactions was analyzed according to the type of account they had with the bank. For the purpose of this analysis the accounts were classified as current account, saving account, term deposits and demand deposits. The differences are analyzed statistically using one-way ANOVA. 
\section[{Null Hypothesis:}]{Null Hypothesis:}\par
H 0 : There is no significant difference in service pattern of the different accounts .\par
Anova Interpretation: It is inferred that there are significant differences between various account services. We proceed further to know which account usage is preferable one.\par
Graph.1\par
? It is observed that 44\% of the people have the current account services followed by the saving account i.e. 26\% 
\section[{b) Period of Association with the bank}]{b) Period of Association with the bank}\par
The Period of Association with the bank is measured as the number of months that the respondents had been operating the bank account with the service provider. For convenient analysis, respondents' are divided into four groups such as, the respondents having an account for less than six months (new users), between six to twelve months, between twelve to eighteen months and more than eighteen months. Adoption of the different services is analyzed statistically using one-way ANOVA. 
\section[{Null Hypothesis:}]{Null Hypothesis:}\par
H 0 : There is no difference in service pattern of the different accounts with respect to age (period of association with the bank).\par
Anova Interpretation : It is inferred that there are significant differences between various account services in terms of the period of association with the bank.\par
c) The Relationship between the frequency of visits and income level, occupation, educational level.\par
The relationship is tested by using two-way ANOVA (i) The Relationship between the frequency of visits and income level\par
To test the relationship between the income of the respondents and the frequency of the visits to the bank, the respondents' are divided into four groups according to their income level such as (>15,000), (15,000-25,000), (25,000-35,000), (35,000 and more).The data have been collected about the frequency of visits weekly or fortnightly or monthly or quarterly.\par
The following hypotheses have been formulated to analyze the data using two-way ANOVA. 
\section[{Null Hypothesis:}]{Null Hypothesis:}\par
H 01 : There is no significant difference in the income levels.\par
H 02 : The respondents' do not differ much with respect to the frequency of visits to the bank.\par
Anova Interpretation: It is inferred that, the people have a wide difference with respect to the income level and also the frequency of visiting the bank. We proceed further to know which income group people visit the bank most. 
\section[{Graph. 2}]{Graph. 2}\par
? It is observed that the people of higher income group visit the bank the most.\par
(ii) The Relationship between the frequency of visits and occupation\par
For the convenience of the analysis of the relationship between the occupation of the respondents and the frequency of the visits to the bank, the respondents' are divided into four groups such as government servant, professionals, private sector employees and the business men. The data have been collected about the frequency of visits weekly or fortnightly or monthly or quarterly.\par
The following hypotheses have been formulated to analyze the data using two-way ANOVA 
\section[{Null Hypothesis:}]{Null Hypothesis:}\par
H 01 : There is no significant difference in the occupation.\par
H 02 : The respondents' do not differ much with respect to the frequency of visits to the bank.\par
Anova Finding out the critical differences and comparing these with each other, we find insignificant difference among the treatments A 1, B 1, C 1, D 1 , E 1 (column wise).\par
? There exists insignificant differences among the people of the different occupation but, the mean score of the businessmen and the monthly visits to the bank are the maximum. So, business men visit the bank the most and the people visit the bank mostly quarterly. 
\section[{c) The Relationship between the frequency of visits and educational qualification}]{c) The Relationship between the frequency of visits and educational qualification}\par
The people assessing to ICICI bank are spread on a cross-section of the different education groups from under graduate to professional degree. A majority of the respondents are graduates and professional. This basic objective of the analysis is to find out whether there is an association among the people of different educational levels as well as the frequency of visits to the bank.\par
The following hypotheses have been formulated to analyze the data using two-way ANOVA 
\section[{Null Hypothesis:}]{Null Hypothesis:}\par
H 01 : There is no significant difference in the occupation.\par
Anova Table  {\ref -}   {\ref ---------H} 02 is accepted.\par
Interpretation : It is inferred that, the people have a wide difference with respect to the frequency of visiting the bank and there exists insignificant differences among the people of the different levels education. 
\section[{d) The Relationship between the preferred choice of banking services and the educational level}]{d) The Relationship between the preferred choice of banking services and the educational level}\par
The association between the variables is tested by using chi-square test. Null hypothesis H 0 : There is no significant association between the education level and the preferred choice of banking.\par
Statistical test : Chi square test is the most appropriate test for this purpose.\par
Level of significance : Desired level of significance is 5\% = 0.05 Degrees of freedom : (4-1) (4-1) = 9 Test statistic :\par
Chi-Square Tests H 0 is rejected and H 1 is accepted Interpretation : So, H 0 is rejected and H 1 is accepted. In other words, there is an association between the education level and the preferred choice of banking.\par
Phi coefficient : It is used to test the strength of association between two variables i.e. education level and the preferred choice of banking.? = ? (x 2 / N) = 0.145\par
The value ? is nearer to zero. It indicates that the association between two variables is not so strong.\par
We proceed further to know the most popular choice of the banking services. 
\section[{Graph . 3}]{Graph . 3}\par
? It is observed that the people prefer to the ATM card services the most.\par
e) The relationship between the rank and the factors influencing the opening of a bank account among the respondents Satisfaction is an important element to create demand for any banking services. When a consumer gets satisfaction from the services, he becomes the ambassador for that. It is therefore necessary to assess the relationship between the rank and the factors influencing the opening of a bank account among the respondents. The data have been collected on 5-point likert type scale in all five attributes. The statements were measurable on a Likert scale of 1-5; where 5 indicates strongly disagree and 1 indicates strongly agree. From the above analysis we observed that two attributes Convenient ATM location and the convenient bank location have the lowest rank sum. So, we conclude that the Convenient ATM location and the Convenient bank location are the more influencing Let us test the relationship between the rank and the factors influencing the opening of the bank account among the respondents by using Kolmogorov-Smirnov test. 
\section[{Graph of Preferred choice of Banking}]{Graph of Preferred choice of Banking}\par
Null hypothesis H 0 : There is no relationship between the rank and the factors influencing the opening of a bank account among the respondents.  Interpretation : As H 0 is rejected and H 1 is accepted, there exists a relationship between the rank and the factors influencing the opening of a bank account among the respondents.\par
f) The effect of tracking transaction, credit card payment and demat services on the frequency of visits.\par
The frequency of visits of the customer to the bank is correlated with tracking transaction, credit card payment and demats services. Here the basic interest is to find out the weightage of the independent variables (tracking transaction, credit card payment and demat services) on the predictor, frequency of visits by using the Multiple Regression technique.\par
Let Y be the dependent variable = frequency of visits B = the coefficient of determinant (a constant value) X 1 = tracking transaction Adjusted R Square value tells us that our model accounts for 97.8\% of variance in the frequency of visits and it signifies that it is a very good model. This table gives details of the correlation between each pair of variables. There is a very good correlation between the criterion and the predictor variables. The values here are acceptable. a Dependent Variable : YX 2 = credit card payment X 3 = demat services Y = B 0 + B 1 X 1 + B 2 X 2 + B 3 X 3 Step-by-Step Multiple Regression\par
The Standardized Beta Coefficients give a measure of the contribution of each variable to the model. A large value indicates that a unit change in this predictor variable has a large effect on the criterion variable. The t and Sig ( p) values give a rough indication of the impact of each predictor variable -a big absolute t value and small p value suggests that a predictor variables having a large impact on the criterion variable.\par
Tracking transaction has the highest beta value (.340), credit card payment and the demat services have the negative values of (-1.1886) and (-0.127).Error variance is explained by constant by 14.506, followed by tracking transaction (0.422), credit card payment (0.938), demat services (0.518).Sample t-test correlates positively for tracking transaction (1.427) with the frequency of visits to the bank.Y = 29.509 + 0.603 X 1 -1.886 X 2 -0.127X 3\par
By substituting the values 0,1,2,3 for the predictor constant, the frequency of visits can be predicted for every account holder. 
\section[{IX.}]{IX.} 
\section[{CONCLUSION AND FINDINGS}]{CONCLUSION AND FINDINGS}\par
India has a well developed banking system. Most of the banks in India were founded by Indian entrepreneurs to provide financial assistance to traders, agriculturists and Indian industrialists. Indian banks have played a significant role in the development of Indian economy by inculcating the habit of saving in Indians and by lending finance to Indian industry. The ICICI Group is well positioned to participate in and contribute to this process. ICICI bank is among the first to recognize the opportunity presented by the retail market. With the increase in employment opportunities, it has made it possible to open up the doors for the retail sectors which have led to access the banks more frequently. The purpose of measuring customers' acceptability of ICICI bank is to see whether the ICICI bank stands in this regard in the eyes of its customers, thereby enabling service and product improvements leading to higher satisfaction levels. The research is just one component in the quest to improve customer satisfaction. The major findings of the study are given below. a. It is found that there exist significant differences between various account services such as current account, saving account, term deposits and demand deposits and 44\% of the people have the current d. There exists insignificant differences among the people of the different occupation but, the business men visit the bank the most and the people visit the bank mostly quarterly. e. It is found that, the people have a wide difference with respect to the frequency of visiting the bank and there exists insignificant differences among the people of the different levels of education. f. There is no strong association between the education level and the preferred choice of banking. At the same time it is observed that the people prefer to the ATM card services (36\%) the most followed by phone banking (34\%). g. There exists a relationship between the rank and the factors influencing the opening of a bank account among the respondents. h. It is found that the Convenient ATM location and the Convenient bank location are the more influencing factors of opening the bank account where as the least preference goes to Loan / Deposits. i. The frequency of visits is positively correlated with the tracking transaction and it is negatively correlated with the credit card payment and demat services. account services followed by the saving account i.e. 26\% b. It is inferred that there are significant differences between various account services in terms of the period of association with the bank. c. It is observed that the people of higher income group visit the bank most.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.5988636363636364\textwidth}P{0.028977272727272723\textwidth}P{0.08693181818181818\textwidth}P{0.09981060606060606\textwidth}P{0.035416666666666666\textwidth}}
Sources of variation\tabcellsep d.f.\tabcellsep Sum of squares\tabcellsep Mean Sum of squares\tabcellsep F\\
Column (type of account)\tabcellsep 3\tabcellsep 81.267\tabcellsep 27.089\tabcellsep F 1 = 4.21\\
Error\tabcellsep 12\tabcellsep 77.2128\tabcellsep 6.4344\tabcellsep \\
Total\tabcellsep 15\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Level of significance : Desired level of significance is}\tabcellsep \tabcellsep \\
5\%\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{F 0.05 (3, 20) =3.5874 < Cal. F 1 (type of account) ------H 01}\tabcellsep \tabcellsep \\
is rejected\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_0}Table 1}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.5988636363636364\textwidth}P{0.028977272727272723\textwidth}P{0.08693181818181818\textwidth}P{0.09981060606060606\textwidth}P{0.035416666666666666\textwidth}}
Sources of variation\tabcellsep d.f.\tabcellsep Sum of squares\tabcellsep Mean Sum of squares\tabcellsep F\\
Column (type of account)\tabcellsep 3\tabcellsep 81.267\tabcellsep 27.089\tabcellsep F 1 = 4.21\\
Error\tabcellsep 12\tabcellsep 77.2128\tabcellsep 6.4344\tabcellsep \\
Total\tabcellsep 15\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Level of significance : Desired level of significance is}\tabcellsep \tabcellsep \\
5\%\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{F 0.05 (3, 20) =3.5874 < Cal. F 1 (type of account) ------H 01}\tabcellsep \tabcellsep \\
is rejected\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
  {\small\itshape [Note: ICICI Bank: A Multivariate Analysis of Customers' Acceptability]} 
\caption{\label{tab_1}Table 2}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.655256064690027\textwidth}P{0.020619946091644203\textwidth}P{0.068733153638814\textwidth}P{0.08018867924528303\textwidth}P{0.025202156334231805\textwidth}}
Sources of variation\tabcellsep d.f.\tabcellsep Sum of squares\tabcellsep Mean Sum of squares\tabcellsep F\\
Row (Frequency of visits)\tabcellsep 3\tabcellsep 83.621\tabcellsep 27.873\tabcellsep 4.22\\
Column (Income level)\tabcellsep 3\tabcellsep 79.856\tabcellsep 26.619\tabcellsep 4.0331\\
Error\tabcellsep 9\tabcellsep 59.4\tabcellsep 6.60\tabcellsep \\
Total\tabcellsep 15\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Level of significance : Desired level of significance is}\tabcellsep \tabcellsep \\
5\%\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{F 0.05 (3, 15) =3.2874 < Cal. F 1 (Frequency of visits) ------}\tabcellsep \tabcellsep \\
H 01 is rejected\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{F 0.05 (3, 15) = 3.2874 < Cal. F 2 (Income level) --------H 02}\tabcellsep \tabcellsep \\
is rejected\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table 3}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.38827160493827156\textwidth}P{0.04722222222222222\textwidth}P{0.17314814814814813\textwidth}P{0.19413580246913578\textwidth}P{0.04722222222222222\textwidth}}
Sources of variation\tabcellsep d.f.\tabcellsep Sum of squares\tabcellsep Mean Sum of squares\tabcellsep F\\
Row (Frequency of visits)\tabcellsep 3\tabcellsep 71.9088\tabcellsep 23.9696\tabcellsep 3.87\\
Column (Occupation)\tabcellsep 3\tabcellsep 70.0344\tabcellsep 23.3448\tabcellsep 4.11\\
Error\tabcellsep 9\tabcellsep 41.12\tabcellsep 5.68\tabcellsep \\
Total\tabcellsep 15\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 4}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.398015873015873\textwidth}P{0.06071428571428571\textwidth}P{0.08769841269841269\textwidth}P{0.11468253968253968\textwidth}P{0.11468253968253968\textwidth}P{0.0742063492063492\textwidth}}
Preferred choice of Banking\tabcellsep Under\tabcellsep Graduates\tabcellsep Post Graduates\tabcellsep Professionals\tabcellsep Total\\
Phone Banking\tabcellsep 19\tabcellsep 12\tabcellsep 6\tabcellsep 5\tabcellsep 42\\
Internet Banking\tabcellsep 3\tabcellsep 3\tabcellsep 4\tabcellsep 8\tabcellsep 18\\
ATM\tabcellsep 9\tabcellsep 8\tabcellsep 8\tabcellsep 20\tabcellsep 45\end{longtable} \par
 
\caption{\label{tab_5}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.10625\textwidth}P{0.74375\textwidth}}
d.f\tabcellsep Asymp. Sig. (2-sided)\end{longtable} \par
 
\caption{\label{tab_6}Table 9 Value}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{10} \par 
\begin{longtable}{P{0.85\textwidth}}
: Rank\end{longtable} \par
 
\caption{\label{tab_7}Table 10}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{11} \par 
\begin{longtable}{P{0.655794701986755\textwidth}P{0.11821192052980131\textwidth}P{0.0759933774834437\textwidth}}
( Observed\tabcellsep E (Expected frequency)\tabcellsep O -E\\
1.616\tabcellsep 0.20\tabcellsep 1.416\\
1.56\tabcellsep 0.20\tabcellsep 1.36\\
2.232\tabcellsep 0.20\tabcellsep 2.032\\
1.992\tabcellsep 0.20\tabcellsep 1.792\\
1.92\tabcellsep 0.20\tabcellsep 1.72\\
\multicolumn{2}{l}{Test statistic : KS -calculated value is obtained by the}\tabcellsep \\
following rule\tabcellsep \tabcellsep \\
? (O-E) = 8.608\tabcellsep \tabcellsep \\
KS -calculated value = (1.36 / ? n) = 0.1225\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Calculated Value > Tabulated value, H 0 is}\tabcellsep \\
rejected and H 1 is accepted.\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_9}Table 11 O}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{12} \par 
\begin{longtable}{P{0.3297413793103448\textwidth}P{0.06594827586206897\textwidth}P{0.05862068965517241\textwidth}P{0.15387931034482757\textwidth}P{0.2418103448275862\textwidth}}
\multicolumn{2}{l}{Model R}\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\\
1\tabcellsep \multicolumn{2}{l}{.989 .978}\tabcellsep .968\tabcellsep 1.63656\\
\multicolumn{4}{l}{a Predictors : (Constant), X3, X1, X2}\end{longtable} \par
 
\caption{\label{tab_10}Table 12 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{13} \par 
\begin{longtable}{P{0.38163265306122446\textwidth}P{0.09251700680272108\textwidth}P{0.1792517006802721\textwidth}P{0.09829931972789116\textwidth}P{0.09829931972789116\textwidth}}
\tabcellsep \tabcellsep : Correlations\tabcellsep \tabcellsep \\
\tabcellsep Y\tabcellsep X1\tabcellsep X2\tabcellsep X3\\
Y\tabcellsep 1\tabcellsep .975\tabcellsep -.985\tabcellsep -.932\\
X1\tabcellsep .975\tabcellsep 1\tabcellsep -.967\tabcellsep -.905\\
X2\tabcellsep -.985\tabcellsep -.967\tabcellsep 1\tabcellsep .943\\
X3\tabcellsep -.932\tabcellsep -.905\tabcellsep .943\tabcellsep 1\\
\multicolumn{3}{l}{** Correlation is significant at the 0.01 level (2-tailed).}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_11}Table 13}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{14} \par 
\begin{longtable}{P{0.08333333333333333\textwidth}P{0.25\textwidth}P{0.16666666666666666\textwidth}P{0.26666666666666666\textwidth}P{0.016666666666666666\textwidth}P{0.06666666666666667\textwidth}}
\tabcellsep Unstandardized\tabcellsep \tabcellsep Standardized\tabcellsep t\tabcellsep Sig.\\
Model\tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\end{longtable} \par
 
\caption{\label{tab_12}Table 14 :}\end{figure}
 			\footnote{© 2011 Global Journals Inc. (US) September} 			\footnote{© 2011 Global Journals Inc. (US) © 2011 Global Journals Inc. (US)} 			\footnote{© 2011 Global Journals Inc. (US) © 2011 Global Journals Inc. (US) IX September} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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