The Untold story behind Tech Mahindra’s Satyam Acquisition Now that’s a very powerful title for an article coming as it does from an ex Tech Mahindra staffer who spent close to 13 years at the company and who had a front row seat‚ if not the ringside view. However‚ let me state here that this is not an official version nor have I been encouraged by any of Tech M’s management team to write this piece. This story has been put together through my personal observations‚ side line conversations
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Personal Profile Data Analysis Part One The subject of this report and five other persons with whom the subject worked provided survey forms. Data Analysis started using data obtained from the subject and then progressed to the data collected from the outside participants. This report also contains an analysis of the subject’s strengths‚ weaknesses‚ opportunities‚ and threats. This paper concludes with personal reflections from the subject and a growth plan to improve the behavioral effectiveness
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DATA ANALYSIS After defining the standards and measuring the results it was time to analyze the data to determine if it supported our initial assessments of each dining experience. Our intuition was that Chili’s served the best French fries‚ but that TGI Fridays provided the best service and customer satisfaction. To be sure we needed to cross reference our feelings with actual data. In cases where there was more than one measurement for a given dimension (i.e. Aesthetics‚ Tangibles)‚ the data
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Data Log(Attendance) = B1wins + B2FCI + B3tktprice + B4payroll + B5state + B6earnspop In order to explain the effect that winnings percentage has on attendance‚ I have created an adjusted economic model that I have specified above. In order to test my economic model‚ I have compiled data for each of the variables specified in the model from the years 2003 to 2005. The question that I will be answering in my regression analysis is whether or not wins have an affect on attendance in Major
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Running head: DATA ANALYSIS USING DESCRIPTIVE STATISTICS Data Analysis Using Descriptive Statistics Marissa Navar University of Phoenix Research and Evaluatiion I RES341 Richard A. Stanley June 28‚ 2009 Data Analysis Using Descriptive Statistics Histogram The Histogram chart shows the measurement of frequency in home buyers. It shows what home buyers are willing to spend in today’s current economy. The histogram explains although the economy is in a bad state that some home
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Running head: CASE ANALYSIS OF THE ACCOUNTING FRAUD AT WORLDCOM Case Analysis of the Accounting Fraud at WorldCom Angela Crossley Troy University October 27‚ 2008 History The origin of WorldCom can be traced back to 1983. The CEO‚ Bernard J. Ebbers‚ of WorldCom had very interesting beginnings. He invested in Long Distance Discount Services (LLDS) with eight other investors‚ and believed that the telecommunications industry was a very good business venture. In the beginning
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Computer Fraud and Abuse Techniques Adware Using software to collect web-surfing and spending data and forward it to advertising or media organizations. It also causes banner ads to pop up on computer monitors as the Internet is surfed. Bluebugging Taking control of someone else’s phone to make calls‚ send text messages‚ listen to their phone calls‚ or read their text messages. Bluesnarfing Stealing contact lists‚ images‚ and other data using Bluetooth. Botnet‚ bot herders A network of hijacked
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Data Table Analysis Data Table Analysis Kudler’s Fine Foods is a gourmet food store that provides specialized products in the Southern California region. Since the inventory of the store is perishable‚ it is important to have control of the inventory on hand and put in place a procedure for replacing the inventory promptly. If Kudler’s has too much inventory on hand‚ the loss of revenues due to waste increases. Alternatively‚ if Kudler’s cannot replace inventory fast enough‚ they risk alienating
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SPSS Data Analysis Examples Logit Regression Version info: Code for this page was tested in SPSS 20. Logistic regression‚ also called a logit model‚ is used to model dichotomous outcome variables. In the logit model the log odds of the outcome is modeled as a linear combination of the predictor variables. Please note: The purpose of this page is to show how to use various data analysis commands. It does not cover all aspects of the research process which researchers are expected to do. In particular
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Project / Assignment – I DRISHAN SENGUPTA (MB-1122) PROBLEM Take a time series data of reasonable length on any financial variable of your interest. Instead of real time series‚ you may as well consider a time series of artificially generated (i.e.‚ simulated) data such that the DGP of the series incorporates‚ inter alia‚ volatility. i. Plot the data and comment on its
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