retailers behavior towards Aircel in selected region. The data is collected directly by visiting outlets through structured interview scheduled. The statistical tools used to analyze the data are: Co-relation analysis‚ Simple Linear Regression and Multiple Linear Regression. The software used to analyze the data is Windostat version 8.6‚ developed by Indostat services‚ is an advanced level statistical software for research and experimental data analysis. The study is carried mainly in the areas like
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A SUMMER TRAINING PROJECT REPORT On “A study on Wage and Salary Administration‚ Performance Linked Incentive Scheme and Quality of Work Life” At NTPC Ltd. FARAKKA‚ WEST BENGAL Submitted in the Partial Fulfillment of “Master of Business Administration” SUBMITTED TO: SUBMITTED TO Ms. Pragya Sonam
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SIMPLE VERSUS MULTIPLE REGRESSION The difference between simple and multiple regression is similar to the difference between one way and factorial ANOVA. Like one-way ANOVA‚ simple regression analysis involves a single independent‚ or predictor variable and a single dependent‚ or outcome variable. This is the same number of variables used in a simple correlation analysis. The difference between a Pearson correlation coefficient and a simple regression analysis is that whereas the correlation does
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Simple Linear Regression Model 1. The following data represent the number of flash drives sold per day at a local computer shop and their prices. | Price (x) | Units Sold (y) | | $34 | 3 | | 36 | 4 | | 32 | 6 | | 35 | 5 | | 30 | 9 | | 38 | 2 | | 40 | 1 | | a. Develop as scatter diagram for these data. b. What does the scatter diagram indicate about the relationship between the two variables? c. Develop the estimated regression equation and explain what the
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STATISTICS FOR MGT DECISIONS FINAL EXAMINATION Forecasting – Simple Linear Regression Applications Interpretation and Use of Computer Output (Results) NAME SECTION A – REGRESSION ANALYSIS AND FORECASTING 1) The management of an international hotel chain is in the process of evaluating the possible sites for a new unit on a beach resort. As part of the analysis‚ the management is interested in evaluating the relationship between the distance of a hotel from the beach and the hotel’s
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difficulty in breathing for those around the scent. • The layout‚ maintenance and cleanliness of the customer areas - Committing strict hygiene standards. - Following critical standards for raw and finished product quality‚ cleanliness and sanitation. - Adhering to restaurant performance standards for crew stations and as per shift manager leadership - Washing your hands a minimum of once every hour - False nails are permitted to be worn
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Emotional Intelligence is a Better Than a Higher IQ Emotional intelligence is one of the best predictors of success. In fact‚ many studies show that emotional intelligence is a better indicator to success than a higher IQ (intelligence quotient). Take for instance Richard Branson who is dyslexic who couldn’t read and write as well as his other classmates in school‚ but he became one of the richest men in the world. Why is that? There are several reasons. But the main reason why emotional
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of traits that enable a successful future‚ the specific ones detailed in this paper are the Intelligence Quotient (I.Q.)‚ Emotional Intelligence (commonly referred to as E.Q.)‚ and Grit (defined as perservance for long term goals.). Intelligence Quotient The History and Use of I.Q. tests Alfred Binet was the creator of the very first widely used intelligence test after being asked by the French Ministry in 1904 to find a way to identify slow
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their functions‚ duties and responsibilities. The strategies that they use play a very crucial role in the attaining higher goals. Many components come into consideration when we take the role of the teacher closely. The teachers’ performance for a large part is determined by his/her personality. For this‚ Intelligence-that of IQ and Emotional- EQ are very useful sources of information. An intelligence quotient‚ or IQ‚ is a score derived from
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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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