Course Home - Course Project | | Print This Page | Course Project: AJ DAVIS DEPARTMENT STORES Introduction | Project Part A: Exploratory Data Analysis | Project Part A: Grading Rubric | Project Part B: Hypothesis Testing and Confidence Intervals | Project Part B: Grading Rubric | Project Part C: Regression and Correlation Analysis | Project Part C: Grading Rubric | | Introduction | | AJ DAVIS is a department store chain‚ which has many credit customers and wants to find out more information
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GM533 Course Project – Case 32 Executive Summary: The purpose of this analysis is to assist the Quick Stab Collection Agency (QSCA) in determining if the amount or size of a bill collection is directly related to the number of days the bill is late. In order to support the validity of this relationship‚ a statistical analysis on the data provided will support the relationship with 95% confidence. These findings will give us a better understanding of the QSCA’s business and provide key insights
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Part a1 Data were collected from 430 undergraduate college students for the purpose of examining the relationship between student personality characteristics and their preference for personality styles in their lecturers. Table 1 below presents a summary of the data collected. Of the 430 subjects for whom data was attempted‚ with 5 subjects providing no data‚ Of the 425 subjects included in data analysis‚ 307 were female‚ 117 were male‚ and 1 failed to indicate their gender. With the exception of
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The T-Distribution and T-Test “In probability and statistics‚ Student ’s t-distribution (or simply the t-distribution) is a continuous probability distribution that arises when estimating the mean of a normally distributed population in situations where the sample size is small” (Narasimhan ‚ 1996). Similar to the normal distribution‚ the t-distribution is symmetric and bell-shaped‚ but has heavier tails‚ meaning that it is more likely to produce values far from its mean. This makes the t-distribution
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Case Problem: Par‚ Inc. Section I: Summary Par‚ Inc.‚ a major manufacturer of golf equipment believes that a cut-resistant‚ longer lasting golf ball could increase their market share. In addition to the requirement that the ball be longer lasting‚ they wanted to ensure that the new coating would not reduce driving distances‚ and would be comparable to the current product. Section II: Relevant Statistical Results Statistic Current Model New Model Sample Mean 270.275 267.500 Standard Error 1
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Student Registration number N0433493 Name Harpreet Singh Dulai Introduction Statistics are collection of samples from raw data‚ which enable users to understand and interpret quantitative data in order to draw up conclusions and create future predictions. (Valerie J.Easton & John H.McColl) One beneficial programme has been created in order to simplify sampling through large amounts of data. This can be founded through computer packages. The computer package that has been implemented is SPSS
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GDP % Change Comparisons The descriptive statistics below show the % change in both countries annual GDP figures‚ starting in 1980 up to 2009‚ as seen in Figure 1. This is an example of continuous data‚ which is data that can take on an infinite number of different values. All data is different on an annual basis‚ this therefore makes all data for both countries ungrouped. (Source – IMF Statistics World Economic Outlook Database‚ October 2008). Statistics UK USA Number of entries 30 30
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Statistics for Management Unit 1 Unit 1 Introduction Structure: 1.1 Introduction to Statistics Learning objectives Importance of Statistics in modern business environment 1.2 Definition of Statistics 1.3 Scope and Applications of Statistics 1.4 Characteristics of Statistics 1.5 Functions of Statistics 1.6 Limitations of Statistics 1.7 Statistical Softwares 1.8 Summary 1.9 Terminal Questions 1.10 Answers to SAQs and TQs Answers to Self Assessment Questions Answers to Terminal
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BANDA National Consultants in Information System and Agricultural Statistics FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Lilongwe‚ April 2011 ACKNOWLEDGEMENTS The researcher would like to thank the Food and Agriculture Organisation of the United Nations (FAO) for offering him the opportunity of carrying out this important assignment and the Division of Agricultural Statistics of the National Statistical Office (NSO) for the technical support. The
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Sweetening Statistics Sandeep Agrawal Professor Dr. M. Reza Zomorrodian MAT300 March 12‚ 2013 Abstract The following assessment investigates the practices involved in this semester’s statistical M&M evaluation. The paper initially describes the individual random samples taken and then combined into the class’ data set. Then the totals‚ their proportions‚ and some other descriptive statistics are detailed before examining the confidence intervals for the proportions. The next
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