yields for the past seven and 30 days. Before calling the money market fund managers to obtain additional data, Lisa decided to do some preliminary analysis of the data already collected. Managerial Report 1. Use appropriate descriptive statistics to summarize the data on assets and yields for the money market funds. 2. Develop a 95% confidence interval estimate of the mean assets, mean 7-day yield, and mean 30-day yield for the population of money market funds. Provide a managerial interpretation
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Used: 4 Clustering: 4 Segment Profile: 5 Regression: 7 Decision Tree: 8 Model Comparison: 9 Knowledge, interpretation and conclusion 9 Executive Summary: This summary presents findings of the data mining techniques used in the Crime Statistics by City dataset. The aim of the project is to enhance the knowledge and hands on experience on EM tool and to make appropriate projections about crime rates in cities. Project Goal: Our goal is to determine the similarities between cities and
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Chapter 5 Sample questions 1. Time-series forecasting models: a. | are useful whenever changes occur rapidly and wildly | b. | are more effective in making long-run forecasts than short-run forecasts | c. | are based solely on historical observations of the values of the variable being forecasted | d. | attempt to explain the underlying causal relationships which produce the observed outcome | e. | none of the above | 2. The forecasting technique which attempts to forecast short-run
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How could graphics and/or statistics be used to misrepresent data? Where have you seen this done? In the medial society, graphics and statistics are frequently used to prove (or disprove) theories related to illness and medications. However, the data may be misinterpreted based on an individual’s biased opinion if they are not willing to completely investigate all sides of an argument. This is most common when an individual has a personal, or monetary, interest in a cause. One thing that
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Application of Bootstrap method in spectrometric data analysis By XIAO Jiali, Jenny ( 0830300038) A Final Year Project thesis (STAT 4121; 3 Credits) submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Statistics at BNU-HKBU UNITED INTERNATIONAL COLLEGE December, 2011 DECLARATION I hereby declare that all the work done in this Project is of my independent effort. I also certify that I have never submitted the idea and product of this Project for
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Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. There are variety of different types of statistics, hard statistics are numerical data that can not be manipulated, soft statistics are numerical data that can be manipulated, official statistics are produced by formal institutions whilst unofficial are carried out by informal institutions. By definition, statistical data is quantative data which increases its reliability. Using Statistics
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don't know which are the strongest. An intelligent correlation analysis can lead to a greater understanding of your data. Techniques in Determining Correlation There are several different correlation techniques. The Survey System's optional Statistics Moduleincludes the most common type, called the Pearson or product-moment correlation. The module also includes a variation on this type called partial correlation. The latter is useful when you want to look at the relationship between two variables
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Chapter 3 Methodology Historical Research Design purpose is to collect, verify, synthesize evidence to establish facts that defend or refute your hypothesis. It uses primary sources, secondary sources, and lots of qualitative data sources such as logs, diaries, official records, reports, etc. The limitation is that the sources must be both authentic and valid. When we think of research, we often think of a laboratory or classroom where two or more groups receive different treatments or alternative
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Introduction to Multiple Regression Dale E. Berger Claremont Graduate University http://wise.cgu.edu Overview Multiple regression is a flexible method of data analysis that may be appropriate whenever a quantitative variable (the dependent or criterion variable) is to be examined in relationship to any other factors (expressed as independent or predictor variables). Relationships may be nonlinear, independent variables may be quantitative or qualitative, and one can
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SAMPLING: In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. The sampling process comprises several stages: * Defining the population of concern
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