Professor Faleh Alshamari Submitted by: Wajeha Sultan Final Project Hashing: Open and Closed Hashing Definition: Hashing index is used to retrieve data. We can find‚ insert and delete data by using the hashing index and the idea is to map keys of a given file. A hash means a 1 to 1 relationship between data. This is a common data type in languages. A hash algorithm is a way to take an input and always have the same output‚ otherwise known as a 1 to 1 function. An ideal hash function is
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Problem Set 1 1. (Star Wars) Real GDP = 461.0(214.5/60.6) = 1‚631.76 (E.T.) Real GDP = 399.9(214.5/96.5) = 888.90 (Titanic) Real GDP = 600.8(214.5/160.5) = 802.94 (Shrek 2) Real GDP = 437.2(214.5/188.9) = 496.45 (Avatar) Real GDP = 760.5(214.5/214.5) = 760.5 Real GDP in Order of Largest to Smallest Movies Nominal Box Office Receipts (millions) CPI in Year Released Real Box Office Receipts (millions) Star Wars (1977) 461.0 60.6 1‚631.76 E.T. The Extra-Terrestrial (1982) 399.9 96.5 888.90 Titanic
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study: MBA Course Title: Marketing Research Course code: MBA 763 Assignment: Secondary Data Mat Number: 74168 Name: Abiona Timothy Olufemi What is Data Data is a collection of facts‚ such as numbers‚ words‚ measurements‚ observations or even just descriptions of things. 1.Information in raw or unorganized form (such as alphabets‚ numbers‚ or symbols) that refer to‚ or represent‚ conditions‚ ideas‚ or objects. Data is limitless and present everywhere in the universe. See also information and knowledge
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Introduction: Data analysis is an attempt by the researcher to summarize collected data either quantitative or qualitative. Generally‚ quantitative analysis is simply a way of measuring things but more specifically it can be considered as a systematic approach to investigations. In this approach numerical data is collected or the researcher transforms collected or observed data into numerical data. It is ideal for finding out when and where‚ who and what and any relationships and patterns between
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Chapter 4 Simple regression model Practice problems Use Chapter 4 Powerpoint question 4.1 to answer the following questions: 1. Report the Eveiw output for regression model . Please write down your fitted regression model. 2. Are the sign for consistent with your expectation‚ explain? 3. Hypothesize the sign of the coefficient and test your hypothesis at 5% significance level using t-table. 4. What percentage of variation in 30 year fixed mortgage rate is explained
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The methodology of this study is use Augmented Dickey Fuller (ADF) test statistic to determine whether the variables had been used are stationary or non-stationary. Vector Auto Regression (VAR) method is apply in this study. The advantages of VAR is time series can be exhibited at the same time. The VAR methodology is revises for autocorrelation and endogeneity parametrically using vector error correction model (VECM) specification. Base on Johansen (1988; 1995)‚ the benefit of VECM is that it prevents
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Problem Set 2 Name: __________________________________________ Problem Set 2 is to be completed by 11:59 p.m. (ET) on Monday of Module/Week 4. 1. The following table presents data for wages in the market for internet security professionals. (HINT: in the labor market the roles are reversed. Those who want to hire labor are the demanders. The workers enter the work force providing labor to the market place so they are the suppliers.) Wage Quantity Demanded Quantity Supplied $50‚000
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DATA COMPRESSION The word data is in general used to mean the information in digital form on which computer programs operate‚ and compression means a process of removing redundancy in the data. By ’compressing data’‚ we actually mean deriving techniques or‚ more specifically‚ designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms‚ including both compression and decompression. Data Compression
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Big Data Management: Possibilities and Challenges The term big data describes the volumes of data generated by an enterprise‚ including Web-browsing trails‚ point-of-sale data‚ ATM records‚ and other customer information generated within an organization (Levine‚ 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations‚
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DATA COLLECTION Business Statistics Math 122a DLSU-D Source: Elementary Statistics (Reyes‚ Saren) Methods of Data Collection 1. 2. 3. 4. 5. DIRECT or INTERVIEW METHOD INDIRECT or QUESTIONNAIRE METHOD REGISTRATION METHOD OBSERVATION METHOD EXPERIMENT METHOD DIRECT or INTERVIEW Use at least two (2) persons – an INTERVIEWER & an INTERVIEWEE/S – exchanging information. Gives us precise & consistent information because clarifications can be made. Questions not fully understood by the respondent
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