1 Secondary data analysis: an introduction All data are the consequence of one person asking questions of someone else. (Jacob 1984: 43) This chapter introduces the field of secondary data analysis. It begins by considering what it is that we mean by secondary data analysis‚ before describing the type of data that might lend itself to secondary analysis and the ways in which the approach has developed as a research tool in social and educational research. The second part of the chapter considers
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Text Problem Sets A1. (Bond valuation) A $1‚000 face value bond has a remaining maturity of 10 years and a required return of 9%. The bond’s coupon rate is 7.4%. What is the fair value of this bond? Number of years (N) = 10‚ future value (FV) = 1000‚ interest rate (I/YR) = 9 0.074 * 1000 = 74 = PMT or annual payment‚ I then pressed CPT on my financial calculator to compute the price of the bond and then pressed PV or present value. The fair value of the bond is $897.32. Using Cash Flow of
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Problem Set 4 1. What determines whether a financial asset is included in the M1 money supply? Why are interest-earning checkable deposits included in M1‚ whereas interest-earning savings accounts and Treasury bills are not? a. Any financial asset that can be easily changed into physical money is included in the M1 money supply. b. Because checkable deposits are easily changed into physical money‚ they are included in M1; however‚ savings accounts and Treasury bills cannot be‚ due to the fact that
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CACL 2014 Case studies and problem sets Problem Set 1 The following problems and questions should be answered after you have read Chapters 1 and 2. 1. GML is a public company. Its shares are listed for quotation on the ASX. What does it mean to say that a company is listed? Are all public companies listed on the ASX? See [¶1-120]‚ [¶1-140] and key terms [¶1-500] If a public company is listed on the ASX‚ members of the public can buy and sell securities (such as shares) issued by the company
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Analysis of Data The researcher distributed 150 questionnaires to people and students from different schools. After collecting the papers‚ each was tallied one by one. The questionnaire has a total of Seven(7) questions each with a different set and amount of answers. One hundred(100) questionnaires were distributed in person while the Fifty(50) were answered online. The results of the survey will be explained by percentage and shown through pie chart as well along with a slight conclusion for
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Travis Kellenberger AGEC 700 Problem Set #3 2) The demand curve for a product is given by Qdx = 1‚200-3Px- .01Pz‚ where Pz = $300. a) What is the own price elasticity of demand when Px = $140? Is demand elastic or inelastic at this price? What would happen to the firm’s revenue if it decided to charge a price below $140? At the given prices‚ quantity demanded is 750 units: Qdx = 1‚200- (3 *140) -.1 (300) = 750. -140/750=-.56; demand is inelastic at this price point and you would be decreasing
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Running head: SET THE STAGE FOR SUCCESS Gabby Gonzalez July 1‚ 2009 GEN/200 Abstract Everyone has a goal to meet‚ but sometimes they do not know the right way to act upon their own goals. Some could be clueless to many strategies that may help someone succeed their goals. However‚ four excellent strategies to succeed would be goal-setting‚ vision‚ time management‚ and organization. Learning these strategies in procedure will help anyone that is dedicated accomplish their goal to succeed
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CUSTOMER DATA In the term of customer data‚ technology now day give a big role to evaluate the concepts by the overall to moving ownership of the customer when they are away from the individual departments and different it at the enterprise level. In the customer relationship management concept‚ individual that in the each department has responsible for the customer. The success factor for Customer Relationship Management (CRM) is by deploying technology that provides various levels of data access
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1. Data mart definition A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. Data marts are small slices of the data warehouse. Whereas data warehouses have an enterprise-wide depth‚ the information in data marts pertains to a single department. In some deployments‚ each department or business unit is considered the owner of its data
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There are many key differences that are important to understand between data oriented and process oriented approaches to designing a new system. The system focus of the data views and process views are entirely different. The process view focuses on what the systems supposed to do and when‚ while the data view has a focus on what the system needs to operate. Another noteworthy difference that distinguishes the two views is the design stability. The design stability of a process view is a more limited
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