QUANTITATIVE METHODS - STATISTICS ------------------------------------------------- (SUBJECT CODE: STA1114) ------------------------------------------------- Instructions to Students: 1. Assignment questions consist of: * Question One - 25% * Question Two - 25% 2. Assignment question must be combined into ONE (1) booklet‚ attached with “Assignment Submission Form” as the front cover‚ enclosed with the “Marking Criteria.” typed with double spacing
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Week 4 Exercises Chapter 5 – Section 1. Question 5 To perform a certain type of blood analysis‚ lab technicians must perform two procedures. The first procedure requires either one or two separate steps‚ and the second procedure requires either one‚ two‚ or three steps. a. List the experimental outcomes associated with performing the blood analysis. Answer: There are two procedures that a lab technician must perform. The first procedure requires either one or two separate steps‚ which could be named
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Statistics 1 Business Statistics LaSaundra H. – Lancaster BUS 308 Statistics for Managers Instructor Nicole Rodieck 3/2/2014 Statistics 2 When we hear about business statistics‚ when think about the decisions that a manager makes to help make his/her business successful. But do we really know what it takes to run a business on a statistical level? While some may think that business statistics is too much work because it entails a detailed decision making process
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Official Statistics on crime are often likened to the ¡§tip of an Iceberg¡¨. Critically assess this assertion in light of the ¡§dark figure¡¨ of crime and any new forms of data that can provide a clearer picture of the true extent of crime. Crime is continuously changing in its definition in people¡¦s perceptions with no complex classification being universally accepted. This forms the basis of the problems faced when attempting to count crime‚ who determines what crime is; the government of
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EXERCISE IN STATISTICS Below are hypothetical data. (1) Organize them in bivariate tables to answer the problems below. Determine the statistics to use for each. 1. Are sex and occupation associated? 2. Are age and income correlated? 3. Are educational attainment and sex associated? 4. Are civil status and occupation associated? 5. Are occupation and income related N>E> you may use data transformation (from interval data to nominal data) Respondent No. Age Sex Civil Status Educational attainment
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Standardized description of index numbers for application in generic index computation software modules 1 Photis Stavropoulos1‚ Georges Pongas2‚ Spyros Liapis1‚ George Petrakos1‚ Tonia Ieromnimon1 Agilis S.A. Statistics and Informatics‚ e-mail: Photis.Stavropoulos@agilis-sa.gr‚ Spyros.Liapis@agilis-sa.gr‚ George.Petrakos@agilis-sa.gr‚ Tonia.Ieromnimon@agilis-sa.gr 2 EUROSTAT‚ e-mail: Georges.Pongas@ec.europa.eu Abstract The aim of this paper is to present a scheme for the description of index numbers
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Bibliography: ← Sharma K Suresh‚ Nursing research & statistics‚ second edition‚ Published by Elsevier‚ Page no.61-65 ← Burns‚ N‚ & Grove‚S.K‚ The practice of nursing research‚ 5th edition‚ Published by Elsevier Saunders‚ Page no.30-34 [pic]
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Muli‚ Laurah N. BSMA 2C Table 1 shows the descriptive statistics about the 74 models of automobiles released in the year 1978‚ these include the automobiles’ price‚ mileage‚ repair record‚ headroom‚ trunk space‚ weight‚ length‚ turn circle‚ displacement and the gear ratio with its corresponding results. In terms of automobiles’ price‚ it ranges to $3‚291.00 up to $15‚906.00 for the period of the said year. Its average price is $6‚165.26 with a standard deviation of $2‚949.50. It can be seen
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QUESTION 1 The managing partner for Westwood One Investment Managers Inc. gave a public seminar in which she discussed a number of issues‚ including investment risk analysis. In that seminar‚ she reminded people that the coefficient of variation can often be used as a measure of risk of an investment. To demonstrate her point of view‚ she used two hypothetical stocks as examples. She let x equal the change in assets for a $1‚000.00 investment in stock1 and y reflect the change in assets for a
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following table (see sheet CORRELATION) | Shoe size | Height | Shoe size | 1 | | Height | 0.86434 | 1 | As we can see that the correlation coefficient R=0.86434 is positive and close to 1‚ it suggests that there is a strong positive relationship between the shoe size and the height. Next‚ let’s formulate the following data (see SHOW SIZE DATA) Using Excel to get the following descriptive statistics for both variables:
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