without missing responses ..................................................................... 7 Section 2: Frequencies without descriptive & with missing responses ...................................... 8 Section 3: Frequencies with descriptive statistics ...................................................................... 9 Ordinal data ............................................................................................................................. 9 Interval/Ratio data ..........
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important Greek financial institution. The data we gathered cover the period from 1 January 2008 until 31 December 2010‚ and obviously the frequency of the data is daily. Table 1 provides a multitude of informative key descriptive statistics. Table 1. Descriptive statistics of the 5 Year CDS spreads of (i) a sovereign‚ Greece‚ and (ii) a financial institution‚ Alpha Bank. All numbers are in basis points. | Spread_Greece | Spread_AlphaBank | Mean | 298.419 | 468.322 | Median | 162.36 | 445.32
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Brief Introduction: AJ Davis is a department store chain‚ which has many credit customers and want to find out more information about these customers. AJ Davis has complied a sample of 50 credit customers with data selected in the following variables: Location‚ Income (in $1‚000’s)‚ Size (Number of people living in the household)‚ Years (number of years the customer has lived in the current location)‚ and Credit Balance (customers current credit card balance on the store’s credit car‚ in $)
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960 | |0.01 |2.33 |2.575 | Part A. Single-Sample Inference 1. Test Statistic for the Population Mean ((): Large Sample Test H0: ( = (0 H1: ( ( (0 Test statistic: [pic]‚ where (0 = hypothesized value of ( Note that: Sample mean = [pic] Mean of the sample mean: E([pic]) = ( Standard error of [pic] = [pic] Example
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physics‚ social and others will run well if they are cited in a good mathematics framework. This circumstance stimulated me to attend faculty of mathematics and natural science. I choose statistics as my specialization even though at this time‚ there weren’t many people know about statistics and few students choose statistics as their specialization. I saw in several developed countries such as The Netherlands and Belgium‚ the mathematics degree-holders not only have many opportunities but also were cited
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Villanova University Villanova School of Business Department of Economics and Statistics Mat 1430 Business Statistics Dr. Michael W. Varano Spring 2013 Office: Bartley Hall 1008 All Sections Office Hours: TBA (and/or by appointment) Telephone: (610) 519-7799 e-mail: michael.varano@villanova.edu https://elearning.villanova.edu/webct/
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Home Work (Chapter One) 1. Define each of the following statistical terms: a. Descriptive statistics b. Statistical inference c. Population d. Sample 2. Explain whether each of the following represents a population or a sample. a. Number of goals scored by all teams of champion’s league. b. Cars owned by 200 families in Dammam. c. Monthly salaries of all employees of a company. d. Yield of tomatoes per ha for 20 plots of land. e
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Basic Business Statistics 11th Edition Chapter 1 Introduction and Data Collection Basic Business Statistics‚ 11e © 2009 Prentice-Hall‚ Inc. Chap 1-1 Learning Objectives In this chapter you learn: How Statistics is used in business The sources of data used in business The types of data used in business The basics of Microsoft Excel The basics of Minitab Basic Business Statistics‚ 11e © 2009 Prentice-Hall‚ Inc.. Chap 1-2 Why Learn Statistics? So you are
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employees (c) Preference for beverages and (d) Amount spent on drinks. This case study is used: (1) To understand the concept and practical applications of scales of measurement; (2) To discuss the implications of scales in Quantitative Methods/Statistics for Management. This case study is useful for understanding ‘measures of central tendencies •
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(That is‚ does the average cycle length under these conditions differ significantly from 24 hours?) (a) Use the steps of hypothesis testing. (b) Sketch the distributions involved‚ (c) Explain your answer to someone who has never taken a course in statistics. x | | | | | | | | | | | 25 | 0 | 0 | | | | | | | | 27 | 2 | 4 | | | | | | | | 25 | 0 | 0 | | | | | | | | 23 | -2 | 4 | | | | | | | | 24 | -1 | 1 | | | | | | | | 25 | 0 | 0 | | | | | |
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