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Preface. I. THE R LANGUAGE. 1. Basics of R.1.1 What is R?1.2 Installing R.1.3 R Documentation. 1.4 Basics. 1.5 Getting Help. 1.6 Data Entry. 1.7 Tidying Up. 1.8 Saving and Retrieving the Workspace. 2. Summarising Statistical Data. 2.1 Measures of Central Tendency. 2.2 Measures of Dispersion. 2.3 Overall Summary Statistics. 2.4 Programming in R.3. Graphical Displays. 3.1 Boxplots. 3.2 Histograms. 3.3 Stem and Leaf. 3.4 Scatter Plots. 3.5 Graphical Display vs Summary Statistics. II: FUNDAMENTALS OF PROBABILITY. 4. Basics. 4.1 Experiments, Sample Spaces and Events. 4.2 Classical Approach to Probability. 4.3 Permutations and Combinations. 4.4 The Birthday Problem. 4.5 Balls and Bins. 4.6 Relative Frequency Approach to Probability. 4.7 Simulating Probabilities. 5. Rules of Probability. 5.1 Probability and Sets. 5.2 Mutually Exclusive Events. 5.3 Complementary Events. 5.4 Axioms of Probability. 5.5 Properties of Probability. 6. Conditional Probability. 6.1 Multiplication Law of Probability. 6.2 Independent Events. 6.3 The Intel Fiasco. 6.4 Law of Total Probability. 6.5 Trees. 7. Posterior Probability and Bayes. 7.1 Bayes' Rule. 7.2 Hardware Fault Diagnosis. 7.3 Machine Learning. 7.4 The Fundamental Equation of Machine Translation. 8. Reliability. 8.1 Series Systems. 8.2 Parallel Systems. 8.3 Reliability of a System. 8.4 Series-Parallel Systems. 8.5 The Design of Systems. 8.6 The General System. III: DISCRETE DISTRIBUTIONS. 9. Discrete Distributions. 9.1 Discrete Random Variables. 9.2 Cumulative Distribution Function. 9.3 Some Simple Discrete Distributions. 9.4 Benford's Law. 9.5 Summarising Random Variables: Expectation. 9.6 Properties of Expectations. 9.7 Simulating Expectation for Discrete Random Variables. 10. The Geometric Distribution. 10.1 Geometric Random Variables. 10.2 Cumulative Distribution Function. 10.3 The Quantile Function. 10.4 Geometric Expectations. 10.5 Simulating Geometric Probabilities and Expectations. 10.6 Amnesia. 10.7 Project. 11. The Binomial Distribution. 11.1 Binomial Probabilities. 11.2 Binomial Random Variables. 11.3 Cumulative Distribution Function. 11.4 The Quantile Function. 11.5 Machine Learning and the Binomial Distribution. 11.6 Binomial Expectations. 11.7 Simulating Binomial Probabilities and Expectations. 11.8 Project. 12. The Hypergeometric Distribution. 12.1 Hypergeometric Random Variables. 12.2 Cumulative Distribution Function. 12.3 The Lottery. 12.4 Hypergeometric or Binomial?.12.5 Project. 13. The Poisson Distribution. 13.1 Death by Horse Kick. 13.2 Limiting Binomial Distribution. 13.3 Random Events in Time and Space. 13.4 Probability Density Function. 13.5 Cumulative Distribution Function. 13.6 The Quantile Function. 13.7 Estimating Software Reliability. 13.8 Modelling Defects in Integrated Circuits. 13.9 Simulating Poisson Probabilities. 13.10Projects. 14. Sampling Inspection Schemes. 14.1 Introduction. 14.2 Single Sampling Inspection Schemes. 14.3 Acceptance Probabilities. 14.4 Simulating Sampling Inspections Schemes. 14.5 Operating Characteristic Curve. 14.6 Producer's and Consumer's Risks. 14.7 Design of Sampling Schemes. 14.8 Rectifying Sampling Inspection Schemes. 14.9 Average Outgoing Quality. 14.10Double Sampling Inspection Schemes. 14.11Average Sample Size. 14.12Single vs Double Schemes. 14.13Project. IV. CONTINUOUS DISTRIBUTIONS. 15. Continuous Distributions. 15.1 Continuous Random Variables. 15.2 Probability Density Function. 15.3 Cumulative Distribution Function. 15.4 The Uniform Distribution. 15.5 Expectation of a Continuous Random Variable. 15.6 Simulating Continuous Variables. 16. The Exponential Distribution. 16.1 Probability Density Function Of Waiting Times. 16.2 Cumulative Distribution Function. 16.3 Quantiles. 16.4 Exponential Expectations. 16.5 Simulating the Exponential Distribution. 16.6 Amnesia. 16.7 Simulating Markov. 17. Applications of the Exponential Distribution. 17.1 Failure Rate and Reliability. 17.2 Modelling Response Times. 17.3 Queue Lengths. 17.4 Average Response Time. 17.5 Extensions of the M/M/1 queue. 18. The Normal Distribution. 18.1 The Normal Probability Density Function. 18.2 The Cumulative Distribution Function. 18.3 Quantiles. 18.4 The Standard Normal Distribution. 18.5 Achieving Normality; Limiting Distributions. 18.6 Project in R.19. Process Control. 19.1 Control Charts. 19.2 Cusum Charts. 19.3 Charts for Defective Rates. 19.4 Project. V. TAILING OFF. 20. Markov and Chebyshev Bound. 20.1 Markov's Inequality. 20.2 Algorithm Run-Time. 20.3 Chebyshev's Inequality. Appendix 1: Variance derivations. Appendix 2: Binomial approximation to the hypergeometric. Appendix 3:. Standard Normal Tables.

What this book covers -- some applications of portable computers -- 1. Which computer? -- Developing a selection methodology -- computers v. terminals -- portables v. hand-helds v. transportables v. plug-ins -- the ideal portable -- what to look for in a portable -- Summary — 20 portables on the market -- 2. The HX-20 -- to the HX-20 -- the hardware components -- environmental considerations -- documentation and technical support -- warranty -- prices -- 3. HX-20 BASIC -- Why and how to learn BASIC -- what to get in HX-20 BASIC -- what HX-20 BASIC is missing -- 4. Using and writing BASIC programs -- Finding and entering BASIC programs -- tips on converting programs written for other machines -- programming tips -- some BASIC programs and subroutines -- 5. The 6301 microprocessor -- Basic concepts -- to machine architecture -- programming the 6301 -- interrupts -- the real-time clock -- 6. Assembly language -- Why use machine/assembly language? an assembler -- other assemblers -- storing machine code into memory -- using the Monitor as a learning tool -- assembly language coding hints -- sample program -- 7. Forth -- An introduction to the language -- description of HCCS Forth -- 8. Communications -- The why of data communications -- The how of data communications -- 9. Word processing -- Word processing on the HX-20 -- Ffosswriter -- SkiWriter -- Intext -- Other WP/Editing programs -- 10. Inventory/stock tracking -- What to look for in an inventory system -- available inventory software -- bar code readers and software -- technical information on bar codes -- bar code printing program -- 11. Software and systems -- Packaged software and systems from the US, UK and Australia -- 12. Peripherals -- Different peripherals available: what they do, how they connect, where to get them -- 13. Operating tips -- Appendix A: Vendor List -- Where to go to buy software, hardware, supplies -- Appendix B: Where to go for more information Magazines -- Magazines, newsletters, user's groups -- Appendix C: Portable Computer Manufacturers -- Appendix D: System Reference -- Appendix E: Computer Terminology -- Glossary of the familiar but different, as well as the totally unfamiliar.

1. The prehistory of the computer industry, 1880-1939 -- 2. The advent of the mainframe digital computer, 1940-1957 -- 3. Broadening scale and scope of the mainframe computer industry, 1957-1965 -- 4. The industry's supercomputing and minicomputing sectors, 1957-1975 -- 5. The rise of software as a service, product, business, and industry, 1958-1975 -- 6. Infrastructure for long-term change, 1962-1975 -- 7. The personal computer and PC software, 1975-1990 -- 8. The computer networking revolution and the computer industry, 1990-2004 -- Conclusion: looking backwards and looking ahead

Joachim R. HÖFLICH entwickelt eine Theorie der Institutionalisierung computervermittelter Kommunikation, die den Nutzer und seine Erwartungen in den Mittelpunkt stellt. Nutzungsepisoden richten sich demnach an "Computerrahmen" aus, die Regeln und Routinen enthalten, wann und in welcher Form ein Medium und seine Dienste zu verwenden ist. Je nach Verwendungszweck (Information, öffentliche Diskussion oder interpersonale Kommunikation) strukturieren unterschiedliche Erwartungen das Verhalten der Nutzer. Am Beispiel der Zeitungsmailbox "Augsburg Newsline", die HÖFLICH Mitte der 90er Jahre mit verschiedenen methodischen Ansätzen untersucht hat, demonstriert er die Brauchbarkeit des begrifflichen Bezugsrahmens für die empirische Forschung. Das Buch stellt somit einen wertvollen Beitrag zur sozial- und kommunikationswissenschaftlichen Analyse der Online-Medien dar.

This veto message from Governor Nikki Haley vetoes R.201, H.5024, a bill that would allow the Board of the Denmark-Olar School District No.2 to assess a capital property tax millage without voter referendum.