Statistics for Health Care Management and Administration : Working with Excel. by Kros, John F., ProQuest Ebook Subscriptions

Table of Contents: “…6.2 The Distribution of Frequencies -- Exercises for Section 6.2 -- 6.3 The Sampling Distribution of the Mean -- Exercises for Section 6.3 -- 6.4 Mean and Standard Deviation of a Discrete Numerical Variable -- Exercises for Section 6.4 -- 6.5 The Distribution of a Proportion -- Exercises for Section 6.5 -- 6.6 The t Distribution -- Exercises for Section 6.6 -- Key Terms -- Part 2 -- Chapter 7 Confidence Limits and Hypothesis Testing -- 7.1 What Is a Confidence Interval? …”
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Transact-SQL cookbook / by Špetič, Aleš, Safari Books Online

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Investing demystified : how to invest without speculation and sleepless nights / by Kroijer, Lars, Safari Books Online

Table of Contents: “…; Expected returns: no promises, but expect 4â#x80;#x93;5% after inflation; Larsâ#x80;#x99;s predictions; In summary; Chapter 6: The risk of equity markets; Understanding the risk you take to get returns; The standard deviation; You can lose a lot!; Donâ#x80;#x99;t assume that markets always bounce back; Diversification and the false sense of security; Risk rethought; Chapter 7: Adding other government and corporate bonds…”
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Probability and stochastic processes : a friendly introduction for electrical and computer engineers / by Yates, Roy D., Goodman, David J., 1939-, Safari Books Online

Table of Contents: “…1.7 MatlabProblems; Chapter 2: Sequential Experiments; 2.1 Tree Diagrams; 2.2 Counting Methods; 2.3 Independent Trials; 2.4 Reliability Analysis; 2.5 Matlab; Problems; Chapter 3: Discrete Random Variables; 3.1 Definitions; 3.2 Probability Mass Function; 3.3 Families of Discrete Random Variables; 3.4 Cumulative Distribution Function (CDF); 3.5 Averages and Expected Value; 3.6 Functions of a Random Variable; 3.7 Expected Value of a Derived Random Variable; 3.8 Variance and Standard Deviation; 3.9 Matlab; Problems; Chapter 4: Continuous Random Variables; 4.1 Continuous Sample Space.…”
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Probabilistic design for optimization and robustness for engineers / by Dodson, Bryan, 1962-, Safari Books Online

Table of Contents: “…5.3 Limitations of first-order Taylor series approximation for variance5.4 Effect of non-normal input distributions; 5.5 Nonconstant input standard deviation; 5.6 Summary; Exercises; 6 Desirability; 6.1 Introduction; 6.2 Requirements and scorecards; 6.2.1 Types of requirements; 6.2.2 Design scorecard; 6.3 Desirability-single requirement; 6.3.1 Desirability-one-sided limit; 6.3.2 Desirability-two-sided limit; 6.3.3 Desirability-nonlinear function; 6.4 Desirability-multiple requirements; 6.4.1 Maxi-min total desirability index; 6.5 Desirability-accounting for variation.…”
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Risk neutral pricing and financial mathematics : a primer / by Knopf, Peter M., Teall, John L., 1958-, Safari Books Online

Table of Contents: “…2.3.1 Physical and Risk-Neutral ProbabilitiesIllustration: Probability Space; 2.3.2 Random Variables; Illustration: Discrete Random Variables; 2.4 Statistics and Metrics; 2.4.1 Metrics in Discrete Spaces; 2.4.1.1 Expected Value, Variance, and Standard Deviation; Illustration; 2.4.1.2 Co-movement Statistics; 2.4.2 Metrics in Continuous Spaces; Illustration: Distributions in a Continuous Space; 2.4.2.1 Expected Value and Variance; 2.5 Conditional Probability; Illustration: Drawing a Spade; 2.5.1 Bayes Theorem; Illustration: Detecting Illegal Insider Trading; 2.5.2 Independent Random Variables.…”
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Risk Modelling in General Insurance : From Principles to Practice. by Gray, Roger J., PALCI EBSCO books

Table of Contents: “…3.6.2 Asymptotic approximations3.7 Statistics for compound distributions; 3.8 The individual risk model; 3.8.1 The mean and variance for the individual risk model; 3.8.2 The distribution function and moment generating function for the individual risk model; 3.8.3 Approximations for the individual risk model; Exercises; 4: Model based pricing -- setting premiums; 4.1 Premium calculation principles; 4.1.1 The expected value principle (EVP); 4.1.2 The standard deviation principle (SDP); 4.1.3 The variance principle (VP); 4.1.4 The quantile principle (QP); 4.1.5 The zero utility principle (ZUP).…”
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Probability and random variables for electrical engineering : probability : measurement of uncertainty / by Catak, Muammer, Allahviranloo, Tofigh, Pedrycz, Witold, 1953-, SpringerLink (Online service)

Table of Contents: “…4.5.5 Sum of Two Statistically Independent Continuous Random Variables, Z=X+Y -- 4.5.6 Sum of Two Statistically Independent Discrete Random Variables, Z=X+Y -- 4.5.7 Z=XY -- 4.5.8 Z=XY -- 4.5.9 Central Limit Theorem -- 4.6 Problems -- 5 Statistical Analysis of Random Variables -- 5.1 Statistical Analysis of One Random Variable -- 5.1.1 Expected Value and Mean -- 5.1.2 Variance and Standard Deviation -- 5.2 Moment Generating Functions -- 5.2.1 Maclaurin Series -- 5.2.2 Characteristic Function -- 5.3 Statistical Analysis of Multiple Random Variables -- 5.3.1 Normalized Joint Moments…”
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Mastering . NET Machine Learning. by Dixon, Jamie, ProQuest Ebook Subscriptions

Table of Contents: “…-- Getting ready for machine learning -- Setting up Visual Studio -- Learning F♯ -- Third-party libraries -- Math.NET -- Accord.NET -- Numl -- Summary -- Chapter 2: AdventureWorks Regression -- Simple linear regression -- Setting up the environment -- Preparing the test data -- Standard deviation -- Pearson's Correlation -- Linear regression -- Math.NET -- Regression try 1 -- Regression try 2 -- Accord.NET -- Regression -- Regression evaluation using RSME -- Regression and the real world -- Regression against actual data -- AdventureWorks app -- Setting up the environment -- Updating the existing web project -- Implementing the regression -- Summary -- Chapter 3: More AdventureWorks Regression -- Introduction to multiple linear regression -- Intro example -- Keep adding x variables? …”
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The micro-world observed by ultra high-speed cameras we see what you don't see / by SpringerLink (Online service)

Table of Contents: “…2.3 Backside Illuminated ISIS; 3 Multi-framing Cameras with Silicon Image Sensors; 3.1 Macro-pixel Image Sensors; 3.2 Multi-collection-Gate Image Sensor; 4 3D-Stacked Image Sensors; 4.1 BSI to 3D-Stacking; 4.2 A Driver Circuit for Ultra High-Speed Imaging; 5 Time-Space Conversion; 6 Theoretical Highest Frame Rate of Silicon Image Sensors; 6.1 Acceleration of the Frame Rate; 6.2 Standard Deviation of Travel Time of Signal Electrons; 6.3 Identification of Parameters; 6.4 Comparison with Monte Carlo Simulations; 6.5 Generalization of the Theory; References…”
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Statistics with JMP : Graphs, Descriptive Statistics and Probability. by Goos, Peter, ProQuest Ebook Subscriptions

Table of Contents: “…3.1.3 Arithmetic mean -- 3.1.4 Geometric mean -- 3.2 Measures of relative location -- 3.2.1 Order statistics, quantiles, percentiles, deciles -- 3.2.2 Quartiles -- 3.3 Measures of variation or spread -- 3.3.1 Range -- 3.3.2 Interquartile range -- 3.3.3 Mean absolute deviation -- 3.3.4 Variance -- 3.3.5 Standard deviation -- 3.3.6 Coefficient of variation -- 3.3.7 Dispersion indices for nominal and ordinal variables -- 3.4 Measures of skewness -- 3.5 Kurtosis -- 3.6 Transformation and standardization of data -- 3.7 Box plots -- 3.8 Variability charts -- 3.9 Bivariate data -- 3.9.1 Covariance…”
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Essential Statistics for the Pharmaceutical Sciences. by Rowe, Philip, ProQuest Ebook Subscriptions

Table of Contents: “…3.1 Summarising data sets -- 3.2 Indicators of central tendency: Mean, median and mode -- 3.3 Describing variability -- standard deviation and coefficient of variation -- 3.4 Quartiles -- Another way to describe data -- 3.5 Describing ordinal data -- 3.6 Using computer packages to generate descriptive statistics -- 3.7 Chapter summary -- Chapter 4 The normal distribution -- 4.1 What is a normal distribution? …”
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Impact Analysis of Total Productive Maintenance : Critical Success Factors and Benefits / by Díaz-Reza, José Roberto, SpringerLink (Online service)

Table of Contents: “…TPM Benefits; 6.4.4 Rating Scale; 6.5 Questionnaire Application; 6.5.1 Sample; 6.5.2 Gathering Data; 6.6 Data Entry and Analysis; 6.7 Data Depuration; 6.7.1 Identification of Missing Values; 6.7.2 Identification of Outliers; 6.7.3 Standard Deviation Analysis; 6.7.4 Normal Distribution; 6.7.5 Homoscedastic Analysis; 6.7.6 Collinearity Analysis; 6.8 Descriptive Analysis.…”
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Emotion and Information Processing A Practical Approach. by Mohanty, Sachi Nandan, SpringerLink (Online service)

Table of Contents: “…Chapter 5: Effect on the Emotional Self-Esteem of Women with Reference to Make-Up -- 5.1 Introduction -- 5.2 Objectives of the Study -- 5.3 Literature Review -- 5.4 Conceptual Framework -- 5.5 Hypothesis -- 5.6 Methodology -- 5.7 Data Analysis -- 5.7.1 Finding out the Response Rate (Table 5.1) -- 5.7.2 Finding out Descriptive Statistics -- 5.7.2.1 Frequencies (Table 5.2) -- 5.7.3 Reliability -- 5.7.4 Using Mean and Standard Deviation -- 5.7.5 Hypothesis 1 -- 5.7.6 Using Correlation and Regression Analysis -- 5.7.7 Using Regression to Prove Hypothesis -- 5.7.8 Hypothesis 2…”
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Data Reduction and Analysis by Raghavender, U. S., PALCI EBSCO books

Table of Contents: “…3.5 Estimates Of Location3.6 Mean; 3.7 Median And Robust Estimates; 3.8 Estimates Of Variability; 3.9 Standard Deviation And Related Estimates; 3.10 Conclusions; Chapter 4 Data Science With Python And R; 4.1 Dataframe; 4.2 Reading The Files; 4.3 Indexing And Slicing; 4.4 Data Selection; 4.5 Function Mapping And Grouping; 4.6 Aggregate; 4.7 Conclusions; Chapter 5 Error Analysis; 5.1 Uncertainties In Data; 5.2 Propagation of Errors; 5.3 Conclusions; Chapter 6 Principal Component Analysis; 6.1 Preparing Our TB Data; 6.2 Using R For PCA; 6.3 Exploring Data Structure With K-Means Clustering…”
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Understanding and Applying Basic Statistical Methods Using R. by Wilcox, Rand R., ProQuest Ebook Subscriptions

Table of Contents: “…2.2.2 The Median -- 2.2.3 Sample Mean versus Sample Median -- 2.2.4 Trimmed Mean -- 2.2.5 R function mean, tmean, and median -- 2.3 Quartiles -- 2.3.1 R function idealf and summary -- 2.4 Measures of Variation -- 2.4.1 The Range -- 2.4.2 R function Range -- 2.4.3 Deviation Scores, Variance, and Standard Deviation -- 2.4.4 R Functions var and sd -- 2.4.5 The Interquartile Range -- 2.4.6 MAD and the Winsorized Variance -- 2.4.7 R Functions winvar, winsd, idealfIQR, and mad -- 2.5 Detecting Outliers -- 2.5.1 A Classic Outlier Detection Method -- 2.5.2 The Boxplot Rule -- 2.5.3 The MAD-Median Rule…”
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Bayesian Statistics : An Introduction. by Lee, Peter M., ProQuest Ebook Subscriptions

Table of Contents: “…1.3.4 The normal distribution -- 1.3.5 Mixed random variables -- 1.4 Several random variables -- 1.4.1 Two discrete random variables -- 1.4.2 Two continuous random variables -- 1.4.3 Bayes' Theorem for random variables -- 1.4.4 Example -- 1.4.5 One discrete variable and one continuous variable -- 1.4.6 Independent random variables -- 1.5 Means and variances -- 1.5.1 Expectations -- 1.5.2 The expectation of a sum and of a product -- 1.5.3 Variance, precision and standard deviation -- 1.5.4 Examples -- 1.5.5 Variance of a sum -- covariance and correlation…”
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The process of enterprise risk management / by Oh, Kok-Boon, PALCI EBSCO books

Table of Contents: “…Mean-Variance Space (Standard Deviation); 3.4.1. Volatility and Expected Returns; 3.4.1.1. …”
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Data Science The Executive Summary - a Technical Book for Non-Technical Professionals. by Cady, Field, ProQuest Ebook Subscriptions

Table of Contents: “…4.2 Outliers, Visualizations, and the Limits of Summary Statistics: A Picture Is Worth a Thousand Numbers -- 4.3 Experiments, Correlation, and Causality -- 4.4 Summarizing One Number -- 4.5 Key Properties to Assess: Central Tendency, Spread, and Heavy Tails -- 4.5.1 Measuring Central Tendency -- 4.5.1.1 Mean -- 4.5.1.2 Median -- 4.5.1.3 Mode -- 4.5.2 Measuring Spread -- 4.5.2.1 Standard Deviation -- 4.5.2.2 Percentiles -- 4.5.3 Advanced Material: Managing Heavy Tails -- 4.6 Summarizing Two Numbers: Correlations and Scatterplots -- 4.6.1 Correlations -- 4.6.1.1 Pearson Correlation…”
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Learning pandas / by Heydt, Michael, ProQuest Ebook Subscriptions

Table of Contents: “…Categorical values as an index -- CategoricalIndex -- Indexing by date and time using DatetimeIndex -- Indexing periods of time using PeriodIndex -- Working with Indexes -- Creating and using an index with a Series or DataFrame -- Selecting values using an index -- Moving data to and from the index -- Reindexing a pandas object -- Hierarchical indexing -- Summary -- Chapter 7: Categorical Data -- Configuring pandas -- Creating Categoricals -- Renaming categories -- Appending new categories -- Removing categories -- Removing unused categories -- Setting categories -- Descriptive information of a Categorical -- Munging school grades -- Summary -- Chapter 8: Numerical and Statistical Methods -- Configuring pandas -- Performing numerical methods on pandas objects -- Performing arithmetic on a DataFrame or Series -- Getting the counts of values -- Determining unique values (and their counts) -- Finding minimum and maximum values -- Locating the n-smallest and n-largest values -- Calculating accumulated values -- Performing statistical processes on pandas objects -- Retrieving summary descriptive statistics -- Measuring central tendency: mean, median, and mode -- Calculating the mean -- Finding the median -- Determining the mode -- Calculating variance and standard deviation -- Measuring variance -- Finding the standard deviation -- Determining covariance and correlation -- Calculating covariance -- Determining correlation -- Performing discretization and quantiling of data -- Calculating the rank of values -- Calculating the percent change at each sample of a series -- Performing moving-window operations -- Executing random sampling of data -- Summary -- Chapter 9: Accessing Data -- Configuring pandas -- Working with CSV and text/tabular format data -- Examining the sample CSV data set -- Reading a CSV file into a DataFrame.…”
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