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 Privitera, Gregory J., author.
 Second edition.  Thousand Oaks, California : SAGE Publications, Inc., [2019]
 Description
 Book — xli, 596 pages ; 26 cm
 Summary

 Acknowledgments
 Introduction and descriptive statistics
 Introduction to statistics
 Summarizing data : frequency distributions in tables and graphs
 Summarizing data : central tendency
 Summarizing data: variability
 Probability and the foundations of inferential statistics
 Probability, normal distributions, and z scores
 Characteristics of the sample mean
 Hypothesis testing : significance, effect size, and power
 Making inferences about one or two means
 Testing means : onesample t test with confidence intervals
 Testing means : twoindependentsample t test with confidence intervals
 Testing means : relatedsamples t test with confidence intervals
 Making inferences about the variability of two or more means
 Oneway analysis of variance : betweensubjects and withinsubjects (repeatedmeasures) designs
 Twoway analysis of variance : betweensubjects factorial design
 Making inferences about patterns, prediction, and nonparametric tests
 Correlation and linear regression
 Chisquare tests : goodnessoffit and the test for independence
 Afterword
 Appendix A: Basic math review and summation notation
 Appendix B: SPSS general instruction guide
 Appendix C: Statistical tables
 Appendix D: Chapter solutions for evennumbered problems
 Glossary
 References
 Index.
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HA29 .P75 2019  Unknown 
 Harshbarger, Ronald J., 1938 author.
 12th edition.  Boston, MA : Cengage Learning, [2019]
 Description
 Book — XV, 901 pages, pages AP 145, A 167, I 118 : illustrations ; 29 cm
 Summary

 0. ALGEBRAIC CONCEPTS. Sets. The Real Numbers. Integral Exponents. Radicals and Rational Exponents. Operations with Algebraic Expressions. Factoring. Algebraic Fractions.
 1. LINEAR EQUATIONS AND FUNCTIONS. Solutions of Linear Equations and Inequalities in One Variable. Functions. Linear Functions. Graphs and Graphing Utilities. Solutions of Systems of Linear Equations. Applications of Functions in Business and Economics.
 2. QUADRATIC AND OTHER SPECIAL FUNCTIONS. Quadratic Equations. Quadratic Functions: Parabolas. Business Applications Using Quadratics. Special Functions and Their Graphs. Modeling Fitting Curves to Data with Graphing Utilities (optional).
 3. MATRICES. Matrices. Multiplication of Matrices. GaussJordan Elimination: Solving Systems of Equations. Inverse of a Square Matrix Matrix Equations. Applications of Matrices: Leontief InputOutput Models.
 4. INEQUALITIES AND LINEAR PROGRAMMING. Linear Inequalities in Two Variables. Linear Programming: Graphical Methods. The Simplex Method: Maximization. The Simplex Method: Duality and Minimization. The Simplex Method with Mixed Constraints.
 5. EXPONENTIAL AND LOGARITHMIC FUNCTIONS. Exponential Functions. Logarithmic Functions and Their Properties. Equations and Applications with Exponential and Logarithmic Functions.
 6. MATHEMATICS OF FINANCE. Simple Interest Sequences. Compound Interest Geometric Sequences. Future Values of Annuities. Present Values of Annuities. Loans and Amortization.
 7. INTRODUCTION TO PROBABILITY. Probability Odds. Unions and Intersections of Events: OneTrial Experiments. Conditional Probability: The Product Rule. Probability Trees and Bayes'' Formula. Counting: Permutations and Combinations. Permutations, Combinations, and Probability. Markov Chains.
 8. FURTHER TOPICS IN PROBABILITY DATA DESCRIPTION. Binomial Probability Experiments. Data Description. Discrete Probability Distributions The Binomial Distribution. Normal Probability Distribution. The Normal Curve Approximation to the Binomial Distribution.
 9. DERIVATIVES. Limits. Continuous Functions Limits at Infinity. Rates of Change and Derivatives. Derivative Formulas. The Product Rule and the Quotient Rule. The Chain Rule and the Power Rule. Using Derivative Formulas. HigherOrder Derivatives. Applications: Marginals and Derivatives.
 10. APPLICATIONS AND DERIVATIVES. Relative Maxima and Minima: Curve Sketching. Concavity: Points of Inflection. Optimization in Business and Economics. Applications of Maxima and Minima. Rational Functions: More Curve Sketching.
 11. DERIVATIVES CONTINUED. Derivatives of Logarithmic Functions. Derivatives of Exponential Functions. Implicit Differentiation. Related Rates. Applications in Business and Economics.
 12. INDEFINITE INTEGRALS. Indefinite Integrals. The Power Rule. Integrals Involving Exponential and Logarithmic Functions. Applications of the Indefinite Integral in Business and Economics. Differential Equations.
 13. DEFINITE INTEGRALS: TECHNIQUES OF INTEGRATION. Area Under a Curve. The Definite Integral: The Fundamental Theorem of Calculus. Area Between Two Curves. Applications of Definite Integrals in Business and Economics. Using Tables of Integrals. Integration by Parts. Improper Integrals and Their Applications. Numerical Integration Methods: The Trapezoidal Rule and Simpson''s Rule.
 14. FUNCTIONS OF TWO OR MORE VARIABLES. Functions of Two or More Variables. Partial Differentiation. Applications of Functions of Two Variables in Business and Economics. Maxima and Minima. Maxima and Minima of Functions Subject to Constraints: Lagrange Multipliers. APPENDICES. A. Graphing Calculator Guide. B. Excel Guide. C. Areas Under the Standard Normal Curve.
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HF5691 .H3184 2019  Unknown 
3. Spatial regression models [2019]
 Ward, Michael Don, 1948 author.
 Second edition.  Thousand Oaks, California : SAGE Publications, [2019]
 Description
 Book — xv, 112 pages ; 22 cm.
 Summary

 Chapter 1: Why Space in the Social Sciences?
 Chapter 2: Maps as Displays of Information
 Chapter 3: Interdependency Among Observations
 Chapter 4: Spatially Lagged Dependent Variables
 Chapter 5: Spatial Error Model
 Chapter 6: Extensions.
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HA30.6 .W37 2019  Unknown 
 Wagner, William E. (William Edward), author.
 Thousand Oaks, California : SAGE Publications, Inc., [2019]
 Description
 Book — xiii, 213 pages ; 23 cm
 Summary

 Acknowledgments
 Chapter 1: Brief Introduction to Research in the Social, Behavioral, and Health Sciences What Is the Purpose of Research? How Is Research Done? Scientific Method and Hypothesis Testing Inductive Research Deductive Research Research Designs
 Chapter 2: Variables and Measurement Variables and Data Levels of Variable Measurement Types of Relationships Research Design and Measurement Quality
 Chapter 3: How to Sample and Collect Data for Analysis Why Use a Sample? Probability Sampling Methods Nonprobability Sampling Methods Validating a Sample Split Ballot Designs How and Where Are Data Collected Today?
 Chapter 4: Data Frequencies and Distributions Univariate Frequencies and Relative Frequencies Cumulative Percentages and Percentiles Frequencies for Quantitative Data Univariate Distributions The Normal Distribution NonNormal Distribution Characteristics Data Transformations for Dealing With NonNormal Distributions Bivariate Frequencies
 Chapter 5: Using and Interpreting Univariate and Bivariate Visualizations Univariate Data Visualization Bivariate Data Visualization
 Chapter 6: Central Tendency and Variability Understanding How to Calculate and Interpret Measures of Central Tendency Understanding How Individuals in a Distribution Vary Around a Central Tendency
 Chapter 7: What Are z Scores, and Why Are They Important? What Is a z Score? How to Calculate a z Score The Standard Normal Table Working With the Standard Normal Distribution to Calculate z Scores, Raw Scores, and Percentiles Confidence Intervals
 Chapter 8: Hypothesis Testing and Statistical Significance Null and Alternative Hypotheses Statistical Significance Test Statistic Distributions Choosing a Test of Statistical Significance The ChiSquare Test of Independence The Independent Samples t Test OneWay Analysis of Variance
 Chapter 9: How to Measure the Relationship Between Nominal and Ordinal Variables Choosing the Correct Measure of Association Trying to Reduce Error (PRE Statistics) Calculating and Interpreting Lambda Calculating and Interpreting Gamma Calculating and Interpreting Somers' d Calculating and Interpreting Kendall's Taub Interpreting PRE Statistics Overview
 Chapter 10: Effect Size Effect Size Choosing an Effect Size
 Chapter 11: How to Interpret and Report Regression Results What Is a Regression? Correlation Bivariate Regression Coefficient of Determination (r2) Multiple Regression Logistic Regression
 Chapter 12: Indices, Typologies, and Scales Indices, Typologies, and Scales Defined and Explained Appendix A. The Standard Normal Table Appendix B. Critical Values for t Statistic Appendix C. Critical Values for ChiSquare Appendix D. Critical Values for F Statistic Appendix E. Glossary About the Authors.
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HA29 .W3325 2019  Unknown 
 Carreyrou, John author.
 First edition.  New York : Alfred A. Knopf, 2018.
 Description
 Book — x, 339 pages ; 25 cm
 Summary

 A purposeful life
 The gluebot
 Apple envy
 Goodbye East Paly
 The childhood neighbor
 Sunny
 Dr. J
 The miniLab
 The wellness play
 "Who is LTC Shoemaker?"
 Lighting a Fuisz
 Ian Gibbons
 Chiat\day
 Going live
 Unicorn
 The grandson
 Fame
 The hippocratic oath
 The tip
 The ambush
 Trade secrets
 La mattanza
 Damage control
 The empress has no clothes
 Epilogue.
"The full inside story of the breathtaking rise and shocking collapse of Theranosthe Enron of Silicon Valleyby the prizewinning journalist who first broke the story and pursued it to the end in the face of pressure and threats from the CEO and her lawyers. In 2014, Theranos founder and CEO Elizabeth Holmes was widely seen as the female Steve Jobs: a brilliant Stanford dropout whose startup "unicorn" promised to revolutionize the medical industry with a machine that would make blood tests significantly faster and easier. Backed by investors such as Larry Ellison and Tim Draper, Theranos sold shares in an early fundraising round that valued the company at $9 billion, putting Holmes's worth at an estimated $4.7 billion. There was just one problem: the technology didn't work. For years, Holmes had been misleading investors, FDA officials, and her own employees. When Carreyrou, working at the Wall Street Journal, got a tip from a former Theranos employee and started asking questions, both Carreyrou and the Journal were threatened with lawsuits. Undaunted, the newspaper ran the first of dozens of Theranos articles in late 2015. By early 2017, the company's value was zero and Holmes faced potential legal action from the government and her investors. Here is the riveting story of the biggest corporate fraud since Enron, a disturbing cautionary tale set amid the bold promises and goldrush frenzy of Silicon Valley" Provided by publisher.
 Online
6. The cow with ear tag #1389 [2018]
 Gillespie, Kathryn (Kathryn A.), author.
 Chicago : The University of Chicago Press, 2018.
 Description
 Book — 252 pages : illustrations ; 24 cm
 Summary

 Sadie
 The politics of research
 The smell of money
 Life for sale
 The cow with ear tag #1389
 Seeking sanctuary
 Doublethinking dairy
 "The stamp of dairyness"
 California dreaming
 On knowing and responding.
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HV4765 .W2 G55 2018  Unknown 
 Cambridge, UK : Royal Society of Chemistry, [2018]
 Description
 Book — 42 pages : color illustrations ; 30 cm
Science Library (Li and Ma)
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HD8039 .C46 G73 2018  Unknown 
8. Energy return on investment : a unifying principle for biology, economics, and sustainability [2016]
 Hall, Charles A. S., author.
 Cham, Switzerland : Springer, [2018]
 Description
 Book — xii, 174 pages : illustrations (some color) ; 24 cm.
 Summary

 Energy as the master resource. The ecological theatre and the evolutionary play. Energy Return on Investment as master driver. Calculating Energy costs and gains in plant and animal populations. Calculating Energy costs and gains in human societies. Maximum Power. The future in a lower EROI world.
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HD9502 .A2 H355 2018  Unknown 
 Pinker, Steven, 1954 author.
 New York, New York : Viking, an imprint of Penguin Random House LLC, [2018]
 Description
 Book — xix, 556 pages : illustrations ; 25 cm
 Online
10. Financial mathematics for actuaries [2018]
 Chan, WaiSum, author.
 Second edition.  New Jersey : World Scientific, [2018]
 Description
 Book — xviii, 353 pages ; 25 cm
 Online
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HF5691 .C345 2018  Unknown 
 Saari, D. (Donald) author.
 Philadelphia, PA, USA : Society for Industrial and Applied Mathematics, [2018]
 Description
 Book — xvii, 171 pages : illustrations ; 25 cm.
 Summary

 Preface
 Chapter 1: Evolutionary game theory
 Chapter 2: All those puzzling voting mysteries!
 Chapter 3: Voting theory applied elsewhere
 Chapter 4: Voting: Symmetry and decompositions
 Chapter 5: Game theory: A decomposition
 Chapter 6: The reductionist approach Bibliography Index.
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H61.25 .S237 2018  Unknown 
12. Options, futures, and other derivatives [2018]
 Hull, John, 1946 author.
 Tenth edition.  New York, NY : Pearson, [2018]
 Description
 Book — xxiii, 868 pages ; 26 cm
 Summary

 List of Business Snapshots List of Technical Notes Preface
 1. Introduction
 2. Futures markets and central counterparties
 3. Hedging strategies using futures
 4. Interest rates
 5. Determination of forward and futures prices
 6. Interest rate futures
 7. Swaps
 8. Securitization and the credit crisis of
 2007
 9. XVAs
 10. Mechanics of options markets
 11. Properties of stock options
 12. Trading strategies involving options
 13. Binomial trees
 14. Wiener processes and Ito's lemma
 15. The BlackScholesMerton model
 16. Employee stock options
 17. Options on stock indices and currencies
 18. Futures options and Black's model
 19. The Greek letters
 20. Volatility smiles
 21. Basic numerical procedures
 22. Value at risk and expected shortfall
 23. Estimating volatilities and correlations
 24. Credit risk
 25. Credit derivatives
 26. Exotic options
 27. More on models and numerical procedures
 28. Martingales and measures
 29. Interest rate derivatives: The standard market models
 30. Convexity, timing, and quanto adjustments
 31. Equilibrium models of the short rate
 32. Noarbitrage models of the short rate
 33. HJM, LMM, and multiple zero curves
 34. Swaps Revisited
 35. Energy and commodity derivatives
 36. Real options
 37. Derivatives mishaps and what we can learn from them Glossary of terms DerivaGem software Major exchanges trading futures and options Tables for N (x) Author index Subject index.
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HG6024 .A3 H85 2018  Unknown 
 Nuwer, Rachel Love, author.
 First edition.  New York, NY : Da Capo Press, 2018.
 Description
 Book — ix, 374 pages : illustrations ; 24 cm
 Summary

 Part I. Drivers of demand. The hunter ; Her sister's pangolin scale guy ; Rhino horn in the cookie tin ; The holy grail of herpetology ; White gold
 Part II. Inside the trade. The $50,000,000 bonfire ; The CITES circus ; Of prostitutes, poachers, and politicans ; The front line
 Part III. The saving game. A park reborn ; If rhinos could choose ; My tiger wine is corked ; Rising moon bears ; Order ahead for pangolin.
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HV6410 .N89 2018  Unknown 
14. Principles & methods of statistical analysis [2018]
 Frieman, Jerome, author.
 Thousand Oaks, California : SAGE Publications, Inc., [2018]
 Description
 Book — xxix, 496 pages ; 24 cm
 Summary

 Preface About the Authors Prologue PART I * GETTING STARTED
 Chapter 1: The Big Picture Models The Classical Statistical Model Designing Experiments and Analyzing Data Summary Questions Raised by the Use of the Classical Statistical Model Conceptual Exercises
 Chapter 2: Examining Our Data: An Introduction to Some of the Techniques of Exploratory Data Analysis Descriptive Statistics Histograms Exploratory Data Analysis Quantile Plots StemandLeaf Displays LetterValue Displays Box Plots Did My Data Come From a Normal Distribution? Why Should We Care About Looking at Our Data? Summary Conceptual Exercises PART II * THE BEHAVIOR OF DATA
 Chapter 3: Properties of Distributions: The Building Blocks of Statistical Inference The Effects of Adding a Constant or Multiplying by a Constant The Standard Score Transformation The Effects of Adding or Subtracting Scores From Two Different Distributions The Distribution of Sample Means The Central Limit Theorem Averaging Means and Variances Expected Value Theorems on Expected Value Summary Conceptual Exercises PART III * THE BASICS OF STATISTICAL INFERENCE: DRAWING CONCLUSIONS FROM OUR DATA
 Chapter 4: Estimating Parameters of Populations From Sample Data Statistical Inference With the Classical Statistical Model Criteria for Selecting Estimators of Population Parameters Maximum Likelihood Estimation Confidence Intervals Beyond Normal Distributions and Estimating Population Means Summary Conceptual Exercises
 Chapter 5: Resistant Estimators of Parameters A Closer Look at Sampling From NonNormal Populations The Sample Mean and Sample Median Are LEstimators Measuring the Influence of Outliers on Estimates of Location and Spread ?Trimmed Means as Resistant and Efficient Estimators of Location Winsorizing: Another Way to Create a Resistant Estimator of Location Applying These Resistant Estimators to Our Data Resistant Estimators of Spread Applying These Resistant Estimators to Our Data (Part 2) MEstimators: Another Approach to Finding Resistant Estimators of Location Which Estimator of Location Should I Use? Resampling Methods for Constructing Confidence Intervals A Final Caveat Summary Conceptual Exercises
 Chapter 6: General Principles of Hypothesis Testing Experimental and Statistical Hypotheses Estimating Parameters The Criterion for Evaluating Our Statistical Hypotheses Creating Our Test Statistic Drawing Conclusions About Our Null Hypothesis But Suppose H0 Is False? Errors in Hypothesis Testing Power and Power Functions The Use of Power Functions pValues, a, and Alpha (Type I) Errors: What They Do and Do Not Mean A Word of Caution About Attempting to Estimate the Power of a Hypothesis Test After the Data Have Been Collected Is It Ever Appropriate to Use a OneTailed Hypothesis Test? What Should We Mean When We Say Our Results Are Statistically Significant? A Final Word Summary Conceptual Exercises PART IV * SPECIFIC TECHNIQUES TO ANSWER SPECIFIC QUESTIONS
 Chapter 7: The Independent Groups tTests for Testing for Differences Between Population Means Student's ttest Distribution of the Independent Groups tStatistic when H0 Is True Distribution of the Independent Groups tStatistic When H0 Is False Factors That Affect the Power of the Independent Groups tTest The Assumption Behind the Homogeneity of Variance Assumption Graphical Methods for Comparing Two Groups Suppose the Population Variances Are Not Equal? Standardized Group Differences as Estimators of Effect Size Robust Hypothesis Testing Resistant Estimates of Effect Size Summary Conceptual Exercises
 Chapter 8: Testing Hypotheses When the Dependent Variable Consists of Frequencies of Scores in Various Categories Classifying Data Testing Hypotheses When the Dependent Variable Consists of Only Two Possibilities The Binomial Distribution Testing Hypotheses About the Parameter p in a Binomial Experiment The Normal Distribution Approximation to the Binomial Distribution Testing Hypotheses About the Difference Between Two Binomial Parameters (p1  p2) Testing Hypotheses in Which the Dependent Variable Consists of Two or More Categories Summary Conceptual Exercises
 Chapter 9: The Randomization/Permutation Model: An Alternative to the Classical Statistical Model for Testing Hypotheses About Treatment Effects The Assumptions Underlying the Classical Statistical Model The Assumptions Underlying the Randomization Model Hypotheses for Both Models The Exact Randomization Test for Testing Hypotheses About the Effects of Different Treatments on Behavior The Approximate Randomization Test for Testing Hypotheses About the Effects of Different Treatments on Behavior Using the Randomization Model to Investigate Possible Effects of Treatments SingleParticipant Experimental Designs Summary Conceptual Exercises Additional Resources
 Chapter 10: Exploring the Relationship Between Two Variables: Correlation Measuring the Degree of Relationship Between Two IntervalScale Variables Randomization (Permutation) Model for Testing Hypotheses About the Relationship Between Two Variables The Bivariate Normal Distribution Model for Testing Hypotheses About Population Correlations Creating a Confidence Interval for the Population Correlation Using the Bivariate Normal Distribution Model Bootstrap Confidence Intervals for the Population Correlation Unbiased Estimators of the Population Correlation Robust Estimators of Correlation Assessing the Relationship Between Two Nominal Variables The Fisher Exact Probability Test for
 2 x
 2 Contingency Tables With Small Sample Sizes Correlation Coefficients for Nominal Data in Contingency Tables Summary Conceptual Exercises
 Chapter 11: Exploring the Relationship Between Two Variables: The Linear Regression Model Assumptions for the Linear Regression Model Estimating Parameters With the Linear Regression Model Regression and Prediction Variance and Correlation Testing Hypotheses With the Linear Regression Model Summary Conceptual Exercises
 Chapter 12: A Closer Look at Linear Regression The Importance of Looking at Our Data Using Residuals to Check Assumptions Testing Whether the Relationship Between Two Variables Is Linear The Correlation Ratio: An Alternate Way to Measure the Degree of Relationship and Test for a Linear Relationship Where Do We Go From Here? When the Relationship Is Not Linear The Effects of Outliers on Regression Robust Alternatives to the Method of Least Squares A Quick Peek at Multiple Regression Summary Conceptual Exercises
 Chapter 13: Another Way to Scale the Size of Treatment Effects The Point Biserial Correlation Coefficient and the tTest Advantages and Disadvantages of Estimating Effect Sizes With Correlation Coefficients or Standardized Group Difference Measures Confidence Intervals for Effect Size Estimates Final Comments on the Use of Effect Size Estimators Summary Conceptual Exercises
 Chapter 14: Analysis of Variance for Testing for Differences Between Population Means What Are the Sources of Variation in Our Experiments? Experimental and Statistical Hypotheses Estimating Variances When There Are More Than Two Conditions in Your Experiment Assumptions for Analysis of Variance Testing Hypotheses About Differences Among Population Means With Analysis of Variance Factors That Affect the Power of the FTest in Analysis of Variance Relational Effect Size Measures for Analysis of Variance Randomization Tests for Testing for Differential Effects of Three or More Treatments Using ANOVA to Study the Effects of More Than One Factor on Behavior Partitioning Variance for a TwoFactor Analysis of Variance Testing Hypotheses With TwoFactor Analysis of Variance Testing Hypotheses About Differences Among Population Means With Analysis of Variance Dealing With Unequal Sample Sizes in Factorial Designs Summary Conceptual Exercises
 Chapter 15: Multiple Regression and Beyond Overview of the General Linear Model Approach Regression Simple Versus Multiple Regression Multiple Regression Types of Multiple Regression Interactions in Multiple Regression Continuous x Continuous Interactions Categorical x Continuous Interactions Categorical x Categorical Interactions: ANOVA Versus Regression Summary Conceptual Exercises Epilogue Appendices A. Some Useful Rules of Algebra B. Rules of Summation C. Logarithms D. The Inverse of the Cumulative Normal Distribution E. The Unit Normal Distribution F. The tDistribution G. The Fisher r to zr Transformation H. Critical Values for F With Alpha = .05 I. The Chi Square Distribution References Index.
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HA29 .F76812 2018  Unknown 
 Singapore : Springer, [2018]
 Description
 Book — xxi, 264 pages : illustrations (some color) ; 25 cm.
 Summary

 Chapter 1: Organization resilience: What makes companies and organizations sustainable?.
 Chapter 2: Organizational resilience: Theoretical framework.
 Chapter 3: A resourcebased model of organizational resilience.
 Chapter 4: The champion company that disappeared: A resilience resources analysis of Circuit City.
 Chapter 5: BP and Deepwater Horizon: A catastrophe from a resilience perspective.
 Chapter 6: Resilient leadership: Lessons from three legendary business leaders.
 Chapter 7: Financial resilience: The role of financial balance, profitability, and ownership.
 Chapter 8: Resilience in the productdelivery supply chain.
 Chapter 9: Followership: An important social resource for organizational resilience.
 Chapter 10: Followership for organizational resilience in healthcare.
 Chapter 11: Organizational resilience and stagnation at a fashion company.
 Chapter 12: Business clusters and organizational resilience.
 Chapter 13: Regional resilience.
 Chapter 14: Conclusions: The resilience framework summarised.
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HD58.9 .R47 2018  Unknown 
 Washington, DC : The National Academies Press, [2018]
 Description
 Book — xx, 292 pages : color illustrations ; 23 cm.
 Summary

 Sexual harassment research
 Sexual harassment in academic sciences, engineering, and medicine
 Job and health outcomes of sexual harassment and how women respond to sexual harassment
 Legal and policy mechanisms for addressing sexual harassment
 Changing the culture and climate in higher education
 Findings, conclusions, and recommendations.
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HQ1237.5 .U6 S49 2018  Unknown 
 Flora, David B., author.
 London ; Thousand Oaks, California : SAGE Publications, 2018.
 Description
 Book — xvi, 456 pages : illustrations ; 26 cm
 Summary

 1. Foundations of Statistical Modeling Demonstrated with Simple Regression
 2. Multiple Regression with Continuous Predictors
 3. Regression with Categorical Predictors
 4. Interactions in Multiple Regression: Models for Moderation
 5. Using Multiple Regression to Model Mediation and Other Indirect Effects
 6. Introduction to Multilevel Modeling
 7. Basic Matrix Algebra for Statistical Modeling
 8. Exploratory Factor Analysis
 9. Structural Equation Modeling I: Path Analysis
 10. Structural Equation Modeling II: Latent Variable Models
 11. Growth Curve Modeling.
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HA29 .F56 2018  Unknown 
18. Statistics for the behavioral sciences [2018]
 Privitera, Gregory J., author.
 Third edition.  Thousand Oaks, California : SAGE Publications, Inc., [2018]
 Description
 Book — xliii, 650 pages, 114 variously numbered pages ; 26 cm
 Summary

 About the author
 Acknowledgments
 Preface to the instructor
 To the student : how to use spss with this book
 Introduction and descriptive statistics
 Introduction to statistics
 Summarizing data: frequency distributions in tables and graphs
 Summarizing data: central tendency
 Summarizing data: variability
 Probability and the foundations of inferential statistics
 Probability
 Probability, normal distributions, and Z scores
 Probability and sampling distributions
 Making inferences about one or two means
 Hypothesis testing: significance, effect size, and power
 Testing means : onesample and twoindependentsample t tests
 Testing means : the relatedsamples T test
 Estimation and confidence intervals
 Making inferences about the variability of two or more means
 Analysis of variance: oneway betweensubjects design
 Analysis of variance : oneway withinsubjects (repeatedmeasures) design
 Analysis of variance: twoway betweensubjects factorial design
 Making inferences about patterns, frequencies, and ordinal data
 Correlation
 Linear regression and multiple regression
 Nonparametric tests: chisquare tests
 Nonparametric tests: tests for ordinal data
 Afterword
 Appendix A. Basic math review and summation notation
 Appendix B. SPSSs general instructions guide
 Appendix C. Statistical tables
 Appendix D. Chapter solutions for evennumbered problems
 Glossary
 References.
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HA29 .P755 2018  Unknown 
19. Thinking through statistics [2018]
 Martin, John Levi, 1964 author.
 Chicago ; London : The University of Chicago Press, 2018.
 Description
 Book — xiv, 362 pages : illustrations, maps ; 24 cm
 Summary

 Introduction
 Know your data
 Selectivity
 Misspecification and control
 Where is the variance?
 Opportunity knocks
 Time and space
 When the world knows more about the processes than you do
 Too good to be true.
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HA29 .M135 2018  Unknown 
 Gayle, Vernon, author.
 London ; New York, NY : Bloomsbury Academic, an imprint of Bloomsbury Publishing Plc, 2018.
 Description
 Book — xiv, 151 pages ; 22 cm.
 Summary

 1. Introduction
 2. Getting Started
 3. Temporal Analysis with CrossSectional Data
 4. Analysis of Data on Durations
 5. Analysis of Repeated Contacts Data
 6. Conclusion Bibliography Index.
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HA29 .G26 2018  Unknown 