Getting started with data science
Subtitle: making sense of data with analytics
By: Murtaza Haider
Published: 2016
Language: eng
Number of pages: 573
ISBN-13: 9780133991024
Subjects: Big data; Data mining
Notes: Includes bibliographical references and index.
Table of contents: title: Data Science: The Sexiest Job in the 21st Century; title: Storytelling at Google and Walmart; title: Getting Started with Data Science; title: Do We Need Another Book on Analytics?; title: Repeat, Repeat, Repeat, and Simplify; title: Chapters' Structure and Features; title: Analytics Software Used; title: What Makes Someone a Data Scientist?; title: Existential Angst of a Data Scientist; title: Data Scientists: Rarer Than Unicorns; title: Beyond the Big Data Hype; title: Big Data: Beyond Cheerleading; title: Big Data Hubris; title: Leading by Miles; title: Predicting Pregnancies, Missing Abortions; title: What's Beyond This Book?; title: Summary; title: Endnotes; title: The Liberated Data: The Open Data; title: The Caged Data; title: Big Data Is Big News; title: It's Not the Size of Big Data; It's What You Do with It; title: Free Data as in Free Lunch; title: FRED; title: Quandl; title: U.S. Census Bureau and Other National Statistical Agencies; title: Search-Based Internet Data; title: Google Trends; title: Google Correlate; title: Survey Data; title: PEW Surveys; title: ICPSR; title: Summary; title: Endnotes; title: The Final Deliverable; title: What Is the Research Question?; title: What Answers Are Needed?; title: How Have Others Researched the Same Question in the Past?; title: What Information Do You Need to Answer the Question?; title: What Analytical Techniques/Methods Do You Need?; title: The Narrative; title: The Report Structure; title: Have You Done Your Job as a Writer?; title: Building Narratives with Data; title: "Big Data, Big Analytics, Big Opportunity"; title: Urban Transport and Housing Challenges; title: Human Development in South Asia; title: The Big Move; title: Summary; title: Endnotes; title: 2014: The Year of Soccer and Brazil; title: Using Percentages Is Better Than Using Raw Numbers; title: Data Cleaning; title: Weighted Data; title: Cross Tabulations; title: Going Beyond the Basics in Tables; title: Seeing Whether Beauty Pays; title: Data Set; title: What Determines Teaching Evaluations?; title: Does Beauty Affect Teaching Evaluations?; title: Putting It All on (in) a Table; title: Generating Output with Stata; title: Summary Statistics Using Built-In Stata; title: Using Descriptive Statistics; title: Weighted Statistics; title: Correlation Matrix; title: Reproducing the Results for the Hamermesh and Parker Paper; title: Statistical Analysis Using Custom Tables; title: Summary; title: Endnotes; title: Telling Stories with Figures; title: Data Types; title: Teaching Ratings; title: The Congested Lives in Big Cities; title: Summary; title: Endnotes; title: Random Numbers and Probability Distributions; title: Casino Royale: Roll the Dice; title: Normal Distribution; title: The Student Who Taught Everyone Else; title: Statistical Distributions in Action; title: Z-Transformation; title: Probability of Getting a High or Low Course Evaluation; title: Probabilities with Standard Normal Table; title: Hypothetically Yours; title: Consistently Better or Happenstance; title: Mean and Not So Mean Differences; title: Handling Rejections; title: The Mean and Kind Differences; title: Comparing a Sample Mean When the Population SD Is Known; title: Left Tail Between the Legs; title: Comparing Means with Unknown Population SD; title: Comparing Two Means with Unequal Variances; title: Comparing Two Means with Equal Variances; title: Worked-Out Examples of Hypothesis Testing; title: Best Bu-Apple Store Comparison; title: Assuming Equal Variances; title: Exercises for Comparison of Means; title: Regression for Hypothesis Testing; title: Analysis of Variance; title: Significantly Correlated; title: Summary; title: Endnotes; title: The Department of Obvious Conclusions; title: Why Regress?; title: Introducing Regression Models; title: All Else Being Equal; title: Holding Other Factors Constant; title: Spuriously Correlated; title: A Step-By-Step Approach to Regression; title: Learning to Speak Regression; title: The Math Behind Regression; title: Ordinary Least Squares Method; title: Regression in Action; title: This Just In: Bigger Homes Sell for More; title: Does Beauty Pay? Ask the Students; title: Survey Data, Weights, and Independence of Observations; title: What Determines Household Spending on Alcohol and Food; title: What Influences Household Spending on Food?; title: Advanced Topics; title: Homoskedasticity; title: Multicollinearity; title: Summary; title: Endnotes; title: To Smoke or Not to Smoke: That Is the Question; title: Binary Outcomes; title: Binary Dependent Variables; title: Let's Question the Decision to Smoke or Not; title: Smoking Data Set; title: Exploratory Data Analysis; title: What Makes People Smoke: Asking Regression for Answers; title: Ordinary Least Squares Regression; title: Interpreting Models at the Margins; title: The Logit Model; title: Interpreting Odds in a Logit Model; title: Probit Model; title: Interpreting the Probit Model; title: Using Zelig for Estimation and Post-Estimation Strategies; title: Estimating Logit Models for Grouped Data; title: Using SPSS to Explore the Smoking Data Set; title: Regression Analysis in SPSS; title: Estimating Logit and Probit Models in SPSS; title: Summary; title: Endnotes; title: What Is Categorical Data?; title: Analyzing Categorical Data; title: Econometric Models of Binomial Data; title: Estimation of Binary Logit Models; title: Odds Ratio; title: Log of Odds Ratio; title: Interpreting Binary Logit Models; title: Statistical Inference of Binary Logit Models; title: How I Met Your Mother? Analyzing Survey Data; title: A Blind Date with the Pew Online Dating Data Set; title: Demographics of Affection; title: High-Techies; title: Romancing the Internet; title: Dating Models; title: Multinomial Logit Models; title: Interpreting Multinomial Logit Models; title: Choosing an Online Dating Service; title: Pew Phone Type Model; title: Why Some Women Work Full-Time and Others Don't; title: Conditional Logit Models; title: Random Utility Model; title: Independence From Irrelevant Alternatives; title: Interpretation of Conditional Logit Models; title: Estimating Logit Models in SPSS; title: Summary; title: Endnotes; title: Fundamentals of GIS; title: GIS Platforms; title: Freeware GIS; title: GIS Data Structure; title: GIS Applications in Business Research; title: Retail Research; title: Hospitality and Tourism Research; title: Lifestyle Data: Consumer Health Profiling; title: Competitor Location Analysis; title: Market Segmentation; title: Spatial Analysis of Urban Challenges; title: The Hard Truths About Public Transit in North America; title: Toronto Is a City Divided into the Haves, Will Haves, and Have Nots; title: Income Disparities in Urban Canada; title: Where Is Toronto's Missing Middle Class? It Has Suburbanized Out of Toronto; title: Adding Spatial Analytics to Data Science; title: Race and Space in Chicago; title: Developing Research Questions; title: Race, Space, and Poverty; title: Race, Space, and Commuting; title: Regression with Spatial Lags; title: Summary; title: Endnotes; title: Introducing Time Series Data and How to Visualize It; title: How Is Time Series Data Different'?; title: Starting with Basic Regression Models; title: What Is Wrong with Using OLS Models for Time Series Data?; title: Newey-West Standard Errors; title: Regressing Prices with Robust Standard Errors; title: Time Series Econometrics; title: Stationary Time Series; title: Autocorrelation Function (ACF); title: Partial Autocorrelation Function (PCF); title: White Noise Tests; title: Augmented Dickey Fuller Test; title: Econometric Models for Time Series Data; title: Correlation Diagnostics; title: Invertible Time Series and Lag Operators; title: The ARMA Model; title: ARIMA Models; title: Distributed Lag and VAR Models; title: Applying Time Series Tools to Housing Construction; title: Macro-Economic and Socio-Demographic Variables Influencing Housing Starts; title: Estimating Time Series Models to Forecast New Housing Construction; title: OLS Models; title: Distributed Lag Model; title: Out-of-Sample Forecasting with Vector Autoregressive Models; title: ARIMA Models; title: Summary; title: Endnotes; title: Can Cheating on Your Spouse Kill You?; title: Are Cheating Men Alpha Males?; title: UnFair Comments: New Evidence Critiques Fair's Research; title: Data Mining: An Introduction; title: Seven Steps Down the Data Mine; title: Establishing Data Mining Goals; title: Selecting Data; title: Preprocessing Data; title: Transforming Data; title: Storing Data; title: Mining Data; title: Evaluating Mining Results; title: Rattle Your Data; title: What Does Religiosity Have to Do with Extramarital Affairs?; title: The Principal Components of an Extramarital Affair; title: Will It Rain Tomorrow? Using PCA For Weather Forecasting; title: Do Men Have More Affairs Than Females?; title: Two Kinds of People: Those Who Have Affairs, and Those Who Don't; title: Models to Mine Data with Rattle; title: Summary; title: Endnotes.