{"product_id":"introduction-to-statistical-investigations-isbn-9781119683452","title":"Introduction to Statistical Investigations","description":"\u003cp\u003e\u003ci\u003eIntroduction to Statistical Investigations, Second Edition\u003c\/i\u003e provides a unified framework for explaining variation across study designs and variable types, helping students increase their statistical literacy and appreciate the indispensable role of statistics in scientific research. Requiring only basic algebra as a prerequisite, the program uses the immersive, simulation-based inference approach for which the author team is known. Students engage with various aspects of data collection and analysis using real data and clear explanations designed to strengthen multivariable understanding and reinforce concepts.\u003c\/p\u003e \u003cp\u003eEach chapter follows a coherent six-step statistical exploration and investigation method (ask a research question, design a study, explore the data, draw inferences, formulate conclusions, and look back and ahead) enabling students to assess a variety of concepts in a single assignment. Challenging questions based on research articles strengthen critical reading skills, fully worked examples demonstrate essential concepts and methods, and engaging visualizations illustrate key themes of explained variation. The end-of-chapter investigations expose students to various applications of statistics in the real world using real data from popular culture and published research studies in variety of disciplines. Accompanying examples throughout the text, user-friendly applets enable students to conduct the simulations and analyses covered in the book.\u003c\/p\u003e \u003cp\u003ePreliminaries Introduction to Statistical Investigations 1\u003c\/p\u003e \u003cp\u003eSection P.1: Introduction to the Six-Step Method 2\u003c\/p\u003e \u003cp\u003eExample P.1: Organ Donations 2\u003c\/p\u003e \u003cp\u003eSection P.2: Exploring Data 7\u003c\/p\u003e \u003cp\u003eExample P.2: Oh, Say Can You Sing? 7\u003c\/p\u003e \u003cp\u003eSection P.3: Exploring Random Processes 14\u003c\/p\u003e \u003cp\u003eExploration P.3: Cars or Goats 14\u003c\/p\u003e \u003cp\u003e\u003cb\u003eUnit 1 Four Pillars of Inference: Strength, Size, Breadth, and Cause 30\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 \u003c\/b\u003e\u003cb\u003eSignificance: How Strong Is the Evidence? 31\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 1.1: Introduction to Chance Models 32\u003c\/p\u003e \u003cp\u003eExample 1.1: Can Dolphins Communicate? 33\u003c\/p\u003e \u003cp\u003eExploration 1.1: Can Dogs Understand Human Cues? 41\u003c\/p\u003e \u003cp\u003eSection 1.2: Measuring the Strength of Evidence 45\u003c\/p\u003e \u003cp\u003eExample 1.2: Rock-Paper-Scissors 46\u003c\/p\u003e \u003cp\u003eExploration 1.2: Tasting Water 52\u003c\/p\u003e \u003cp\u003eSection 1.3: Alternative Measure of Strength of Evidence 57\u003c\/p\u003e \u003cp\u003eExample 1.3: Heart Transplant Operations 58\u003c\/p\u003e \u003cp\u003eExploration 1.3: Do People Use Facial Prototyping? 62\u003c\/p\u003e \u003cp\u003eSection 1.4: What Impacts Strength of Evidence? 66\u003c\/p\u003e \u003cp\u003eExample 1.4: Predicting Elections from Faces? 66\u003c\/p\u003e \u003cp\u003eExploration 1.4: Competitive Advantage to Uniform Colors? 72\u003c\/p\u003e \u003cp\u003eSection 1.5: Inference for a Single Proportion: Theory-Based Approach 75\u003c\/p\u003e \u003cp\u003eExample 1.5: Halloween Treats 77\u003c\/p\u003e \u003cp\u003eExploration 1.5: Eye Dominance 80\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 \u003c\/b\u003e\u003cb\u003eGeneralization: How Broadly Do the Results Apply? 117\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 2.1: Sampling from a Finite Population: Proportions 118\u003c\/p\u003e \u003cp\u003eExample 2.1: Voter Turnout 119\u003c\/p\u003e \u003cp\u003eExploration 2.1: Sampling Words 126\u003c\/p\u003e \u003cp\u003eSection 2.2: Quantitative Data 133\u003c\/p\u003e \u003cp\u003eExample 2.2: Sampling Students 134\u003c\/p\u003e \u003cp\u003eExploration 2.2: Sampling Words (cont.) 138\u003c\/p\u003e \u003cp\u003eSection 2.3: Theory-based Inference for a Population Mean 143\u003c\/p\u003e \u003cp\u003eExample 2.3: Estimating Elapsed Time 143\u003c\/p\u003e \u003cp\u003eExploration 2.3: Sleepless Nights? 150\u003c\/p\u003e \u003cp\u003eSection 2.4: Other Statistics 154\u003c\/p\u003e \u003cp\u003eExample 2.4: Estimating Elapsed Time (cont.) 154\u003c\/p\u003e \u003cp\u003eExploration 2.4: Backpack Weights 160\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 \u003c\/b\u003e\u003cb\u003eEstimation: How Large Is the Effect? 187\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 3.1: Statistical Inference: Confidence Intervals 188\u003c\/p\u003e \u003cp\u003eExample 3.1: Can Dogs Sniff Out Cancer? 189\u003c\/p\u003e \u003cp\u003eExploration 3.1: Kissing Right? 194\u003c\/p\u003e \u003cp\u003eSection 3.2: 2SD and Theory-Based Confidence Intervals for a Single Proportion 198\u003c\/p\u003e \u003cp\u003eExample 3.2: Cyberbullying 198\u003c\/p\u003e \u003cp\u003eExploration 3.2: How Mobile Are We? 203\u003c\/p\u003e \u003cp\u003eSection 3.3: 2SD and Theory-Based Confidence Intervals for a Single Mean 207\u003c\/p\u003e \u003cp\u003eExample 3.3: Used Cars 207\u003c\/p\u003e \u003cp\u003eExploration 3.3: Sleepless Nights? (cont.) 210\u003c\/p\u003e \u003cp\u003eSection 3.4: Factors That Affect the Width of a Confidence Interval 213\u003c\/p\u003e \u003cp\u003eExample 3.4: American Cat Ownership 214\u003c\/p\u003e \u003cp\u003eExploration 3.4A: Holiday Spending Habits 216\u003c\/p\u003e \u003cp\u003eExploration 3.4B: Reese’s Pieces 218\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 \u003c\/b\u003e\u003cb\u003eCausation: Can We Say What Caused the Effect? 245\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 4.1: Association and Confounding 246\u003c\/p\u003e \u003cp\u003eExample 4.1: Night Lights and Nearsightedness 247\u003c\/p\u003e \u003cp\u003eExploration 4.1: Home Court Disadvantage? 250\u003c\/p\u003e \u003cp\u003eSection 4.2: Observational Studies Versus Experiments 252\u003c\/p\u003e \u003cp\u003eExample 4.2: Lying on the Internet 253\u003c\/p\u003e \u003cp\u003eExploration 4.2: Have a Nice Trip 257\u003c\/p\u003e \u003cp\u003e\u003cb\u003eUnit 2 Comparing Two Groups 278\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 \u003c\/b\u003e\u003cb\u003eComparing Two Proportions 279\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 5.1: Comparing Two Groups: Categorical Response 280\u003c\/p\u003e \u003cp\u003eExample 5.1: Buckling Up? 280\u003c\/p\u003e \u003cp\u003eExploration 5.1: Murderous Nurse? 285\u003c\/p\u003e \u003cp\u003eSection 5.2: Comparing Two Proportions: Simulation-Based Approach 288\u003c\/p\u003e \u003cp\u003eExample 5.2: Swimming with Dolphins 289\u003c\/p\u003e \u003cp\u003eExploration 5.2: Is Yawning Contagious? 297\u003c\/p\u003e \u003cp\u003eSection 5.3: Comparing Two Proportions: Theory-Based Approach 304\u003c\/p\u003e \u003cp\u003eExample 5.3: Parents’ Smoking Status and Their Babies’ Sex 305\u003c\/p\u003e \u003cp\u003eExploration 5.3: Donating Blood 311\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 \u003c\/b\u003e\u003cb\u003eComparing Two Means 346\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 6.1: Comparing Two Groups: Quantitative Response 347\u003c\/p\u003e \u003cp\u003eExample 6.1: Geyser Eruptions 347\u003c\/p\u003e \u003cp\u003eExploration 6.1: Cancer Pamphlets 350\u003c\/p\u003e \u003cp\u003eSection 6.2: Comparing Two Means: Simulation-Based Approach 354\u003c\/p\u003e \u003cp\u003eExample 6.2: Dung Beetles 354\u003c\/p\u003e \u003cp\u003eExploration 6.2: Lingering Effects of Sleep Deprivation 363\u003c\/p\u003e \u003cp\u003eSection 6.3: Comparing Two Means: Theory-Based Approach 369\u003c\/p\u003e \u003cp\u003eExample 6.3: Violent Video Games and Aggression 369\u003c\/p\u003e \u003cp\u003eExploration 6.3: Close Friends 378\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 \u003c\/b\u003e\u003cb\u003ePaired Data: One Quantitative Variable 407\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 7.1: Paired Designs 408\u003c\/p\u003e \u003cp\u003eExample 7.1: Can You Study with Music Blaring? 408\u003c\/p\u003e \u003cp\u003eExploration 7.1: Rounding First Base 411\u003c\/p\u003e \u003cp\u003eSection 7.2: Simulation-Based Approach to Analyzing Paired Data 413\u003c\/p\u003e \u003cp\u003eExample 7.2: Rounding First Base (cont.) 414\u003c\/p\u003e \u003cp\u003eExploration 7.2: Exercise and Heart Rate 420\u003c\/p\u003e \u003cp\u003eSection 7.3: Theory-Based Approach to Analyzing Data from Paired Samples 425\u003c\/p\u003e \u003cp\u003eExample 7.3: Dad Jokes? 425\u003c\/p\u003e \u003cp\u003eExploration 7.3: Comparing Auction Formats 431\u003c\/p\u003e \u003cp\u003e\u003cb\u003eUnit 3 Analyzing More General Situations 456\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 \u003c\/b\u003e\u003cb\u003eComparing More Than Two Proportions 458\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 8.1: Comparing Multiple Proportions: Simulation-Based Approach 459\u003c\/p\u003e \u003cp\u003eExample 8.1: Coming to a Stop 460\u003c\/p\u003e \u003cp\u003eExploration 8.1: Recruiting Organ Donors 466\u003c\/p\u003e \u003cp\u003eSection 8.2: Comparing Multiple Proportions: Theory-Based Approach 470\u003c\/p\u003e \u003cp\u003eExample 8.2: Sham Acupuncture 471\u003c\/p\u003e \u003cp\u003eExploration 8.2A: Conserving Hotel Towels 476\u003c\/p\u003e \u003cp\u003eExploration 8.2B: Nearsightedness and Night Lights Revisited 480\u003c\/p\u003e \u003cp\u003eSection 8.3: Chi-Square Goodness-of-Fit Test 484\u003c\/p\u003e \u003cp\u003eExample 8.3: Fair Die? 484\u003c\/p\u003e \u003cp\u003eExploration 8.3: Are Birthdays Equally Distributed Throughout the Week? 490\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 \u003c\/b\u003e\u003cb\u003eComparing More Than Two Means 519\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 9.1: Comparing Multiple Means: Simulation- Based Approach 520\u003c\/p\u003e \u003cp\u003eExample 9.1: Comprehending Ambiguous Prose 520\u003c\/p\u003e \u003cp\u003eExploration 9.1: Exercise and Brain Volume 525\u003c\/p\u003e \u003cp\u003eSection 9.2: Comparing Multiple Means: Theory-Based\u003c\/p\u003e \u003cp\u003eApproach 529\u003c\/p\u003e \u003cp\u003eExample 9.2: Recalling Ambiguous Prose 530\u003c\/p\u003e \u003cp\u003eExploration 9.2: Comparing Popular Diets 538\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 \u003c\/b\u003e\u003cb\u003eTwo Quantitative Variables 565\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 10.1: Two Quantitative Variables: Scatterplots and Correlation 566\u003c\/p\u003e \u003cp\u003eExample 10.1: Why Whales Are Big, but Not Bigger 567\u003c\/p\u003e \u003cp\u003eExploration 10.1: Height and Winning at Tennis 571\u003c\/p\u003e \u003cp\u003eSection 10.2: Inference for the Correlation Coefficient: Simulation-Based Approach 576\u003c\/p\u003e \u003cp\u003eExample 10.2: Exercise Intensity and Mood Changes 576\u003c\/p\u003e \u003cp\u003eExploration 10.2: Draft Lottery 580\u003c\/p\u003e \u003cp\u003eSection 10.3: Least Squares Regression 585\u003c\/p\u003e \u003cp\u003eExample 10.3: Height and Winning at Tennis (cont.) 585\u003c\/p\u003e \u003cp\u003eExploration 10.3: Predicting Height from Footprints 590\u003c\/p\u003e \u003cp\u003eSection 10.4: Inference for the Regression Slope: Simulation-Based Approach 596\u003c\/p\u003e \u003cp\u003eExample 10.4: Do Students Who Spend More Time in Non-Academic Activities Tend to Have Lower GPAs? 596\u003c\/p\u003e \u003cp\u003eExploration 10.4: Predicting Brain Density from Number of Facebook Friends 599\u003c\/p\u003e \u003cp\u003eSection 10.5: Inference for the Regression Slope: Theory-Based Approach 601\u003c\/p\u003e \u003cp\u003eExample 10.5A: Predicting Heart Rate from Body Temperature 602\u003c\/p\u003e \u003cp\u003eExample 10.5B: Smoking and Drinking 606\u003c\/p\u003e \u003cp\u003eExploration 10.5: Predicting Brain Density from Number of Facebook Friends (cont.) 608\u003c\/p\u003e \u003cp\u003e\u003cb\u003eUnit 4 Probability (Online) 11-1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 \u003c\/b\u003e\u003cb\u003eModeling Randomness 11-2\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSection 11.1: Basics of Probability 11-3\u003c\/p\u003e \u003cp\u003eExample 11.1: Random Ice Cream Prices 11-3\u003c\/p\u003e \u003cp\u003eExploration 11.1: Random Babies 11-8\u003c\/p\u003e \u003cp\u003eSection 11.2: Probability Rules 11-10\u003c\/p\u003e \u003cp\u003eExample 11.2: Watching Films 11-11\u003c\/p\u003e \u003cp\u003eExploration 11.2: Random Ice Cream Prices (cont.) 11-15\u003c\/p\u003e \u003cp\u003eSection 11.3: Conditional Probability and Independence 11-19\u003c\/p\u003e \u003cp\u003eExample 11.3: Watching Films Revisited 11-20\u003c\/p\u003e \u003cp\u003eExploration 11.3A: College Admissions 11-25\u003c\/p\u003e \u003cp\u003eExploration 11.3B: Rare Disease Testing 11-28\u003c\/p\u003e \u003cp\u003eSection 11.4: Discrete Random Variables 11-30\u003c\/p\u003e \u003cp\u003eExample 11.4: A Game of Chance 11-30\u003c\/p\u003e \u003cp\u003eExploration 11.4: Traffic Lights 11-35\u003c\/p\u003e \u003cp\u003eSection 11.5: Random Variable Rules 11-38\u003c\/p\u003e \u003cp\u003eExample 11.5: A Game of Chance Revisited 11-38\u003c\/p\u003e \u003cp\u003eExploration 11.5: Skee-Ball 11-45\u003c\/p\u003e \u003cp\u003eSection 11.6: Binomial and Geometric Random Variables 11-50\u003c\/p\u003e \u003cp\u003eExample 11.6: Time to Leave the Nest? 11-52\u003c\/p\u003e \u003cp\u003eExploration 11.6: Clueless Quiz 11-59\u003c\/p\u003e \u003cp\u003eSection 11.7: Continuous Random Variables and Normal Distributions 11-63\u003c\/p\u003e \u003cp\u003eExample 11.7: Heights of Adult Women 11-65\u003c\/p\u003e \u003cp\u003eExploration 11.7A: Birthweights 11-69\u003c\/p\u003e \u003cp\u003eExploration 11.7B: Run, Girl, Run! 11-71\u003c\/p\u003e \u003cp\u003eSection 11.8: Revisiting Theory-Based Approximations of Sampling Distributions 11-72\u003c\/p\u003e \u003cp\u003eExample 11.8A: Time to Leave the Nest Revisited 11-74\u003c\/p\u003e \u003cp\u003eExample 11.8B: Intelligence Test 11-75\u003c\/p\u003e \u003cp\u003eExploration 11.8A: Racket Spinning 11-77\u003c\/p\u003e \u003cp\u003eExploration 11.8B: Random Ice Cream Prices (cont.) 11-77\u003c\/p\u003e \u003cp\u003eAppendix A Calculation Details 645\u003c\/p\u003e \u003cp\u003eAppendix B Stratified and Cluster Samples 662\u003c\/p\u003e \u003cp\u003eSolutions to Selected Exercises 666\u003c\/p\u003e \u003cp\u003eIndex 728\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989466857701,"sku":"NP9781119683452","price":111.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119683452.jpg?v=1761784215","url":"https:\/\/k12savings.com\/es\/products\/introduction-to-statistical-investigations-isbn-9781119683452","provider":"K12savings","version":"1.0","type":"link"}