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Break down biostatistics, make sense of complex concepts, and pass your class If you're taking biostatistics, you may need or want a little extra assistance as you make your way through. Biostatistics For Dummies follows a typical biostatistics course at the college level, helping you understand even the most difficult concepts, so you can get the grade you need. Start at the beginning by learning how to read and understand mathematical equations and conduct clinical research. Then, use your knowledge to analyze and graph your data. This new edition includes more example problems with…mehr
Break down biostatistics, make sense of complex concepts, and pass your class
If you're taking biostatistics, you may need or want a little extra assistance as you make your way through. Biostatistics For Dummies follows a typical biostatistics course at the college level, helping you understand even the most difficult concepts, so you can get the grade you need. Start at the beginning by learning how to read and understand mathematical equations and conduct clinical research. Then, use your knowledge to analyze and graph your data. This new edition includes more example problems with step-by-step walkthroughs on how to use statistical software to analyze large datasets. Biostatistics For Dummies is your go-to guide for making sense of it all.
Review basic statistics and decode mathematical equations
Learn how to analyze and graph data from clinical research studies
Look for relationships with correlation and regression
Use software to properly analyze large datasets
Anyone studying in clinical science, public health, pharmaceutical sciences, chemistry, and epidemiology-related fields will want this book to get through that biostatistics course.
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Autorenporträt
Monika Wahi, MPH, CPH, leads the data science consulting firm DethWench Professional Services (DPS). She is also author of 8 LinkedIn Learning courses. John C. Pezzullo, PhD, held academic positions at Wayne State University and George-town University, including in the department of biomathematics and biostatistics.
Inhaltsangabe
Introduction 1 Part 1: Getting Started with Biostatistics 5 CHAPTER 1: Biostatistics 101 7 CHAPTER 2: Overcoming Mathophobia: Reading and Understanding Mathematical Expressions 15 CHAPTER 3: Getting Statistical: A Short Review of Basic Statistics 29 Part 2: Examining Tools and Processes 51 CHAPTER 4: Counting on Statistical Software 53 CHAPTER 5: Conducting Clinical Research 61 CHAPTER 6: Taking All Kinds of Samples 77 CHAPTER 7: Having Designs on Study Design 87 Part 3: Getting Down and Dirty with Data 99 CHAPTER 8: Getting Your Data into the Computer 101 CHAPTER 9: Summarizing and Graphing Your Data 111 CHAPTER 10: Having Confidence in Your Results 129 Part 4: Comparing Groups 139 CHAPTER 11: Comparing Average Values between Groups 141 CHAPTER 12: Comparing Proportions and Analyzing Cross-Tabulations 159 CHAPTER 13: Taking a Closer Look at Fourfold Tables 173 CHAPTER 14: Analyzing Incidence and Prevalence Rates in Epidemiologic Data 191 Part 5: Looking for Relationships with Correlation and Regression 199 CHAPTER 15: Introducing Correlation and Regression 201 CHAPTER 16: Getting Straight Talk on Straight-Line Regression 213 CHAPTER 17: More of a Good Thing: Multiple Regression 233 CHAPTER 18: A Yes-or-No Proposition: Logistic Regression 249 CHAPTER 19: Other Useful Kinds of Regression 271 CHAPTER 20: Getting the Hint from Epidemiologic Inference 291 Part 6: Analyzing Survival Data 299 CHAPTER 21: Summarizing and Graphing Survival Data 301 CHAPTER 22: Comparing Survival Times 317 CHAPTER 23: Survival Regression 327 Part 7: The Part of Tens 349 CHAPTER 24: Ten Distributions Worth Knowing 351 CHAPTER 25: Ten Easy Ways to Estimate How Many Participants You Need 361 Index 369
Introduction 1 Part 1: Getting Started with Biostatistics 5 CHAPTER 1: Biostatistics 101 7 CHAPTER 2: Overcoming Mathophobia: Reading and Understanding Mathematical Expressions 15 CHAPTER 3: Getting Statistical: A Short Review of Basic Statistics 29 Part 2: Examining Tools and Processes 51 CHAPTER 4: Counting on Statistical Software 53 CHAPTER 5: Conducting Clinical Research 61 CHAPTER 6: Taking All Kinds of Samples 77 CHAPTER 7: Having Designs on Study Design 87 Part 3: Getting Down and Dirty with Data 99 CHAPTER 8: Getting Your Data into the Computer 101 CHAPTER 9: Summarizing and Graphing Your Data 111 CHAPTER 10: Having Confidence in Your Results 129 Part 4: Comparing Groups 139 CHAPTER 11: Comparing Average Values between Groups 141 CHAPTER 12: Comparing Proportions and Analyzing Cross-Tabulations 159 CHAPTER 13: Taking a Closer Look at Fourfold Tables 173 CHAPTER 14: Analyzing Incidence and Prevalence Rates in Epidemiologic Data 191 Part 5: Looking for Relationships with Correlation and Regression 199 CHAPTER 15: Introducing Correlation and Regression 201 CHAPTER 16: Getting Straight Talk on Straight-Line Regression 213 CHAPTER 17: More of a Good Thing: Multiple Regression 233 CHAPTER 18: A Yes-or-No Proposition: Logistic Regression 249 CHAPTER 19: Other Useful Kinds of Regression 271 CHAPTER 20: Getting the Hint from Epidemiologic Inference 291 Part 6: Analyzing Survival Data 299 CHAPTER 21: Summarizing and Graphing Survival Data 301 CHAPTER 22: Comparing Survival Times 317 CHAPTER 23: Survival Regression 327 Part 7: The Part of Tens 349 CHAPTER 24: Ten Distributions Worth Knowing 351 CHAPTER 25: Ten Easy Ways to Estimate How Many Participants You Need 361 Index 369
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