Test Bank Statistics in Context 1st Edition by Barbara Blatchley
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Test Bank Statistics in Context 1st Edition by Barbara Blatchley
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Test Bank Statistics in Context 1st Edition by Barbara Blatchley
Statistics in Context offers a fresh approach to teaching statistics. Designed to reduce students fear of numbers, the text aims to put statistics-wary readers at ease with uncomplicated explanations and practical examples drawn from real research and everyday life.
ISBN-10 : 0190278951
ISBN-13 : 978-0190278953
Barbara Blatchley (Author)
Table Of Contents
STATISTICS IN CONTEXT
CONTENTS IN BRIEF
CONTENTS
FIGURES, TABLES, AND BOXES
PREFACE
INTRODUCING . . . Statistics in Context
ACKNOWLEDGMENTS
CONTENTS OVERVIEW
CHAPTER ONE: INTRODUCTION: STATISTICS-WHO NEEDS THEM?
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
WHAT ARE STATISTICS?
TYPES OF STATISTICS
The Historical Context: ROLL THEM BONES
DESCRIPTIVE STATISTICS
INFERENTIAL STATISTICS
VARIABLES
INDEPENDENT AND DEPENDENT VARIABLES
Think About It . . . : HOW A TAN AFFECTS ATTRACTIVENESS
CHANCE ERROR
USING STATISTICS
SOME CAUTIONARY NOTES ABOUT STATISTICS
STATISTICS IN CONTEXT
SUMMARY
TERMS YOU SHOULD KNOW
WRITING ASSIGNMENT
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
Introducing SPSS: The Statistical Package for the Social Sciences
CHAPTER TWO: TYPES OF DATA
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
DATA, DATA EVERYWHERE
SCALES OF MEASUREMENT
QUALITATIVE DATA
The Historical Context: S. S. STEVENS AND HIS POWER LAW
QUANTITATIVE DATA
Think About It . . .: SCALES OF MEASUREMENT
ORGANIZING DATA
FREQUENCY DISTRIBUTIONS
UNGROUPED FREQUENCY DISTRIBUTIONS
Think About It . . . FREQUENCY DISTRIBUTIONS (PART 1)
GROUPED FREQUENCY DISTRIBUTIONS
Think About It . . .: FREQUENCY DISTRIBUTIONS (PART 2)
SCALES OF MEASUREMENT IN CONTEXT
. . . AND FREQUENCY DISTRIBUTIONS
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
WRITING ASSIGNMENT
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
Getting Data into Your Stats Program
Reading in Data with SPSS
Reading in Data with R
CHAPTER THREE: A PICTURE IS WORTH A THOUSAND WORDS: CREATING AND INTERPRETING GRAPHICS
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
VISUALIZING PATTERNS IN DATA
The Historical Context WILLIAM PLAYFAIR AND THE USE OF GRAPHICS IN PUBLISHING
BAR CHARTS AND HISTOGRAMS
DISCRETE DATA
CONTINUOUS DATA
STEM-AND-LEAF GRAPHS
FREQUENCY POLYGONS
PIE CHARTS
Think About It . . . INTERPRETING GRAPHICS
OTHER GRAPHICS
GRAPHING MEANS
GRAPHING RELATIONSHIPS
GRAPHING TIME
GRAPHICS IN CONTEXT: RULES FOR CREATING GOOD GRAPHS
RULES FOR CREATING A GOOD GRAPH
SUMMARY
TERMS YOU SHOULD KNOW
WRITING ASSIGNMENT
A NOTE ON GRAPHING WITH STATISTICAL SOFTWARE
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
GRAPHING WITH SPSS AND R
Graphing with SPSS
Graphing with R
CHAPTER FOUR: MEASURES OF CENTRAL TENDENCY: WHAT’S SO AVERAGE ABOUT THE MEAN?
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
MEASURES OF CENTER
MEASURES OF CENTER: WHAT IS TYPICAL?
The Historical ContextADOLPHE QUETELET AND THE “AVERAGE MAN”
THE MODE AND THE MEDIAN
FINDING THE POSITION OF THE MODE
FINDING THE POSITION OF THE MEDIAN
THE MEAN
MODE, MEDIAN, AND MEAN: WHICH IS THE “BEST” MEASURE OF CENTER?
Think About It . . . ESTIMATING MEASURES OF CENTER
SHAPES OF DISTRIBUTIONS
NORMAL DISTRIBUTIONS
FINDING CENTER WITH GROUPED DATA
Think About It . . . SHAPES OF DISTRIBUTIONS
MEASURES OF CENTER IN CONTEXT
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
WRITING ASSIGNMENT
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
CHAPTER FIVE: VARIABILITY: THE “LAW OF LIFE”
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
MEASURING VARIABILITY
CONSISTENCY AND INCONSISTENCY IN DATA
The Historical Context WHAT IS THE SHAPE OF THE EARTH?
MEASURES OF VARIABILITY
THE RANGE
THE INTERQUARTILE RANGE
GRAPHING THE IQR
THE VARIANCE
AVERAGE DEVIATION FROM THE MEAN
THE STANDARD DEVIATION
FINDING THE VARIANCE IN A POPULATION
FINDING THE STANDARD DEVIATION IN A POPULATION
FINDING STANDARD DEVIATION IN A POPULATION VERSUS A SAMPLE
FINDING VARIANCE AND STANDARD DEVIATION: AN EXAMPLE
Think About It . . . THE RANGE RULE
STANDARD DEVIATION IN CONTEXT
DESCRIPTIVE STATISTICS IN CONTEXT
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
WRITING ASSIGNMENT
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
DESCRIPTIVE STATISTICS WITH SPSS AND R
Descriptive Statistics with SPSS
Descriptive Statistics with R
CHAPTER SIX: WHERE AM I? NORMAL DISTRIBUTIONS AND STANDARD SCORES
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
STATISTICS SO FAR
STANDARD SCORES
The Historical Context ALFRED BINET AND INTELLIGENCE TESTING
THE Z-SCORE
THE “3-SIGMA RULE”
PROPORTIONS IN THE STANDARD NORMAL CURVE
THE BENEFITS OF STANDARD SCORES
COMPARING SCORES FROM DIFFERENT DISTRIBUTIONS
CONVERTING A Z-SCORE INTO A RAW SCORE
CONVERTING A PERCENTILE RANK INTO A RAW SCORE
Think About It . . . THE RANGE RULE REVISITED
STANDARD SCORES IN CONTEXT
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
WRITING ASSIGNMENT
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
CHAPTER SEVEN: BASIC PROBABILITY THEORY
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
PROBABILITY
PROBABILITY AND FREQUENCY
BASIC SET THEORY
The Historical Context: THE GAMBLER’S FALLACY
CONDITIONAL PROBABILITY
COMBINING PROBABILITIES
USING PROBABILITY
Think About It . . . PROBABILITY THEORY AND CARD GAMES
PROBABILITY IN CONTEXT
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
CHAPTER EIGHT: THE CENTRAL LIMIT THEOREM AND HYPOTHESIS TESTING
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
INTRODUCTION: ERROR IN STATISTICS
INFERENTIAL STATISTICS
THE SCIENTIFIC METHOD
The Historical Context: KINNEBROOK’S ERROR AND STATISTICS
THE CENTRAL LIMIT THEOREM
MEASURING THE DISTRIBUTION OF LARGE SETS OF EVENTS
THE LAW OF LARGE NUMBERS AND THE CENTRAL LIMIT THEOREM
Think About It . . . THE LAW OF LARGE NUMBERS AND DICE GAMES
DRAWING SAMPLES FROM POPULATIONS
THE SAMPLING DISTRIBUTION OF THE MEANS
THE THREE STATEMENTS THAT MAKE UP THE CENTRAL LIMIT THEOREM
RANDOM SAMPLING
USING THE CENTRAL LIMIT THEOREM
ESTIMATING PARAMETERS AND HYPOTHESIS TESTING
THE NULL AND ALTERNATIVE HYPOTHESES
DIRECTIONAL HYPOTHESES
HYPOTHESIS TESTING IN CONTEXT
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
CHAPTER NINE: THE Z-TEST
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
ERROR REVISITED
The Historical Context: THE TRIAL OF THE PYX
HOW DIFFERENT IS DIFFERENT ENOUGH? CRITICAL VALUES AND P
ASSUMPTIONS IN HYPOTHESIS TESTING
THE OUTER 5%: THE REJECTION REGION
Think About It . . . P-VALUES AND ALPHA LEVELS
FINDING THE Z-VALUE IN A NONDIRECTIONAL HYPOTHESIS
THE Z-TEST
ANOTHER EXAMPLE
STATISTICS AS ESTIMATES
ON BEING RIGHT: TYPE I AND TYPE II ERRORS
AN EXAMPLE
p-VALUES
INFERENTIAL STATISTICS IN CONTEXT: GALTON AND THE QUINCUNX
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
WRITING ASSIGNMENT
PRACTICE PROBLEMS
Think About It . . .
REFERENCES
CHAPTER TEN: T-TESTS
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
INFERENTIAL TESTING SO FAR
WILLIAM GOSSET AND THE DEVELOPMENT OF THE T-TEST
“STUDENT’S” FAMOUS TEST
The Historical Context STATISTICS AND BEER
THE SINGLE-SAMPLE T-TEST
DEGREES OF FREEDOM
WHEN BOTH σ AND μ ARE UNKNOWN
INDEPENDENT-SAMPLES T-TEST
THE STANDARD ERROR OF THE DIFFERENCE
FINDING THE DIFFERENCE BETWEEN TWO MEANS: AN EXAMPLE
FINDING THE DIFFERENCE BETWEEN MEANS WITH UNEQUAL SAMPLES
ASSUMPTIONS
Think About It . . . T-TESTS AND SAMPLE SIZE
DEPENDENT-SAMPLES T-TESTS
INTRODUCTION
USING A DEPENDENT-SAMPLES T-TEST: AN EXAMPLE
CALCULATIONS AND RESULTS
Think About It . . . T-TESTS AND VARIABILITY
T-TESTS IN CONTEXT: “GARBAGE IN, GARBAGE OUT”
SUMMARY
TERMS YOU SHOULD KNOW
GLOSSARY OF EQUATIONS
WRITING ASSIGNMENT
PRACTICE PROBLEMS
USING THE FORMULA FOR UNEQUAL N’S WITH EQUAL N’S
Think About It . . .
REFERENCES
Conducting t-Tests with SPSS and R
t-Tests with SPSS
t-Tests with R
CHAPTER ELEVEN: ANALYSIS OF VARIANCE
OVERVIEW
LEARNING OBJECTIVES
Everyday Statistics
COMPARING MORE THAN TWO GROUPS
ANALYSI