About the Authors |
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xix | |
Acknowledgements |
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xxi | |
How to Use This Book |
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xxii | |
Starting with Four Big Pictures |
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xxv | |
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1 Why Do We Need Statistics? |
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1 | (10) |
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3 | (1) |
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4 | (1) |
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5 | (2) |
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7 | (4) |
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11 | (18) |
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13 | (1) |
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Phase 1 Ideas, Hypotheses and Design |
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13 | (7) |
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Phase 2 Evidence, Analysis and Inference |
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20 | (2) |
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Phase 3 Results, Presenting and Persuading |
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22 | (7) |
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29 | (26) |
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31 | (3) |
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Variability and Variables |
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34 | (3) |
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37 | (2) |
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Types of Measurement Value |
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39 | (3) |
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42 | (1) |
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43 | (5) |
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48 | (1) |
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49 | (6) |
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4 Relationships between Variables |
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55 | (30) |
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What Is a Relationship between Variables? |
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57 | (1) |
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The Logic of Relationships |
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57 | (4) |
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61 | (9) |
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The Strength of a Relationship: Effect Sizes |
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70 | (9) |
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Effect Sizes in Psychology |
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79 | (1) |
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Relationships, Statistics and Variability |
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80 | (5) |
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85 | (76) |
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91 | (24) |
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Why is Uncertainty Important? |
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93 | (1) |
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93 | (1) |
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Variability: Possible Samples from One Population |
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93 | (9) |
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Uncertainty: Possible Populations with One Sample |
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102 | (7) |
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109 | (6) |
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6 Null Hypothesis Testing |
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115 | (24) |
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The Logic of Null Hypothesis Testing |
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117 | (7) |
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Likelihood Functions and Null Hypothesis Testing |
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124 | (1) |
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The Consequences of Null Hypothesis Testing |
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125 | (3) |
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A Conversation about Testing for Null Effects |
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128 | (3) |
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131 | (1) |
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131 | (8) |
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7 Statistical Tests for One Independent Variable |
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139 | (22) |
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The Logic of a Statistical Test |
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141 | (2) |
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The Specific Statistical Tests |
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143 | (12) |
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155 | (6) |
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INTERMEZZO 2 TAILS - ONE, TWO OR MANY? |
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161 | (66) |
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8 Minimising Uncertainty: Research Design |
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167 | (20) |
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A Brief Recap of Uncertainty |
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169 | (1) |
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Planning Ahead: Predictions |
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169 | (6) |
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Using Expected Outcomes to Check a Design |
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175 | (5) |
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180 | (1) |
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181 | (1) |
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A General Framework for Design Decisions |
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182 | (5) |
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9 Measurements and Uncertainty |
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187 | (14) |
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Decision 1 Measurement Type |
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189 | (1) |
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Decision 2 Measurement Values |
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190 | (3) |
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193 | (4) |
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197 | (4) |
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10 Sampling and Uncertainty |
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201 | (26) |
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Decision 1 Recruiting Participants |
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203 | (3) |
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Decision 2 How to Use Participants |
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206 | (3) |
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Decision 3 How Many Participants? |
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209 | (3) |
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Pitfalls in Sampling Design |
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212 | (6) |
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218 | (1) |
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Practical Matters - or How (Not) to Cheat |
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219 | (8) |
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INTERMEZZO 3 REPLICATION AND META-ANALYSIS |
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227 | (86) |
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11 Hypotheses with More than One Independent Variable |
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235 | (22) |
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237 | (2) |
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Idea 1 Main Effects - Separate Relationships for Each IV |
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239 | (5) |
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Idea 2 Interactions - One IV Switches the Effect of Another |
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244 | (7) |
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251 | (6) |
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12 Covariations: Relationships between Two Independent Variables |
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257 | (18) |
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Step 1 Total Effect Sizes |
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259 | (2) |
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Step 2 Unique Effect Sizes |
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261 | (2) |
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The Two Meanings of Covariation |
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263 | (1) |
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Another Example of Covariation |
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264 | (5) |
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269 | (6) |
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13 Analysing Data with Two or More Independent Variables |
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275 | (20) |
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Different Ways to Describe Effect Sizes |
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277 | (1) |
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277 | (7) |
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284 | (3) |
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287 | (1) |
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The Historical Statistical Tests |
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288 | (2) |
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290 | (5) |
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295 | (18) |
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297 | (2) |
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A New Concept: Statistics for Building and Comparing Models |
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299 | (2) |
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Thinking about Causation in Models |
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301 | (1) |
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302 | (1) |
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303 | (2) |
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305 | (2) |
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307 | (1) |
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A Summary: Bigger and Bigger Pictures |
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307 | (6) |
Finishing with One Bigger Picture |
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313 | (4) |
References |
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317 | (2) |
Index |
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319 | |