This book introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. They help you grasp concepts and cement your comprehension by using simple notation-frequently substituting words for symbols.
This book introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. They help you grasp concepts and cement your comprehension by using simple notation-frequently substituting words for symbols.
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Inhaltsangabe
From the contents: 1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS. 1.1 Three Reasons to Study Statistics. 1.2 The Nature and Role of Variability. 1.3 Statistics and the Data Analysis Process. 1.4 Types of Data and Some Simple Graphical Displays. 2. COLLECTING DATA SENSIBLY. 2.1 Statistical Studies: Observation and Experimentation. 2.2 Sampling. 2.3 Simple Comparative Experiments. 2.4 More Experimental Design. 2.5 More on Observational Studies: Designing Surveys. 2.6 Interpreting and Communicating the Results of Statistical Analyses. 3. GRAPHICAL METHODS FOR DESCRIBING DATA. 3.1 Displaying Categorical Data: Comparative Bar Charts and Pie Charts. 3.2 Displaying Numerical Data: Stem-and-Leaf Displays. 3.3 Displaying Numerical Data: Frequency Distributions and Histograms. 3.4 Displaying Bivariate Numerical Data. 3.5 Interpreting and Communicating the Results of Statistical Analyses. 4. NUMERICAL METHODS FOR DESCRIBING DATA. 4.1 Describing the Center of a Data Set. 4.2 Describing the Variability in a Data Set. 4.3 Summarizing a Data Set: Boxplots. 4.4 Interpreting Center and Variability: Chebyshev's Rule, the Empirical Rule, and z Scores. 4.5 Interpreting and Communicating the Results of Statistical Analyses. 5. SUMMARIZING BIVARIATE DATA. 5.1 Correlation. 5.2 Linear Regression: Fitting a Line to Bivariate Data. 5.3 Assessing the Fit of a Line. 5.4 Nonlinear Relationship and Transformations. 5.5 Logistic Regression. 5.6 Interpreting and Communicating the Results of Statistical Analyses. 6. PROBABILITY. 6.1 Interpreting Probabilities and Basic Probability Rules. 6.2 Probability as a Basis for Making Decisions. ...
From the contents: 1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS. 1.1 Three Reasons to Study Statistics. 1.2 The Nature and Role of Variability. 1.3 Statistics and the Data Analysis Process. 1.4 Types of Data and Some Simple Graphical Displays. 2. COLLECTING DATA SENSIBLY. 2.1 Statistical Studies: Observation and Experimentation. 2.2 Sampling. 2.3 Simple Comparative Experiments. 2.4 More Experimental Design. 2.5 More on Observational Studies: Designing Surveys. 2.6 Interpreting and Communicating the Results of Statistical Analyses. 3. GRAPHICAL METHODS FOR DESCRIBING DATA. 3.1 Displaying Categorical Data: Comparative Bar Charts and Pie Charts. 3.2 Displaying Numerical Data: Stem-and-Leaf Displays. 3.3 Displaying Numerical Data: Frequency Distributions and Histograms. 3.4 Displaying Bivariate Numerical Data. 3.5 Interpreting and Communicating the Results of Statistical Analyses. 4. NUMERICAL METHODS FOR DESCRIBING DATA. 4.1 Describing the Center of a Data Set. 4.2 Describing the Variability in a Data Set. 4.3 Summarizing a Data Set: Boxplots. 4.4 Interpreting Center and Variability: Chebyshev's Rule, the Empirical Rule, and z Scores. 4.5 Interpreting and Communicating the Results of Statistical Analyses. 5. SUMMARIZING BIVARIATE DATA. 5.1 Correlation. 5.2 Linear Regression: Fitting a Line to Bivariate Data. 5.3 Assessing the Fit of a Line. 5.4 Nonlinear Relationship and Transformations. 5.5 Logistic Regression. 5.6 Interpreting and Communicating the Results of Statistical Analyses. 6. PROBABILITY. 6.1 Interpreting Probabilities and Basic Probability Rules. 6.2 Probability as a Basis for Making Decisions. ...
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