## Teaching Statistics: A Bag of TricksStudents in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part II gives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling. |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Contents

1Introduction | |

12 Fitting demonstrations examples and projects into a course | |

13 What makes a good example? | |

14 Why is statistics important? | |

15 The best of the best | |

Part IIntroductory probability andstatistics | |

2First week of class | |

22 Where are the cancers? | |

93 A nonlinear model for golf putting | |

94 Pythagoras goes linear | |

10Lying with statistics | |

102 Selection bias | |

103 Reviewing the semesters material | |

104 1 in 2 marriages end in divorce? | |

105 Ethics and statistics | |

Part IIPutting it all together | |

23 Estimating a big number | |

24 Whats in the news? | |

25 Collecting data from students | |

3Descriptive statistics | |

32 Time series | |

33 Numerical variables distributions and histograms | |

34 Numerical summaries | |

35 Data in more than one dimension | |

36 The normal distribution in one and two dimensions | |

37 Linear transformations and linear combinations | |

38 Logarithmic transformations | |

4Linear regression and correlation | |

42 Correlation | |

43 Regression to the mean | |

5Data collection | |

52 Class projects in survey sampling | |

53 Experiments | |

54 Observational studies | |

6Statistical literacy and thenews media | |

61 Introduction | |

63 Assignment where students find their own articles | |

64 Guidelines for finding and evaluating sources | |

65 Discussion and student reactions | |

66 Examples of course packets | |

7Probability | |

73 Probabilities of compound events | |

74 Probability modeling | |

75 Conditional probability | |

76 You can load a die but you cant bias a coin flip | |

8Statistical inference | |

distributions of totals and averages | |

examples | |

theory | |

z t and χ2 tests | |

86 Simple examples of applied inference | |

87 Advanced concepts of inference | |

9Multiple regression andnonlinear models | |

92 Exam scores | |

11How to do it | |

112 Inclass activities | |

113 Using exams to teach statistical concepts | |

114 Projects | |

115 Resources | |

12Structuring an introductory statistics course | |

122 Finding time for student activities in class | |

123 A detailed schedule for a semesterlong course | |

124 Outline for an alternative schedule of activities | |

Part IIIMore advanced courses | |

13Decision theory and Bayesianstatistics | |

131 Decision analysis | |

132 Bayesian statistics | |

14 Student activities in surveysampling | |

142 Random number generation | |

143 Estimation and confidence intervals | |

144 A visit to Clusterville | |

145 Statistical literacy and discussion topics | |

146 Projects | |

15Problems and projects inprobability | |

152 Introductory problems | |

153 Challenging problems | |

154 Does the Poisson distribution fit real data? | |

155 Organizing student projects | |

156 Examples of structured projects | |

157 Examples of unstructured projects | |

158 Research papers as projects | |

16Directed projects in amathematical statistics course | |

161 Organization of a case study | |

162 Fitting the cases into a course | |

quality control | |

helicopter design | |

1642 Designing the study and fitting a response surface | |

Notes and further reading | |

References | |

Author Index | |

### Other editions - View all

### Common terms and phrases

15 minutes activities analysis answer approximately ask the students assignments average Bayesian Bayesian statistics bias biased binomial distribution blackboard cards Chapter class discussion classroom cluster sample coin flips compared confidence intervals correlation data collection data dredging decision decision problems demonstration depression described in Section dice display error estimate exam scores example expected experiment Gelman give grades graph guess handouts height helicopter histogram homework hypothesis test ideas illegal immigrants illustrate instructor interesting introductory statistics lecture linear regression logarithmic lurking variable Markov chain mathematical mean measurements methods midterm exam newspaper article Nolan normal distribution observational studies paper patients population problem projects proportion questions random digits random numbers random sample San Francisco Examiner scatterplots semester sequence shows soda standard deviation statistical literacy statistically significant statistics class statistics course survey teaching telephone numbers topic typically women write