Introduction to Concepts in Statistics | Introduction to basic concepts of statistics using an original research article on sleep and learning; introduction to visualization and basic graphing in Excel. |

Data Structure | Introduction to data types to characterize numeric and categorical data; visualization and effective communication of data. |

Measures of Centrality and Dispersion | Introduction to measures of centrality and dispersion in samples: mean, median, percentiles, variance, and standard deviation. |

The Normal Distribution | Introduction to the normal distribution: the module utilizes Chapter 6 of the online Collaborative Statistics. |

Estimating the Mean and Variance of a Normal Distribution | Properties of the arithmetic average of a sample from a normally distributed population and discussion of Law of Large Numbers. |

Logarithmic Transformations | Logarithmic transformations of data leads to straight lines when data is displayed that fit power functions or exponential functions. |

Cancer: A Global View | Project that uses Gapminder to find relationships among cancer data. |

Confidence Intervals | Construction and interpretation of confidence intervals; introduction to polls. |

Calibration | This module can be used parallel to a chemistry lab where students collect data to obtain a calibration curve. The student will learn how to find the calibration curve in Excel, use it to calculate the value of the independent variable, and determine the uncertainty. |

Sensitivity and Specificity | Sensitivity and specificity are important concepts to characterize the discrimination ability of diagnostic tests. Using authentic data, students will explore the concepts of sensitivity and specificity. |

Hypothesis Testing | Introduction to statistical hypothesis testing, including type I and type II errors. The students will perform tests using exact calculations. Students will also perform simulations that illustrate how resampling methods can be used to construct statistical tests. |

Testing Means | Introduction to Z-test and t-test. Includes authentic data. |

The Chi‐Square Test for Goodness of Fit | Introduction to chi-square test. Includes authentic data. |

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