Statistics Course

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.