'This course introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and inferential methods. In addition, the course helps students gain an appreciation for the diverse applications of statistics and its relevance to their lives and fields of study. The course does not assume any prior knowledge in statistics and its only prerequisite is basic algebra.'
The course is organized in 4 units:
- 'Unit 1 Exploratory Data Analysis. This is organized into two modules – Examining Distributions and Examining Relationships. The general approach is to provide students with a framework that will help them choose the appropriate descriptive methods in various data analysis situations.
- Unit 2 Producing Data. This unit is organized into two modules – Sampling and Study Design.
- Unit 3 Probability. The unit is a classical treatment of probability and includes basic probability principles, conditional probability, discrete random variables (including the Binomial distribution) and continuous random variables (with emphasis on the normal distribution).
- Unit 4 Inference. This unit introduces students to the logic as well as the technical side of the main forms of inference: point estimation, interval estimation and hypothesis testing. The unit covers inferential methods for the population mean and population proportion, Inferential methods for comparing the means of two groups and of more than two groups (ANOVA), the Chi-Square test for independence and linear regression. The unit reinforces the framework that the students were introduced to in the Exploratory Data Analysis for choosing the appropriate, in this case, inferential method in various data analysis scenarios.
Throughout the course there are many interactive elements. These include: simulations, “walk-throughs” that integrate voice and graphics to explain an example of a procedure or a difficult concept, and, most prominently, computer tutors in which students practice problem solving, with hints and immediate and targeted feedback. The most elaborate of such activities is the “StatTutor,” a tool that supports students as they go through the processes of data analysis while emphasizing the big picture of statistics.'