STAT 101: Introduction to Statistics

Course Prerequisites

Grade S in Math 090 (Intermediate Algebra) or appropriate score on the department placement test.

Course Description

STAT 101 is an introductory course in statistics intended for students in a wide variety of areas of study. Topics discussed include displaying and describing data, the normal curve, regression, probability, statistical inference, confidence intervals, and hypothesis tests with applications in the real world. Students also have the opportunity to analyze data sets using technology.

Credit is not given for STAT 101 for majors in Mathematics and Computer Science. Extensive computer use required.

Credit Awarded

4 hours of credit (some exceptions noted below)

Credit is not given for STAT 101 if the student has credit for STAT 130.  Credit is not given for STAT 101 for any major in  the Department of Mathematics, Statistics, and Computer Science.

Course Materials

Textbook

The Basic Practice of Statistics by Moore, 8th edition, published by MacMillan.  Custom edition (available only from the UIC Bookstore) includes only sections covered in this course. Note that an Achieve code is required for the course while the printed textbook is optional.

Achieve

An Achieve code linked to your Blackboard account is required for this course.  To ensure your Achieve code is properly linked to your blackboard account you should purchase your Achieve code through the link in Blackboard.  An Achieve code purchased through the link in Blackboard will include an electronic version of the textbook, buying a print copy is optional.

 

Exam Study Guides Heading link

List of Topics Heading link

The following topics are covered in Stat 101
Chapter Topic(s)
1 Picturing Distributions with Graphs
2 Describing Distributions with Numbers
3 The Normal Distributions
4 Scatterplots and Correlation
5 Regression
6 Two-Way Tables
8 Sampling and Biases
9 Experiments
12 Introducing Probability: Basic rules and models
13 General Rules of Probability: Addition, Multiplication, Conditional Probability, Bayes’ Theorem
14 Binomial Distributions
15 Sampling Distributions
16 Confidence Intervals for One Mean
17 Tests of Significance for One Mean
18 Inference in Practice
20 Inference about a Population Mean and t-distributions
21 Inference about Two Population Means
22 Inference about a Population Proportion
23 Inference about Two Population Proportions