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Introduction to Statistics

Purpose of Course  showclose

In this course, you will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge.  You will learn about how statistics and probability work together.  The subject of statistics involves the study of methods for collecting, summarizing, and interpreting data.  Statistics formalizes the process of making decisions, and this course is designed to help you use statistical literacy to make better decisions.  Note that this course has applications for the natural sciences, economics, computer science, finance, psychology, sociology, criminology, and many other fields. We read data in articles and reports every day.  After finishing this course, you should be comfortable evaluating an author’s use of data.  You will be able to extract information from articles and display that information effectively.  You will also be able to understand the basics of how to draw statistical conclusions. This course will begin with descriptive statistics and the foundation of statistics.  You will then learn about probability and random distributions, the latter of which enables us to work with several aspects of random events and their applications.  Finally, you will examine a number of ways to investigate the relationships between various characteristics of data.  By the end of this course, you should have a grasp on what statistics represent, how to use them to organize and display data, and how to test data to make effective conclusions.

Course Information  showclose

Welcome to MA121: Introduction to Statistics. General information about this course and its requirements can be found below.

Course Designers: Shreya Amin and Kyle Whittaker

Primary Resources: This course is composed of a range of different free, online materials. However, the course makes primary use of the following materials:
Requirements for Completion: In order to complete this course, you will need to work through each unit and all of its assigned materials.  Pay special attention to Units 1 and 2, as these lay the groundwork for understanding the more advanced material presented in the latter units.  In order to pass this course, you will need to complete the final exam and earn a 70% or higher.  Your score on the exam will be tabulated as soon as you finish it.  If you do not pass the exam, you may take it again.

Note that you will only receive an official grade on your final exam.  However, in order to adequately prepare for it, you will need to work through the assignments and all the reading material in the course.
 
Time Commitment: This course should take a total of 96.25 hours to complete. Each unit includes a time advisory that lists the amount of time you are expected to spend on it.  These should help you plan your time accordingly. It may be useful to take a look at these time advisories and to determine how much time you have over the next few weeks to complete each unit and set goals for yourself.

Tips/Suggestions: It will likely be helpful to have a calculator on hand for this course.  If you do not own or have access to one, consider using this freeware version.

As you read, take careful notes on a separate sheet of paper.  Mark down any important equations, formulas, and definitions that stand out to you.  These notes will be useful to review as you study for your final exam.

Preliminary Information

Course Resources:  You may either proceed through the resource boxes below to encounter distinct chapters and videos as they should be read and viewed in the context of the course, or you may click to download all course materials now.

Course Videos (zipped MP4's, 1.6 Gb)
Course Pack (PDF, 16.6 Mb)

Khan Academy  
This course features a number of Khan Academy™ videos. Khan Academy™ has a library of over 3,000 videos covering a range of topics (math, physics, chemistry, finance, history and more), plus over 300 practice exercises. All Khan Academy™ materials are available for free at www.khanacademy.org.

 
A version of this course is also available in iTunes U.
Preview the course
 in your browser or view our entire suite of iTunes U courses.

Learning Outcomes  showclose

Upon successful completion of this course, you will be able to:
  • define descriptive statistics and statistical inference;
  • distinguish between a population and a sample;
  • explain the purpose of measures of location, variability, and skewness;
  • calculate probabilities;
  • explain the difference between how probabilities are computed for discrete and continuous random variables;
  • recognize and understand discrete probability distribution functions, in general;
  • identify confidence intervals for means and proportions;
  • explain how the central limit theorem applies in inference;
  • calculate and interpret confidence intervals for one population average and one population proportion;
  • differentiate between Type I and Type II errors;
  • conduct and interpret hypothesis tests;
  • compute regression equations for data;
  • use regression equations to make predictions; and
  • conduct and interpret Analysis of Variance (ANOVA).

Course Requirements  showclose

In order to take this course, you must:

√    have access to a computer;

√    have continuous broadband Internet access;

√    have the ability/permission to install plug-ins or software (Adobe Reader, Flash, etc.);

√    have the ability to download and save files and documents to a computer;

√    have the ability to open Microsoft files and documents (.doc, .ppt, .xls, etc.); and

√    have read the Saylor Student Handbook.

Unit Outline show close


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