Course Syllabus

Course Description

Examine the properties behind the concepts of probability and statistics by learning how to investigate the relationships between various characteristics of data.

Course Introduction

If you invest in financial markets, you may want to predict the price of a stock in six months from now on the basis of company performance measures and other economic factors. As a college student, you may be interested in knowing the dependence of the mean starting salary of a college graduate, based on your GPA. These are just some examples that highlight how statistics are used in our modern society. To figure out the desired information for each example, you need data to analyze.

The purpose of this course is to introduce you to the subject of statistics as a science of data. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding of complex data sets has been more of a challenge. In this course, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information.

This course will begin with a brief overview of the discipline of statistics and will then quickly focus on descriptive statistics, introducing graphical methods of describing data. You will learn about combinatorial probability and random distributions, the latter of which serves as the foundation for statistical inference. On the side of inference, we will focus on both estimation and hypothesis testing issues. We will also examine the techniques to study the relationship between two or more variables; this is known as regression.

By the end of this course, you should gain a sound understanding of what statistics represent, how to use statistics to organize and display data, and how to draw valid inferences based on data by using appropriate statistical tools.

This course includes the following units:

• Unit 1: Statistics and Data
• Unit 2: Elements of Probability and Random Variables
• Unit 3: Sampling Distributions
• Unit 4: Estimation with Confidence Intervals
• Unit 5: Hypothesis Testing
• Unit 6: Linear Regression

Course Learning Outcomes

Upon successful completion of this course, you will be able to:

• define and apply the meaning of descriptive statistics and statistical inference, describe the importance of statistics, and interpret examples of statistics in a professional context;
• distinguish between a population and a sample;
• calculate and explain the purpose of measures of location, variability, and skewness;
• apply simple principles of probability;
• compute probabilities related to both discrete and continuous random variables;
• identify and analyze sampling distributions for statistical inferences;
• identify and analyze confidence intervals for means and proportions;
• compare and analyze data sets using descriptive statistics, parameter estimation, and hypothesis testing;
• explain how the central limit theorem applies in inference, and use the theorem to construct confidence intervals;
• 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;
• identify and evaluate relationships between two variables using simple linear regression; and
• discuss concepts pertaining to linear regression, and use regression equations to make predictions.

Throughout this course, you will also see learning outcomes in each unit. You can use those learning outcomes to help organize your studies and gauge your progress.

Course Materials

The primary learning materials for this course are articles, lectures, and videos.

All course materials are free to access and can be found in each unit of the course. Pay close attention to the notes that accompany these course materials, as they will tell you what to focus on in each resource, and will help you to understand how the learning materials fit into the course as a whole. You can also see a list of all the learning materials in this course by clicking on Resources in the navigation bar.

Evaluation and Minimum Passing Score

Only the final exam is considered when awarding you a grade for this course. In order to pass this course, you will need to earn a 70% or higher on the final exam. Your score on the exam will be calculated as soon as you complete it. If you do not pass the exam on your first try, you may take it again as many times as you want, with a 7-day waiting period between each attempt. Once you have successfully passed the final exam you will be awarded a free Course Completion Certificate.

There are also end-of-unit assessments in this course. These are designed to help you study, and do not factor into your final course grade. You can take these as many times as you want until you understand the concepts and material covered. You can see all of these assessments by clicking on Quizzes in the course's navigation bar.

Earning College Credit

This course is eligible for college credit via Saylor Academy's Direct Credit Program. If you want to earn college credit, you must take and pass the Direct Credit final exam. That exam will be password protected and requires a proctor. If you pass the Direct Credit exam, you will receive a Proctor Verified Course Certificate and be eligible to earn an official transcript. For more information about applying for college credit, review the guide to college credit opportunities. Be sure to check the section on proctoring for details like fees and technical requirements.

There is a 14-day waiting period between attempts of the Direct Credit final exam. There is no waiting period between attempts for the not-for-credit exam and the Direct Credit exam. You may only attempt each Direct Credit final exam a maximum of 3 times. Be sure to study in between each attempt!

Tips for Success

MA121: Introduction to Statistics is a self-paced course, which means that you can decide when you will start and when you will complete the course. There is no instructor or an assigned schedule to follow. We estimate that the "average" student will take 32 hours to complete this course. We recommend that you work through the course at a pace that is comfortable for you and allows you to make regular progress. It's a good idea to also schedule your study time in advance and try as best as you can to stick to that schedule.

Learning new material can be challenging, so we've compiled a few study strategies to help you succeed:

• Take notes on the various terms, practices, and theories that you come across. This can help you put each concept into context, and will create a refresher that you can use as you study later on.
• As you work through the materials, take some time to test yourself on what you remember and how well you understand the concepts. Reflecting on what you've learned is important for your long-term memory, and will make you more likely to retain information over time.

Technical Requirements

This course is delivered entirely online. You will be required to have access to a computer or web-capable mobile device and have consistent access to the internet to either view or download the necessary course resources and to attempt any auto-graded course assessments and the final exam.

• To access the full course including assessments and the final exam, you will need to be logged into your Saylor Academy account and enrolled in the course. If you do not already have an account, you may create one for free here. Although you can access some of the course without logging in to your account, you should log in to maximize your course experience. For example, you cannot take assessments or track your progress unless you are logged in.
• You will need to download and install the Wolfram CDF Player to complete the interactive labs in the course.
• If you plan to attempt the optional Direct Credit final exam, then you will also need access to a webcam. This lets our remote proctoring service verify your identity, which is required to issue an official transcript to schools on your behalf.