Introduction to Statistics

Improve your understanding of data and learn how to develop graphs and charts. With real-world applications and easy-to-understand examples drawn from business, health care, sports, education, and politics, this course provides the skills and knowledge you need to start analyzing data.
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6 Weeks / 24 Course Hrs
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Course code: sta

Do you need an introduction to statistics or maybe just a refresher? Do you want to improve your understanding of data and use it to make decisions? If you're looking for help with statistics, this online statistics course is for you!

With easy-to-understand examples combined with real-world applications, this course provides you with the skills and knowledge you need to start analyzing data. You will learn how to use, collect, and apply data to real-life problems with charts, numbers, and graphs.

Beyond that, you will learn ways to visualize and measure relationships to make forecasts and predictions. Throughout the course, you will use real data and a variety of examples drawn from business and industry, health care, sports, education, politics, and the social sciences.

What you will learn

  • Learn about data and data collection practices
  • Learn to summarize and describe data with charts, numbers, and graphs
  • Discover how to calculate and interpret probabilities and then see how they apply to decision making when you're faced with uncertainty
  • Learn ways to visualize and measure relationships in data
  • Develop ways to use data to make forecasts and predictions
  • Understand statistical inference and what it means for a result to be statistically significant

How you will benefit

  • Become more efficient and accurate in reporting on data for your organization
  • Understand how to better interpret the accuracy of data others are presenting and add more value to your team
  • Use this course as a starting point to a career involving data analysis and predictions
  • Become more confident in your ability to make tough decisions based on data presented

How the course is taught

  • Instructor-led or self-paced online course
  • 6 Weeks or 3 Months access
  • 24 course hours

What do you know about statistics? How do you collect reliable data and use it to make informed decisions? In this lesson, you will learn some of the concepts and terms needed throughout the course. You will also find out how statistics affect events in the news and in your everyday life.

Once you have a set of data, how can you summarize and interpret it to figure out what it really means? In this lesson, you will learn to summarize data and describe its center along with its variability. You will see how statistics play a part in medicine, human resources, education, politics, finance, and marketing.

Is there an easier way of understanding data than peering at column after column of numbers? Yes. In this lesson, you will see quantitative data displayed in dot plots, histograms, and many other forms. Knowing how to read and construct these graphs will help you see patterns and spot unusual values in data.

"How much satisfaction do you get from your friendships?" "Which mountain is most dangerous to climb?" This lesson focuses on summarizing and displaying qualitative data from questions like these. You will use charts and tables to analyze real world examples in business, medicine, and more.

Is there a link between the poverty rate and the crime rate? Is your score on a math exam related to your anxiety level? This lesson looks at relationships between two quantitative variables. You will learn to make scatterplots and describe what you see.

Can you predict the next world-record time in the mile run? How can you forecast CO2 levels in the atmosphere? This lesson dives into describing and measuring association between variables. You will use linear regression to find an equation that models the data and use the equation to make predictions.

What's the chance you will have a coin come up "heads" five times in a row? This lesson explores the basics of probability. You will learn the rules that govern probability and see how to apply them in a variety of situations.

What should you expect to happen in a game involving chance? How can you estimate the probability that a healthy baby will be born underweight? This lesson focuses on probability models and expected value. You will learn about the most common probability model in statistics: the normal model.

How do you move beyond the sample at hand to make predictions and draw conclusions about the population? In this lesson, you will discover the key that lets you make inferences about the population. You will see the most important result in all of statistics—the central limit theorem.

"The margin of error for this poll is plus or minus 3%." What does that mean, anyway? This lesson introduces statistical inference and focuses on confidence intervals for proportions. You will learn to calculate the margin of error and use it to build an interval for estimating a population proportion.

Is there really a home team advantage in sports? Did that television ad your company bought result in increased awareness of your product? In this lesson, you will learn to answer questions such as these by testing an appropriate hypothesis using proportions.

How do you test hypotheses about means? For example, can you use a confidence interval to estimate the average number of hours Americans use the Internet each week? Your last lesson introduces inference for means. You will learn to calculate and interpret confidence intervals and hypothesis tests for a mean. And you will find out what the history of statistics has to do with the quality of beer in Ireland.

Ben Sellers has more than 17 years of teaching experience both online and in the traditional classroom. He has taught college students, working professionals, adult learners, and K-12 students. He has also taught a wide variety of students in the medical field, including lab technicians, nurses, pharmacists, and aspiring physicians. Sellers holds undergraduate and graduate degrees in the mathematical sciences and has worked as a mathematical and statistical consultant.

Requirements:

Hardware Requirements:

  • This course can be taken on either a PC or Mac.

Software Requirements:

  • PC: Windows 8 or later.
  • Mac: macOS 10.6 or later.
  • Browser: The latest version of Google Chrome or Mozilla Firefox are preferred. Microsoft Edge and Safari are also compatible.
  • Adobe Acrobat Reader.
  • Software must be installed and fully operational before the course begins.

Other:

  • Email capabilities and access to a personal email account.

Prerequisites:

There are no prerequisites to take this course.

Instructional Material Requirements:

The instructional materials required for this course are included in enrollment and will be available online.

Instructor-Led: A new session of each course begins each month. Please refer to the session start dates for scheduling.
Self-Paced: You can start this course at any time your schedule permits.

Instructor-Led: Once a course session starts, two lessons will be released each week for the 6 week duration of your course. You will have access to all previously released lessons until the course ends.
Self-Paced: You have 3 month access to the course. After enrolling, you can learn and complete the course at your own pace, within the allotted access period.

Instructor-Led: The interactive discussion area for each lesson automatically closes two weeks after each lesson is released, so you're encouraged to complete each lesson within two weeks of its release.
Self-Paced: There is no time limit to complete each lesson, other than completing all lessons within the allotted access period.

Instructor-Led: The final exam will be released on the same day as the last lesson. Once the final exam has been released, you will have two weeks plus 10 days (24 days total) to complete the final and finish any remaining lessons in your course. No further extensions can be provided beyond these 10 days.
Self-Paced: Because this course is self-paced, no extensions will be granted after the start of your enrollment.