Introduction to Statistics | Mt. San Antonio College (2024)

Introduction to Statistics | Mt. San Antonio College (1)

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.

6 Weeks Access / 24 Course Hrs

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  • Syllabus
  • Requirements
  • Instructor
  • Reviews

$129.00

Introduction to Statistics | Mt. San Antonio College (2)

Self-Guided

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No Instructor. Course begins when you enroll.

Introduction to Statistics | Mt. San Antonio College (3)

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$129.00

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Details

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.

Syllabus

Lesson 1 - What Is Statistics, Anyway?

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.

Lesson 2 - Quantitative Data: From Averages to Z-Scores

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.

Lesson 3 - Displaying Quantitative Data: Dots, Plots, and Histograms

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.

Lesson 4 - Displaying Qualitative Data: Percentages, Charts, and Graphs

"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.

Lesson 5 - Is There a Link? Scatterplots and Correlation

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.

Lesson 6 - Linear Regression: How Can You Predict the Future?

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.

Lesson 7 - What's the Chance of That? Probability Concepts

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.

Lesson 8 - Probability Models: What's Normal?

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.

Lesson 9 - The Key to Inference: Sampling Distributions

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.

Lesson 10 - How Certain Are You? Confidence Intervals for Proportions

"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.

Lesson 11 - Trial by Data: Testing Hypotheses About Proportions

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.

Lesson 12 - Inference About Means

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. You will also find out what the history of statistics has to do with the quality of beer in Ireland.

Requirements

Prerequisites:

There are no prerequisites to take this course.


Requirements:

Hardware Requirements:

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

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.

Instructional Material Requirements:

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

Instructor

Introduction to Statistics | Mt. San Antonio College (6)

Ben Sellers

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.

Reviews

Thank you for teaching this course on statistics. Your lessons were easy to follow and understand. I have learned what I expected to learn from this course and would definitely recommend you to others who would like to either learn or improve their comprehension of statistics.

The teaching style of the instructor is very practical and elegant...All the examples are real, not just a bunch of tables or numbers. It was a delight to quickly read the lessons and not have questions afterwards.

I was taking this class to prep for a Healthcare Stats class. I thought it would be a good introduction and it provided me with much of the terminology and game plan. Thank you for your hard work.

The instructor was great - very responsive and helpful. The course was designed well. I learned a lot and the quizzes prepared me well for the final exam.

I think the course is really good and it is the first time in my life that I was able to understand a standard deviation.

I enjoyed this class very much and the interaction with other classmates. I wish there was an online advanced statistics course to continue.

Thanks for a very good learning experience. I would never have imagined I could understand statistics, and yet you made it very easy. I appreciate all the resources available in case I need to revisit and refresh my memory in the future.

Thank you, Ben! Your course was enjoyable. The information will be very helpful for my job..Thanks also for your questions and comments in the discussion areas, which were very helpful.

Thank you for this interesting, useful and beneficial course. Your explanations of mathematical and statistical concepts are clear, concise, and well-illustrated with examples throughout the Lessons...The examples and assignment problems you present are interesting, practical and represent a diverse variety of matters and issues from all aspects of everyday life. Truly, your course exemplifies how an understanding of and the correct use of statistics are relevant to and can enhance our daily lives. Thank you for using your time, talents, expertise and experience to develop, implement, and offer this course in the online format. It has been an exemplary learning experience.

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Self-Guided Course Code: T9315

Instructor-Moderated Course Code: sta

Introduction to Statistics | Mt. San Antonio College (2024)

FAQs

How hard is introduction to statistics in college? ›

It may be difficult at first, but it is just like learning a new language; once the basics are understood and practiced, it becomes much easier and almost second nature over time. Statistics does not deserve the bad reputation that it has been given because at its core, it is not a very difficult class.

What is taught in intro to statistics class? ›

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.

What is the prerequisite for intro to statistics? ›

Before you take statistics, it is a good idea to brush up on the foundational knowledge you'll need in the course. For example, an algebra course is often a prerequisite for statistics classes, so if it's been a while since you've taken that course, you may want to refresh your algebraic skills in advance.

What is the introduction of statistics? ›

Statistics in Mathematics is the study and manipulation of data. It involves the analysis of numerical data, enabling the extraction of meaningful conclusions from the collected and analyzed data sets.

Is statistics harder than calculus? ›

Some students might find Calculus harder, while others might struggle more with Statistics. It's highly personal, so talk to your teachers and peers to help you make the best decision.

What is the easiest math class in college? ›

Easiest Math Class in College?
  1. College Algebra: This class covers basic algebra topics and mainly reviews concepts you've likely learned in high school algebra courses. ...
  2. Statistics: Introductory statistics courses usually don't require much advanced math, and they focus on concepts that apply to various disciplines.
Feb 18, 2024

How to pass college statistics? ›

To pass college statistics, understanding the core concepts and applying them through practice problems is key. Developing effective study strategies, seeking help when needed, and staying engaged in class discussions are vital components of learning how to pass college statistics.

What is the hardest math class? ›

The most difficult math courses I have encountered thus far have included advanced calculus, abstract algebra, and topology (and they will generally only continue to get more challenging each semester).

What math is needed for statistics? ›

Differential and integral calculus, linear algebra, and probability theory are used in statistics' mathematical ideas.

What is the easiest way to learn statistics? ›

Focus on concepts, not formulas.

It's easier to learn statistical concepts – what each formula means and what it can help you figure out – rather than long, complicated formulas. Focus on learning the concepts behind the formulas – you can always look up the formulas later.

How employable is a statistics degree? ›

The Bureau of Labor Statistics projects 31.6% employment growth for statisticians between 2022 and 2032. In that period, an estimated 10,500 jobs should open up. Statisticians practice the science of using data to make decisions.

What is taught in intro to statistics? ›

Topics include Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons.

Is college statistics hard? ›

If you want to excel at your studies, it is important to have a thorough understanding of statistics. However, regardless of how important statistics is, it can be challenging at times. Many students are deathly afraid of anything math-related and actively seek out chances to escape it.

Is statistics a science or art? ›

Answer: Statistics is both science and art. Statistical methods are systematic and have a general application which makes it a science. Further, the successful application of these methods requires skills and experience of using the statistical tools. These aspects make it an art.

Is statistics a hard class in college? ›

If you want to excel at your studies, it is important to have a thorough understanding of statistics. However, regardless of how important statistics is, it can be challenging at times. Many students are deathly afraid of anything math-related and actively seek out chances to escape it.

Is beginning statistics hard? ›

Most people find it difficult, yes. It involves a lot of math but is different from math because you have to deal with probabilities instead of exact numbers. Most people find that conceptually challenging. You'll do fine, though, if you have an analytical mind and diligently study the material.

Is Introduction to Statistical Learning good for beginners? ›

An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning. This book is appropriate for anyone who wishes to use contemporary tools for data analysis.

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