How to Learn Statistics: Best Classes, Books, and Other Resources

 

WhatIs Statistics?

Statistics is a way to understand data. By using mathematical analysis and data collection, statistics is used to develop and study various aspects of sets of data. Everything from collecting to interpreting, analyzing, and presenting data is covered in statistics.

You don’t have to be a mathematician to use statistics. In fact, this is one field we see in almost every aspect of our lives. 

Even something as simple as investing your money or trying to figure out if your favorite sports team has a chance at winning their next game often involves statistics.

WhatIs Statistics Used For?

Statistics is a field not often thought of as used in the real world, but it is found in a surprising number of industries. From quality testing to predicting disease outbreaks, learning statistics is important.

  • Quality Testing. It is well-known that most companies perform quality tests on their products, but have you ever thought about statistics working behind-the-scenes? By conducting focus groups and random sampling tests, companies use statistics to determine product quality quite frequently.
  • Weather Forecasting. We always joke about how the weathermen never accurately report the weather, but the truth is they use statistical methods to draw conclusions. This means that while they are often correct in their forecasts, there is no way to be 100 percent certain when using probabilities to make predictions.
  • Emergency Preparedness. While we aren’t always able to predict natural disasters and their severity, using statistics, emergency managers can use previously collected data to gain an idea of what conditions are likely to cause natural disasters and how severe they will be.
  • Predicting Diseases. Every year during the flu season, millions of people receive flu shots. These shots are meant to prevent people from contracting the flu, but since there are two strains, scientists use statistics to predict which strain will be more prevalent each year and give the correlating flu shot.

Typesof Statistics

While any expert in statistics will tell you how important it is to learn all of the different types of statistics, they will also tell you how important it is to be able to differentiate between them. 

The two biggest types of statistics you will need to learn are descriptive statistics and inferential statistics.

DescriptiveStatistics

Descriptive statistics is the most common type of statistics. This type uses numbers to describe patterns and features within sets of data. Within descriptive statistics, there are two subtypes: measures of central tendency and measures of spread.

Using measures of central tendency, you will find yourself working with the mean, median, mode, and range of a data set to draw conclusions. On the other hand, using measures of spread, you will find yourself using standard deviation, variance, and frequency distribution, amongst other things.

InferentialStatistics

In inferential statistics, scientists have to use more complex mathematical processes to gain insights into the relationships between random variables within a population. Since individual variables cannot all be examined, scientists use statistical samples and sampling distributions to more conveniently study data.

As with descriptive statistics, there are two subsets within inferential statistics: confidence intervals and hypothesis testing. Confidence intervals use a range of values to study statistical samples from a population, while hypothesis testing uses various tests such as chi-squares and t-tests to determine if a theory about a population is correct.

LearningStatistics

Whether you want to learn statistics to aid in learning predictive analytics, decide between data science vs statistics, or simply for your own personal use, we have you covered. You can use any combination of the following resources to create your own custom-learning plan.

Since there is no right way to learn statistics, we suggest determining what type of learner you are and make a game plan from there. That plan may include in-person or online courses, reading books, or simply watching free online tutorials, and as long as it helps you learn, you’ll be ready to go.

How Long Does It Take to Learn Statistics?

Since there is no one way to learn statistics, it only makes sense that there is no one time frame, either. If you choose to learn statistics on your own and devote six to eight hours a day to your studies, you can become a master statistician in just a couple of months.

However, if you decide to enroll in a college degree program, it will take anywhere from two to four years, depending on your degree. There are also plenty of people who learn on their own and take years to become statistics masters. It all depends on your learning type and goals.

Howto Learn Statistics: Step-by-Step

Even though there are dozens of different paths you can take to become a statistics master, this step-by-step guide provides an outline that can be used in any of those paths. 

  1. Take Math Courses in High School. If you are lucky enough to realize you want or need to learn statistics while still in high school, take advantage of that. Take as many upper-level math courses as you can before graduation to get a head start.
  2. Begin to Learn Basics. While there are total math whizzes out there, most people struggle to learn statistics by just diving in. Take some time to familiarize yourself with the basics before trying to learn anything complex.
  3. Enroll in Descriptive Statistics Courses. After learning the basics, you’ll want to take courses focusing on descriptive statistics. This is generally considered the easier-to-learn type of statistics, and you will need to understand this type before moving to inferential statistics.
  4. Enroll in Inferential Statistics Courses. Once you have mastered descriptive statistics, you can begin to learn the more complex inferential statistics. Enroll in classes or watch tutorials focusing on this more difficult type of statistics.
  5. Learn About Predictive Models. Finally, after mastering both descriptive and inferential statistics, you can begin focusing on predictive models. Learning about models such as ANOVA, linear regression, and logistic regression requires a good understanding of the topics covered in both descriptive and inferential statistics.

 

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