Updated June 15, 2023
Introduction to Statistics Certifications
Organizations are being deluged with numerical and non-numerical data and information. All of us in our day-to-day routine use numbers in our calculations. Problems in business contain a great degree of quantitative elements in the form of facts and figures. Managers need to carry out data analysis and interpretation for effective decisions. In this context, they must prepare quantitative arguments to justify their choices. Decision-making using statistical methods is the answer to accomplishing this purpose. This statistics Certifications Course provides the foundations for building competency in statistical thinking.
Top 10 Statistics Certifications Course
There are many options on the internet that will help you learn Statistics Certifications Course for free and many certification courses through which you can get a certificate. Whether you want to make a switch in your carrier or prepare for any Statistics Certifications Course or learn some extra skills to help with your job, or you are just interested in a subject and want to learn more, there will be an online course that you can take to help you achieve your goals.
Data Analysis and Statistical Inference
Duke University / Courses provide Data Analysis and Statistical Inference. The main objective of the Statistics Certifications Course is to teach the students how to analyze and visualize in R and create reports in R; students will be able to understand what statistical inference is and will be able to implement them using the frequency and Bayesian statistical inference models to understand the phenomenon thereby making data-driven decisions, communicate statistical results correctly, effectively and wrangle and visualize data with R packages for data analysis.
Benefits: Students will not only receive the certificate but will also work on a capstone project and have access to other capstone projects hosted on Duke University’s website.7
Intro to Statistics
The Intro to Statistics Certifications Course is taught by Professor Sebastian Thrun and is a free online course that Udacity provides. In this Statistics Certifications Course, one will learn to see relationships in data and to predict based on them, Simpson’s paradox, Probability; Bayes Rule, and Correlation vs. Causation; students are also taught the Maximum Likelihood Estimation, the three M’s of statistics denoting Mean, Median, Mode, Standard Deviation, Variance, Outliers, Quartiles; Binomial Distribution, Central Limit Theorem, Manipulating Normal Distribution, Confidence Intervals, Hypothesis Testing, Linear regression, and correlation.
Benefits: This course is free, no need to pay anything. The Statistics Certifications Course being presented by one of the world’s top universities is a very good place to start learning Statistics Certifications. At the end of the course, a course completion exam has to be written, after which they are handed the course completion certificate.
Stanford University provides the Statistical Learning course. In this Statistics Certifications Course, the students will be taught about one of the machine learning methods, “supervised learning, “which will mainly focus on regression and classification methods, the different types of regression linear, polynomial, and logistic regression. Students will also learn LDA, which stands for linear discriminant analysis, which includes cross-validation and bootstrap. Various model selection techniques (ridge and lasso), including the nonlinear models. The splines and generalized additive models and tree-based methods. Machine learning techniques like random forests and boosting and the widely used support-vector machines.
Benefits: This course is for free, and the students get a certificate of completion; if one scores more than 90%, then Stanford University will provide a distinction in the course.
Introduction to Probability Theory
The Statistics Certifications Course is an introduction to probability theory is provided by Saylor Academy. The Statistics Certifications Course familiarizes the students with the concepts of probability, sample space, events, and probability functions. Using combinations to evaluate the probability of outcomes in coin-flipping experiments, calculate the probability of union and intersection of events and conditional probability, apply Bayes’ theorem to simple situations, calculate the expected values of discrete and continuous random variables, determine the distribution of the sums of random variables, calculate cumulative distributions and marginal distributions, use random processes to model and predict phenomena governed by binomial, multinomial, geometric, exponential, normal, and Poisson distributions and explain and use the law of large numbers and the central limit theorem.
Benefits: One of the best open source curriculum of the entire probability theories, which are available in the form of videos and PDFs. After completing the Statistics Certifications Course, one will become a master of probability and its theories.
Become a statistical Modeler.
The course “Become a statistical modeler” is provided by EDUCBA. In this course, students will learn about EViews – Introductory Economics Modeling, EViews Advanced, Financial Analytics, Data Analytics with QlikView, Statistical tools with Excel, Analytics using Tableau, QM for Windows – Analytics using QM, Predictive Modelling using Minitab, Predictive Modelling using SPSS, Business Analytics using R Hands-on, SAS- Business Analytics using SAS.
Benefits: One of the most promising full packed Statistics Certifications Course out there is EDUCBA’s “Become a Statistical Modeler”. This course will cover every analytics tool out there in the market, including Excel, SAS, SPSS, Tableau, Minitab, QlikView, and R.
Future Prospects of Statistics Certifications
- “Big data,” “data science,” whatever the buzzword of the moment is … data sets are growing exponentially, and that doesn’t show any sign of slowing down. We need efficient procedures for performing thousands or millions of simultaneous tests on trillions of data points. Right now, the answer is all too often to throw inherently inefficient (in the computational sense) methods at the data, which I think is a recipe for frustration. Statisticians need to learn to think like computer scientists, not just casual programmers.
- A related problem with the above is the “curse of dimensionality” or “large p, small n” problem. The data may be getting bigger, but the number of samples per experimental unit often isn’t. Inferences made from these data sets are very error-prone and wildly variable between analyses. New methods need to be invented which can produce not on reliable results but also consistent results.
- Causal inference is the most methodologically exciting field in statistics. If we can prove that maximum correlation is not causation, we can actually overthrow the hoary maxim because a lot of data sets contain enough information to allow us to remove all the causal relationships from just the observational data. And there is a whole lot of observational data out there—much more than experimental data, and there always will be—that is absolutely prime for this kind of analysis.
There is a projected growth in employment in the field of Statistics Certifications by around 34 percent from 2016-2024, which is far higher than other occupations’ growth. As the field of Statistics Certifications is widespread from healthcare to banking to any other field, including policy decisions, the growth will be phenomenal. The data is going to play a huge role in the coming years and will shape the future of all businesses.
This is a guide to the Best Statistics Certifications. Here we discuss the introduction, the top 10 certification statistics course, and the top best statistics certifications. You may also look at the following articles to learn more –