Statistical Analysis Course
14 Online Courses
Statistical Tools in Microsoft Excel1h 14m
Machine Learning - Statistics Essentials8h 01m
Statistics for Data Science using Python3h 56m
Statistics Essentials for Analytics - Beginners1h 07m
Predictive Modeling using SPSS13h 37m
Skills you will master
- Linear Algebra
- Gradient Descent
- Predictive Analysis
- Random Forest
- Grid Search
- Adaboost Regressor
- Affinity Propagation Model
- Gaussian Mixture Model
- Heuristic Search
- Color Models
- Image Loading
- Image Thresholding
- R Programming
- Business Analyics
- Data Science
- Machine Learning
Online Statistical Analysis Course
This Statistical Analysis Course includes 14 comprehensive statistical analysis courses with 124+ hours of video tutorials and Lifetime Access. You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of the 14 courses.
Statistics is a very important course for someone who wants to become a business analyst, data engineer or data scientist. With the advent of machine learning and artificial intelligence, the scope of statistician and statistic professionals have grown a lot.
Currently, a lot of online courses are available for teaching statistics to interested people and each of these courses has their own advantages and disadvantages. Most of these courses introduce one programming language and the imparts all its content based on the examples using that programming language. This Statistical Analysis course being discussed here has a slight advantage compared to all other generic courses in the sense that it teaches more than one programming language. It covers R, Python, SAS, SPSS, Minitab, and Excel. Thus, it is quite comprehensive.
- About Statistical Analysis Course
- Statistical Analysis Course Curriculum
- Certificate of Completion
- Pre-requisites to Statistical Analysis Course
- Sample Preview of this Statistical Analysis Course
- Target Audience for this Statistical Analysis Course
- Online Statistical Analysis Course FAQs – General Questions
- Career Benefits of this Statistical Analysis Certification
- Online Statistical Analysis Course Review / Testimonials
About Statistical Analysis Course
|Course Name||Online Statistical Analysis Course Bundle|
|Deal||You get access to all 14 courses bundle. You do not need to purchase each course separately|
|Hours||124+ Video Hours|
|Core Coverage||This Statistical Analysis course will help you learn statistical tools, and concepts using Tableau, SPSS, Minitab, SAS, Eviews and data science statistics|
|Course Validity||Lifetime Access|
|Eligibility||Anyone who is serious about learning statistical analysis and wants to make a career in analytics|
|Pre-Requisites||Basic knowledge of statistics and data analysis|
|What do you get?||Certificate of Completion for each of the 14 courses|
|Certification Type||Course Completion Certificates|
|Verifiable Certificates?||Yes, you get verifiable certificates for each course with a unique link. These link can be included in your Resume/Linkedin profile to showcase your enhanced skills|
|Type of Training||Video Course – Self Paced Learning|
|System Requirement||1 GB RAM or higher|
|Other Requirement||Speaker / Headphone|
Online Statistical Analysis Course Curriculum
To make things easy for you, here’s a comprehensive Statistical analysis course. Before we ever talk about the target audience, FAQs, let’s look at the course curriculum in detail –
|Serial No.||Course Name||Course Description|
|1||Statistical tools in Excel||This Statistical Analysis course is a little more than 1-hour long. It teaches concepts such as excel basics, mean, median mode in excel, data analysis tool kit, correlation and regression, histogram, moving average etc.|
|2||Learn visual analytics using Tableau||This Statistical Analysis course is 9 hours long. It introduces Tableau and then goes on the show all important functionalities of tableau such as dimensions and measures, plots, data handling etc. It consists of several examples and case studies where the user learns the best ways to use Tableau.|
|3||Business analytics using R||This Statistical Analysis course module is more than 15 hours long. It covers sufficient details of R programing language and how business analytics can be done in R. data types, basic functions of R, libraries and functions, conditional statements, data manipulation and testing etc. are taught in R using examples from business analytics domain.|
|4||Business analytics using SAS||This 11 hours long module, covers ideas from SAS domain. SAS in a well-known and highly in use software for statistical analysis and in this module, students learn all important functionalities of SAS such as data source handling, data validation, data transformation, data manipulation etc. with a lot of examples and use cases.|
|5||Quantitative finance using SAS||This one is a rather short module. This goes for about 4 hours where the user learns about quantitative analysis aspects of SAS. Concepts of the t-test, correlation, regression, multiple regression etc. are discussed.|
|6||Predictive modeling using SAS enterprise miner||This Statistical Analysis course module is about 10 hours long and here students learn about predictive modeling using SAS software. SAS tables, sample statistics, SAS PM EM combination etc. are taught in this module.|
|7||Beginners training Eviews||This module is 6 hours long and it teaches introduction to Eviews, Eview GUI, generating log returns, interpretation and graphs etc. This module is very important for those who want to do econometric data analysis.|
|8||Getting started Splunk||This Statistical Analysis course module is about 9 hours long and, in this module, students learn about Splunk, Splunk map-reduce, Splunk apps and searching the app, Splunk commands, visualization etc.|
|9||Predictive modeling using Minitab||This module is long and has a duration of more than 16 hours. It teaches a very popular statistical analysis tool, Minitab which is in use for many decades now. Minitab basics, various options in Minitab, connecting different data source, data manipulation and deploying algorithms such as linear regression and logistic regression are covered.|
|10||Predictive modeling using SPSS||SPSS is another very popular software for statistical analysis. In this Statistical Analysis course which is about 14 hours long, SPSS concepts such as data import, data handling, linear regression, multiple linear regression etc. are covered.|
|11||Advanced Eviews||This 17 hours long module, teaches the advanced concepts of Eviews after the basics are already covered in one of the above modules. Here users learn about correlation analysis, time series data, VAR modeling, unit root testing etc.|
|12||Machine learning python basic tutorials||Python is a very fundamental language for machine learning and its popularity is continuously increasing. In this module which is 8 hours long, the students are taught about python syntax, various machine learning libraries of python and examples using python code and syntax.|
|13||Statistics data science using Python||This module is 3 hours long where the sole focus in statistical concepts only. Users learn about mean, median, mode, variance, standard deviation, statistics for data science etc.|
|14||Statistics essentials for beginners||In this short video, essential concepts of statistics such as random variables, variable types, graphical representation, sampling techniques etc. are discussed. This module is 1-hour long.|
Certificate of Completion
What is Statistical Analysis?
Statistical analysis is the science of extracting patterns from data, usually numbers. This statistical analysis course teaches a lot of ideas from standard statistic courses from graduate and post-graduate level. Users can expect to lean following skills from this Statistical Analysis course which are data manipulation & statistics basics, data merging, data creation and modification, examples of merge, statistics definition, variables and its types, calculating variance and standard deviation, calculating covariance and correlation, cumulative frequency, histograms and scatter plot, control flow in statistics, probability & probability distribution, Bayes theorem, random variable & its examples, discrete and continuous example, exponential distribution with practice problem and examples, expected value of distribution, gambling and monte hall problem, deal or no deal problem, distribution in advanced details, expected value of distribution such as binomial and normal, ANOVA, Chi-square test etc.
Predictive Modeling is also taught in this Statistical Analysis course and it aims to provide and improve predictive Modeling skills across many business domains. Quantitative methods such as time series analysis and predictive Modeling such as linear regression are taught. These concepts could be extensively utilized in understanding the customer behavior, churn analysis, financial markets movements and share price forecasting, and studying drugs and its effects in medicine and pharma sectors.
Which tangible skills you will learn in this Statistical Analysis course?
This Statistical Analysis course teaches important skills that can be implemented in practice from day one. Any analysis project starts with data understanding and analysis and the methods taught in this course is directly used there. Specific skills that the users will learn are the following: –
- Data manipulation skills
- Data transformation skills
- Data understanding and pattern understanding skills
- Linear regression
- Logistic regression
- Prediction and forecasting skills
- Time series analysis etc.
All these skills are used by the business analyst and data scientists on a daily basis. These are the skills which can land you a job in your desired field of data science.
Pre-requisites to Statistical Analysis Course
Following are the pre-requisite for this Statistical Analysis course: –
- Students should be comfortable with mathematics. You need not to be an expert in it, but you should be able to follow the underlying concepts. Being good with probability is very much beneficial as it makes the course 50% easier. A general rule of thumb is if you enjoyed studying mathematics in high school, you should be fine with this course.
- Familiarity with at least one programming language. Knowledge of coding and some hands-on exposure with one language is mandatory. It could be any language C, Java, C# anything.
- Other than that, there is no hard and fast pre-requisite. Users from any domain such as any field of study or work can join this Statistical Analysis course and understand its content if they meet the above two criteria.
Target Audience for this Statistical Analysis Course
This Statistical Analysis course is suitable for a wide range of audience. Students or working professionals from engineering, science, commerce, management and even medicine domains are suitable for this course. Some of the relevant degrees are B. Tech, M. Tech, BCA, MCA, MBA, B. Sc, BS, MS etc. The Statistics course is suitable for entry-level professionals, seasoned experts, managers, business leaders as well as graduate students. As long as the pre-requisite mentioned above are satisfied, anyone can join this course and can benefit out of it.
Statistical Analysis Course FAQ’s- General Questions
Some common questions always asked by students before enrolling for this Statistical Analysis course is mentioned here for better and quicker decision making.
Is this statistical analysis course sufficient for working as a data scientist?
This course provides a foundation. It covers everything from a statistic perspective. But, to become a data scientist, you also need to learn machine learning algorithms, NLP and deep learning which is not covered in this Statistical Analysis course. Students can enroll for those courses separately at our portal.
Can this Statistical Analysis course help me with a certification?
Yes. The course provides a certification which is very reputable and also can be verified by employers for authenticity and correctness.
How much time would I need to devote to this course each week?
Usually, students need to spend 6-8 works per week, but it is totally flexible and if somebody wants to spend 20 hours per week or only 2 hours per week, that is also doable, and they can finish the course at their own pace and comfort.
How is going to be the scope of this Statistical Analysis course 5 years down the line?
Demand for machine learning and AI professionals are only going to increases in time to come. Many surveys predict manifold increases in job creation in this domain. So, there is a huge scope for such skills in the market today and in time to come.
Career Benefits of this Statistical Analysis Course
This Statistical Analysis Course provides many benefits such as it helps you to switch jobs by learning a new skill. It helps you earn more by either switching job or getting a promotion or working part-time in this domain. Many people also choose to work as a freelancer in their free time. Many start their own blog or website or make YouTube tutorials. This Statistical Analysis course helps a fresh graduate land into their first job, it helps the manager to hire right talent by teaching them what questions to ask during an interview and it teaches business leaders important skills that they can use to expand to a new market or build new businesses. This course and the skills taught here are the pivots of modern software engineering industries which no longer thrive on mundane programming or system designing. Intelligence is the key today and such skills which are covered in this course are the nails and hammer of today information technology companies. This Statistical Analysis course is everything that can help someone realize their dream of becoming and staying relevant if this fast-changing world.
Statistical Analysis Course Testimonials
Good course on learning Stats Tools
Arno Wakfer CA
Machine Learning – Statistics Essentials