R Programming Language-Anonlive
Understand the Now – Predict the Future!
Time series analysis and forecasting is one among the key fields in statistical programming. It allows you to
see patterns in time series data
model this data
finally make forecasts based on those models
Due to modern technology the amount of available data grows substantially from day to day. Successful companies know that. They also know that decisions based on data gained in the past, and modeled for the future, can make a huge difference. Proper understanding and training in statistic analysis and forecasting will offer you the facility to know and make those models. This can make you an invaluable asset for your company/institution and will boost your career!
What will you learn in this course and how is it structured?
You will study alternative ways in how you’ll handle date and time data in R. Things like time zones, leap years or different formats make calculations with dates and time especially tricky for the programmer. You will study POSIXt classes in R Base, the chron package and particularly the lubridate package.
You will learn how to visualize, clean and prepare your data. Data preparation takes an enormous a part of some time as an analyst. Knowing the best functions for outlier detection, missing value imputation and visualization can safe your day.
After that you’ll study statistical methods used for statistic . You will hear about autocorrelation, stationarity and unit root tests.
Then you will see how different models work, how they are set up in R and how you can use them for forecasting and predictive analytics. Models taught are: ARIMA, exponential smoothing, seasonal decomposition and simple models acting as benchmarks. Of course all of this is accompanied with plenty of exercises.
Where are those methods applied?
In nearly any quantitatively working field you will see those methods applied. Especially econometrics and finance love time series analysis. For example stock data features a time component which makes this type of knowledge a major target for forecasting techniques. But of course also in academia, medicine, business or marketing techniques taught in this course are applied.
Is it hard to understand and learn those methods?
Unfortunately learning material on statistic Analysis Programming in R is sort of technical and wishes plenty of prior knowledge to be understood.
With this course it’s the goal to form understanding modeling and forecasting as intuitive and straightforward as possible for you.
While you would like some knowledge in statistics and statistical programming, the course is supposed for people without a serious during a quantitative field like math or statistics. Basically anybody handling time data on a daily basis can enjoy this course.
Learn R Programming by doing!
There are many R courses and lectures out there. However, R features a very steep learning curve and students often get overwhelmed. This course is different!
This course is actually step-by-step. In every new tutorial we repose on what had already learned and move one extra breakthrough .
After every video you learn a replacement valuable concept that you simply can apply directly . and therefore the better part is that you simply learn through live examples.
This training is full of real-life analytical challenges which you’ll learn to unravel . a number of these we’ll solve together, some you’ll have as homework exercises.
In summary, this course has been designed for all skill levels and albeit you’ve got no programming or statistical background you’ll achieve success during this course!
I can’t wait to ascertain you in school ,
Who this course is for:
This course is for you if you would like to find out the way to program in R
This course is for you if you’re uninterested in R courses that are too complicated
This course is for you if you would like to find out R by doing
This course is for you if you wish exciting challenges
You WILL have homework during this course so you’ve got to be prepared to figure thereon