Hello and welcome to the Saturdays if we are of course begin to allow this course comprises 30 to video
lectures divided into six sections.
When you finish that course we'll know how to run some simple but fundamental statistical analysis in
our program that matelot from the beginning that this course starts from two important assumptions.
First of all I would assume that you already know how to work in R and r ce to you.
You don't have to be an expert in our But you have to know at the least the very basics.
So this is not an art course.
We're not going to talk about variables less vectors Luc's functions mattresses etc..
I assume that you already know this stuff a little bit.
Also you should know how to install and load an our package because we are going to use a lot of packages
during this course.
The second assumption is that you have the basic statistics now for us and you are familiar with the
statistical procedures discussed here.
These are not statistics.
Why no one for us.
So I'm not going to explain you what they mean as the standard deviation are or how history looks like
or how the chi square test works just in case you are not familiar with some of this stuff you kosovska
your statistics that it toward this course is neither on our course nor statistics course which is the
course about using our program in order to perform statistical analysis.
Now let's talk a bit about the structure of this.
In the first section.
You are going to learn how to manipulate daytime or how to filter your data how to recode variables
how to sort data or frames and how to compute new variables from the existing ones.
And the second action we are going to get into the descriptive statistics.
So here you will see how to compute the most of this.
The most important statistic indicators for for a variable using the our program we had the third action
you have to learn how to build tables and cross tables and are using different available packages this
action and before approach is an all important topic how to build charts in our So we will learn how
to visualize our data with histograms frequents a line chart column charts mean plot charts scatterplot
charts but both charts the package we are going to use in this section is DZIEDZIC plot to the fifth
section is about checking assumptions here.
We'll see how the chosen normality assumption with both numerical and graphical map of and how to detect
the presence of Lyra's in our data series and the section number 6 We're going to learn how to around
3 univere analysis.
The Wasatch Fertitta asked the binomial test and the chi square test for goodness of fit.
So after only a few hours of our day you know the sound shows of the statistical analysis in please
keep in mind that the out of each section you will find two PTF documents.
The first document contains all the codes used in that section extracted for from the files.
So you will have all of the code at hand as a reference.
The second section contains practical exercises for the procedure started in that section.
I strongly advise you to actually do though exercises in order to verify your knowledge and improve
your skills.
For the last action of course it contains the text file with the download links for the course resources.
So you will be able to download all the data frames used in the course and see as the format as well.
They are FAEs.
We are going to work with just smash them before getting started.
If you want to become a real aspart in statistical analysis we are.
You should take a look at my other two courses to do it with our intermediate level and statistics with
our advanced the intermediate course covers more complex techniques like by veritie tath correlation
between subjective analysis of various multivariate analysis of various and regression analysis for
the advanced course.
It contains techniques like analysis of covariance with subject analysis of variance plus some really
sophisticated procedures like little GC regression factor analysis correspondence analysis martyrdom
national Schelling cluster analysis or discriminant analysis.
So if you want to take advantage of the power r and learn how to apply some superior analysis techniques
you should check these two courses.
Thank you for being a student and let's get started.