Udemy Coupon, (APL 2019), Online Courses Free, 100% Off

Udemy - Statistics with R - Beginner Level

$20 Free 100% Off

Lectures 46
Length 3 hours
Skill Level Beginner Level
Languages English
Published 3/2016

Udemy Coupon Code : GLOBAL

Description

If you want to learn how to perform the basic statistical analyses in the R program, you have come to the right place.

Now you don’t have to scour the web endlessly in order to find how to compute the statistical indicators in R, how to build a cross-table, how to build a scatterplot chart or how to compute a simple statistical test like the one-sample t test. Everything is here, in this course, explained visually, step by step.

So, what will you learn in this course?

First of all, you will learn how to manipulate data in R, to prepare it for the analysis: how to filter your data frame, how to recode variables and compute new variables.

Afterwards, we will take care about computing the main statistical figures in R: mean, median, standard deviation, skewness, kurtosis etc., both in the whole population and in subgroups of the population.

Then you will learn how to visualize data using tables and charts. So we will build tables and cross-tables, as well as histograms, cumulative frequency charts, column and mean plot charts, scatterplot charts and boxplot charts.

Since assumption checking is a very important part of any statistical analysis, we could not elude this topic. So we’ll learn how to check for normality and for the presence of outliers.

Finally, we will perform some basic, one-sample statistical tests and interpret the results. I’m talking about the one-sample t test, the binomial test and the chi-square test for goodness-of-fit.

So after graduating this course, you will know how to perform the essential statistical procedures in the R program. So… enroll today!

Udemy - Learn Statistics from Basics

$200 Free 100% Off

Lectures 19
Length 2 hours
Skill Levels Beginner Level
Languages English
Published 7/2017

Udemy Coupon Code : STAT-BEGINNING

Take This Course

Description

If you take a lot of exams in school, how do you measure your actual performance? How do you compare yourself to other students? Who is the best basketball/soccer/baseball/… player of all times? If you take a blood test and you have values that are higher than the average, should you be worried? All these things are based on descriptive statistics. It is the art of taking lots of information, down to one small number: either the average/median or standard deviation.

Let us take it to a next step. You are a store manager with only one good in your shop. You have monthly data on the sales and the price. If you increase the price, sales drop by X%. If you decrease the price, sales drop by X%. How wonderful would it be that you drew some sort of line (ps: it’s a regression line) that would fit the data well. Why? Because you get a more educated guess what will happen your sales if you change the price. You are in the area of regression models.

Let us take it (many steps) further. You have data on stock prices and other variables. Can you construct some sort of model that will give you an estimate/prediction of the stock price tomorrow, based on the values of certain variables today. Who wouldn’t want that? You can do this via several methods: predictive analysis, markov swithcing models, nonlinear regression models,… The list is endless and the possibilities are endless (although they are more advanced). It can also be interesting just to see how variables relate to one another (but this is not nearly as profitable as the first example).

Why is statistics important? It is based on two elements: inference and prediction. If you are interested in how variables are connected with each other and how the relations are, you have inference. If you want to predict future values, you are obviously in the area of prediction. That is the reason why one would estimate the function of some sort of data set.

How do you make a decision? We use our gut some, but ideally, we want it to be based on information. Data is important, because sometimes our gut is very very wrong. But also, the more you understand statistics, the better your gut feelings get.

First we have to learn how to gather information. If you gather the information incorrectly, it’s worthless.

Once you learn how to collect good data, how do we organize it? How do we summarize and describe it in a way that becomes meaningful and easier to deal with? How do we visualize it?

Now that we have our information and we’ve organized it, what conclusions can be drawn? A set of numbers can tell many different stories, how do you make it tell the truth? What are its limitations? What additional information do we need to make our decision?

Sure, there are areas where statistics is used more formally. Namely business, science, and engineering. But really any time there are decisions to be made, whether they’re personal decisions or professional ones, a solid understanding of statistics can ultimately help you make better ones.

The bottom line is that statistics education can be tailored to your unique path. The first step is simply enrolling in a statistics course, whether you’re a high school or college student, and then opening yourself to its power and potential.

So, welcome to this course on Statistics. We will guide you through all the concepts and make sure that you will in Statistics by the end of this course, along with thorough practice.

Let's get started!