[Chapter 1 Introduction Welcome to the course, learning you have any questions please ask and answer in the Q & A area, I wish a happy learning! ]
This chapter describes the thinking of statistics, the overall framework of statistics, statistical learning what's the use, as well as close ties statistical and machine learning; and learning form of this course is to explain the (+ visual programming) and the need to have knowledge and skills to be explained, so that everyone from the start of the course, really learn to statistics! ...
Chapter 2 [data necessary know the basics, you can not skip]
data is subject statistical analysis, and the data is variable composition. This chapter explains what data and variables, and the type and scale of measurement variables. The basic concept is the cornerstone of statistical analysis.
Chapter 3 describes statistics [core, focusing on learning]
This chapter describes the knowledge of descriptive statistics for different types of variables to explain the relationship between visualization methods of its main features and common digital data features characterize or two variables.
Chapter 4 describes the statistical programming [chapters focus on combat, it is recommended to follow the teacher with knock code to achieve]
This chapter previous chapter the knowledge to carry out the implementation code, so that everyone on the knowledge and application consolidation.
Chapter 5 probability and probability distributions [key chapter, the probability must master the Knowledge]
This chapter explains the basic concepts and properties of probability, which is a cornerstone of statistical inference, learning discrete and continuous random variables and their distribution.
Chapter 6 samples and sampling distributions [distribution key chapter, the sample mean]
if we want to understand the wage level of the whole Chinese programmers, but it can not get all the data, how to do it? Statistics, we collect some random data (sample), to construct a sample function (statistics), and distribution of statistics (sampling distributions) linked, so as to estimate population parameters and the uncertainty of provide a basis for characterization. ...
Chapter 7 parameter estimation and interval estimation [point]
Usually we can not accurately informed population parameters (such as whole Chinese programmers average wage). In statistics, the information we provide through the sample to estimate the overall situation. We can either use a digital (point estimate) as an overall estimate, you can use an interval (interval estimate) represents the overall parameters of the possible range. ...
Chapter 8 Hypothesis Testing Method] [frequencies on
the name implies, hypothesis testing is the process of validating assumptions. For example, we assume there are two interrelated: equal to the average wage programmers A (null hypothesis) vs average wage programmer is not equal to (greater than or less than) A. Based on our estimate of the overall sample obtained, it can be assumed that the numbers A to be compared, so accept or reject the null hypothesis. In this process, we can also make mistakes probability (such as incorrectly rejected the null hypothesis) control. ...
analysis of variance [Chapter 9 than the comparative method two population means]
the last chapter we explain the single overall (such as the average programmer salary is equal to a certain value) and two overall test (such as the national male programmer salary is higher than the national female programmer salary). In this chapter we will show you how to disassemble and analyze more complex data structures (such as gender and educational background of these two factors affect how interactive programmer salary). ...
Chapter 10 Regression Analysis [heavy and difficult, it is recommended to look at the video]
In many cases, between the data / variables are interrelated and influence. For example, we not only care about the programmer's salary is how much, we are also concerned about whether and how wages vary with gender, education and other factors, whether this change is regulated by other factors (such as age) and so on. In this chapter, we not only explain how to use regression analysis depicts the relationship between the variables, we will go to re-examine the method of hypothesis testing from the perspective of regression analysis. In addition, we will also explore the system ...
Chapter 11 [heavy and difficult non-parametric test, please carefully study]
In previous chapters, we do a basic statistical inference is that we know from the overall distribution (such as the overall normal distribution) in which, but we do not know the overall distribution of certain parameters (such as mean or variance), then we use the information obtained based on a sample of the population involved in estimating and testing. However, there are times when we do not know what overall distributed from, how to do it? Let's take a non-parametric tests. ...
Chapter 12 focuses on Bayesian statistics [master the method, please learn]
based on hypothesis testing frequency is first considered null hypothesis (model) is correct, then accept or reject the null hypothesis by information obtained from a sample . So, if we have multiple models at the same time, and want to know based on existing data, which model is most likely to be correct, to how to do it? Bayesian statistics not only provides a method to solve these problems for us and allows us with the accumulation of data and model the correct possibility to be updated. ...
Chapter 13 broader statistical world to apply their knowledge [I wish you]
Congratulations to everyone we completed this course of. This chapter will review and sort out the students learned in this course in statistical knowledge, strengthen the statistical way of thinking, and talk about the wider world statistics. I wish you full harvest, happy learning!
Download: Statistics courses designed specifically for programmers