数据科学学习指导
https://www.zhihu.com/question/20176089
想做数据处理尤其是大数据量处理的相关工作必须兼具 计算机科学基础和统计基础。
强烈推荐:Distance Education § Harvard University Extension School 和哈佛的学生一起学习Data Science。
https://www.zhihu.com/question/20176089
想做数据处理尤其是大数据量处理的相关工作必须兼具 计算机科学基础和统计基础。
强烈推荐:Distance Education § Harvard University Extension School 和哈佛的学生一起学习Data Science。
Public economics (or economics of the public sector) is the study of government policy through the lens of economic efficiency and equity. At its most basic level, public economics provides a framework for thinking about whether or not the government should participate in economics markets and to what extent its role should be. In order to do so, microeconomic theory is utilized to assess whether the private market is likely to provide efficient outcomes in the absence of governmental interference. Inherently, this study involves the analysis of government taxation and expenditures. This subject encompasses a host of topics including market failures, externalities, and the creation and implementation of government policy. Public economics builds on the theory of welfare economics and is ultimately used as a tool to improve social welfare.
Broad methods and topics include:
Emphasis is on analytical and scientific methods and normative-ethical analysis, as distinguished from ideology. Examples of topics covered are tax incidence optimal taxation and the theory of public goods
1、运行 cmd;
2、输入 mpm命令,打开MikTex Package Manager界面;
3、进入Repository菜单,选择Change Package Repository…命令;
4、从Change Package Repository窗口中选择Packages shall be installed from the Internet, 点击下一步;
5、选择一个可连接的地址(第一可用)进行同步;
6、等待数据库同步完成;
7、同步完成后,在Name中输入algorithm并确定;
8、鼠标右击algorithms记录选择,Install选项即可。(此处为已安装状态,所以为灰色状态。
cite from others: http://www.library.illinois.edu/learn/research/proposal.html
Guidelines on writing a research proposal
by Matthew McGranaghan
This is a work in progress, intended to organize my thoughts on the process of formulating a proposal. If you have any thoughts on the contents, or on the notion of making this available to students, please share them with me. Thanks.
Assume we want to investigate some problem by statistical method, and we have data D. several possible statistical models are $M_1$, $M_2$…The number of models could be quite large. For example, if we consider only regression models but are unsure about which of $p$ possible predictors to include, there could be as many as $2^p$. BMA uses Bayesian statistics to select possible candidate predictors and help use construct the right model.
In developing countries, people who are farmer are very special. Because they earn at least part of their livelihood through work in their own enterprises(the land). At the same time, they also can consume a portion of their product(they grow crops, harvest them, sell them or eat them). We know that due to the unique feature of agriculture, household labour is often an important input into the production process of the farmer’s production activity. Consequently, Consequently, individuals make simultaneous decisions about production (the level of output, the demand for factors, and the choice of technology) and consumption (labor supply and commodity demand). This mixture just describes common daily life of most families in developing countries and provides starting point (Agricultural Household Model) for our analysis.
下载Sublime Text 2
安装
按Ctrl + ` 打开console
粘贴代码到console并回车
重启Sublime Text 2
import urllib2,os;pf=’Package Control.sublime-package’;ipp=sublime.installed_packages_path();os.makedirs(ipp) if not os.path.exists(ipp) else None;open(os.path.join(ipp,pf),’wb’).write(urllib2.urlopen(‘http://sublime.wbond.net/'+pf.replace(‘ ‘,’%20’)).read())
definition: The term ‘treatment effect’ refers to the causal effect of a binary (0–1) variable on an outcome variable of scientific or policy interest.
The term ‘treatment effect’ originates in a medical literature concerned with the causal effects of binary, yes-or-no ‘treatments’, such as an experimental drug or a new surgical procedure.
Economics examples include the effects of government programmes and policies, such as those that subsidize training for disadvantaged workers, and the effects of individual choices like college attendance.
Given a data-set describing the labour market circumstances of trainees and a non-trainee comparison group, we can compare the earnings of those who did participate in the programme and those who did not. Any empirical study of treatment effects would typically start with such simple comparisons.
In general, omitted variables bias (also known as selection bias) is the most serious econometric concern that arises in the estimation of treatment effects. The link between omitted variables bias, causality, and treatment effects can be seen most clearly using the potential-outcomes
In general, omitted variables bias (also known as selection bias) is the most serious econometric concern that arises in the estimation of treatment effects. The link between omitted variables bias, causality, and treatment effects can be seen most clearly using the potential-outcomes
framework.