Page 233

Page 233. The verb poder. The Verb PODER. The verb PODER means “to be able to” or “can”. The Verb PODER. Remember, in Spanish all verbs have two parts, the stem and the ending. The Verb Poder. For example POD is the stem ER is the ending…thus makes PODER. Stem Changing Verbs.

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:PS

?? . ?????????????(Precipitation with a Compressed Antisolvent, PCA)????????PS/PMMA????????144,000 ?44,000 ?PS ???????85,000 ?36,000?PMMA ???????PS/PMMA ???????????CO2 ?????,?????PS/PMMA ?????????????????????????PS/PMMA ????CO2?????????CO2 ????????????CO2 ???????????????. ?? . ???????,????????????(

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PS 233

2. Evaluating Our Models. Our hypothesis tests tend to focus on individual coefficients t-testsIn addition, we may want to make an overall evaluation of our modelIs the model a good fit?" to the dataDoes the model explain" the dependent variable?. 3. Explaining" Variance. What do we mean whe

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PS 233

The Problem of Heteroskedasticity. Autocorrelation is one of two possible violations of our assumption E(ee')=s2InSpecifically, it is a violation of the assumption E(et,et-1)=0Coefficients are unbiased, but standard errors and t-tests are wrong.Generally, standard errors are TOO SMALL. Patterns

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PS 233

2. Standards of Model Evaluation. Statistical Significance of CoefficientsT-testsSubstantive Size of EffectsGenerate predictions from the modelSize of ResidualsCompare to substantive effectsForecasting Out-of-Sample. 3. Statistical Significance of Coefficients. First thing we want to do with a

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PS 233

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PS 233

2. Standards of Model Evaluation. Statistical Significance of CoefficientsT-testsSubstantive Size of EffectsGenerate predictions from the modelSize of ResidualsCompare to substantive effectsForecasting Out-of-Sample. 3. Statistical Significance of Coefficients. First thing we want to do with a model is see if the coefficients relevant for our theory are discernable from zeroT-tests give us confidence that relationships we observe are generalizableDon't get too focused on .05 as a

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PS 233

2. OLS Assumptions about Error Variance and Covariance. Talked last time about omitted variable biasViolates the assumption E(e)=0This was only one of the assumptions we made about errors to show that OLS is BLUEAlso assumed cov(e)=E(ee')=s2InThat is, we assumed e ~ (0, s2In). 3. What Should ee

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CSCI 233

CSCI 233. Class 11. Agenda. World Wide Web SNMP Your Career. HTTP. World Wide Web. Early Internet data transfers largely used FTP By 1995, Web traffic overtook FTP, has been the leader ever since Web and Internet are identical for many users The Web is transforming society in many ways.

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CSCI 233

CSCI 233. Class 10. Agenda. DHCP VoIP Internet telephone service SNMP World Wide Web WebDAV Web Services. Dynamic Host Configuration Program (DHCP). Configuration elements for a host: Address of default router Network mask Addresses of mail server, DNS server MTU of local network

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CPSC 233 Tutorial

CPSC 233 Tutorial. Xin Mar 14, 2011. Inheritance. super class – sub class generic – specific sub class inherits non-private attributes non-private methods sub class defines new attributes & methods. UML representation. Hollow triangle. Gramma. public class superClass { // … }

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PS

7a. FI. PS . 1. N2 Gas. 2. TE. TT. 8a. 8b. 3. VE. DAQ. Computer. 4. 7b. Labview. 6b. 6a. Chiller. TT-Temperature Transistor TE-Temperature Element VE-Voltage Element TI1- Temperature Indicator Inlet TI2- Temperature Indicator Outlet FI-Flow Indicator. Water Trap. TI1.

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CPSC 233 Tutorial

CPSC 233 Tutorial. Xin Feb 2, 2011. Scoping rules. Class Foo { int x ; // attribute, valid in the class ✓ Func1 (){ int x ; // shadowing ✗ int y = 0; // local variable. Valid here after till the end of Func1 ✓

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xkcd/233/

http://www.xkcd.com/233/. Text Clustering. David Kauchak cs160 Fall 2009 adapted from: http://www.stanford.edu/class/cs276/handouts /lecture17-clustering.ppt. Administrative. 2 nd status reports Paper review. IR code changes. /common/cs/cs160/project/ requires the mysql …jar

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233-234

233-234. chazelle@cs.princeton.edu. Sedgewick & Wayne (2004); Chazelle (2005). theory. experimentation. computation. theory. experimentation. 1950. computation. theory. experimentation. 2005. computation. experimentation. theory. 2005. computation. Moore’s Law. No Moore’s Law

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MGMD 233-MIS

MGMD 233-MIS. Emerging Trends & Technologies. Amn 2012. STUDENT LEARNING OUTCOMES. Describe emerging trends/technologies that will impact the changing Internet. Describe emerging technologies for physiological interaction with technology.

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233-234

233-234. Sedgewick & Wayne (2004); Chazelle (2005). Adjacency lists. Hansel & Gretel. random walk. 1. Birds eat the bread crumbs. DFS/BFS. 2. They don’t. Diffusion equation. Random walk. Diffusion equation. Normal distribution. 3 views of the same thing. Hansel & Gretel.

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233-234

233-234. Sedgewick & Wayne (2004); Chazelle (2005). How to check if adding an edge creates a cycle?. Label i all nodes of i-th tree. 2. 1. 1. 2. 1. 2. 2. How to check if adding an edge creates a cycle?. Label i all nodes of i-th tree. 2. 1. 1. 2. 1. 2. 2.

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Industrial Operations 233

Industrial Operations 233. Managing People. Manager’s Work. Planning: Deal with people? Organising: Deal with people? Implementing: Deal with people? Monitoring & Control: Deal with people? Meeting, Meeting, and Meeting!! Therefore, deal with people. Machine and People.

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CPSC 233

CPSC 233. Instructor: Nathaly (pronounced as Natalie) Verwaal Office: ICT 710 Course Website: http://cpsc.ucalgary.ca/~verwaal/233 E-mail: verwaal@cpsc.ucalgary.ca Office Hours: W 11:30 – 12:30 H 12:30 – 13:30 by appointment. Learning. Directly Applicable Skills versus

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