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It's the effect size, stupid: what effect size is and why it is important

It's the effect size, stupid: what effect size is and why it is important
It's the Effect Size, StupidWhat effect size is and why it is important Robert CoeSchool of Education, University of Durham, email r.j.coe@dur.ac.uk Paper presented at the Annual Conference of the British Educational Research Association, University of Exeter, England, 12-14 September 2002 Abstract Effect size is a simple way of quantifying the difference between two groups that has many advantages over the use of tests of statistical significance alone. 'Effect size' is simply a way of quantifying the size of the difference between two groups. The routine use of effect sizes, however, has generally been limited to meta-analysis - for combining and comparing estimates from different studies - and is all too rare in original reports of educational research (Keselman et al., 1998). The following guide is written for non-statisticians, though inevitably some equations and technical language have been used. 1. (a) (b) Figure 1 2. Equation 1 3. Table I: Interpretations of effect sizes 4. 5. 6. 7.

Togaware: Rattle: A Graphical User Interface for Data Mining using R Style Anomaly: Value versus Growth - June 23, 2011 This page is temporarily not available. Please check later as it should be available shortly. If you have any questions, please email customer support at support@zacks.com or call 800-767-3771 ext. 9339. Summer is heating up and some of the greatest baseball rivalries are in full swing. One often hears how value stocks outperform growth stocks; hence the value stock anomaly. First, let's define value and growth. To see if a portfolio of high earnings and low price stocks is similar to a portfolio of low estimated growth, I looked at returns to value stocks defined as high E/P and those defined as low EGR. Starting out with a universe of the 3000 most liquid stocks, I tested a value stock portfolio (300 stocks with the highest E/P) and a growth stock portfolio (300 stocks with the lowest E/P) from January 2000 – May 2011. The results over those 11+ years indicate a tendency for value stocks to outperform growth by an average of 1.2% per month for an annualized return of 11.1%.

Code School - Try R Strategien SmallCaps - die Börsenfrau® Kleine wachstumsstarke und fundamental gesunde Unternehmen (Small Caps) bieten sich für die Privatanlegerin als Kapitalanlage hervorragend an. Wichtig dabei ist die Auswahl: Folgen Sie einfach den Anlagegrundsätzen der großen Investoren, Benjamin Graham, Warren Buffett und Peter Lynch. Legen Sie Wert auf wachstumsstarke Unternehmen mit erfolgsversprechenden Zukunftsaussichten und soliden Finanzen. Oder schauen Sie sich Unternehmen mit einem bereits etablierten und soliden Geschäftsmodell an, das noch nicht von der breiten Masse des Marktes entdeckt worden ist. Doch lassen Sie "Penny-Stocks" und "Zockerwerte", die nie einen Gewinn erwirtschaftet haben, links liegen. Mit dem Kauf von Aktien erwerben Sie nicht nur ein Stück Papier, sondern einen Anteil an diesem kleinen Unternehmen. Worauf sollten Sie bei kleinen Unternehmen achten? Dazu ist bei einem kleinem Unternehmen vor allem das Wachstum wichtig. Der besondere Charme kleiner Unternehmen »Growth« und »Value« Der Wert- oder Value-Ansatz 1.

Matlab Matlab is a tool for doing numerical computations with matrices and vectors. It can also display information graphically. The best way to learn what Matlab can do is to work through some examples at the computer. After reading the " getting started " section, you can use the tutorial below for this. Getting started Here is a sample session with Matlab. % matlab >> a = [ 1 2; 2 1 ] a = 1 2 2 1 >> a*a ans = 5 4 4 5 >> quit 16 flops In this example you started Matlab by (you guessed it) typing matlab. The tutorial below gives more examples of how to use Matlab. Matrices To enter the matrix and store it in a variable a, do this: >> a = [ 1 2; 3 4 ] Do this now: define the matrix a. To redisplay the matrix, just type its name: >> a Once you know how to enter and display matrices, it is easy to compute with them. >> a * a Wasn't that easy? >> b = [ 1 2; 0 1 ] Then we compute the product ab: >> a*b Finally, we compute the product in the other order: >> b*a Of course, we can also add matrices: >> a + b x y

Capital Ideas - Rethinking Stock Returns New Evidence on Value Versus Growth Research by Eugene F. Fama "Value Versus Growth: The International Evidence," a 1997 working paper co-written by finance professor Eugene Fama of the University of Chicago Graduate School of Business and Kenneth R. French, a former Chicago faculty member now at the Yale School of Management, argues that the conventional wisdom is wrong. Fama and French define value stocks as those stocks that have high ratios of book value to market value and growth stocks as those that have low ratios of book value to market value. Fama and French reached their findings in the process of examining the validity of the Capital Asset Pricing Model (CAPM) and other asset pricing models. Seeking to test the validity of CAPM, Fama and French in 1992 examined the variables -- price-earnings ratios, firm size, book-to-market equity and leverage -- that research had determined to be related to average returns. Eugene F.

HyperStat Online: An Introductory Statistics Textbook and Online Tutorial for Help in Statistics Courses Recommend HyperStat to your friends on Facebook Click here for more cartoons by Ben Shabad. Other Sources Stat Primer by Bud Gerstman of San Jose State University Statistical forecasting notes by Robert Nau of Duke University related: RegressIt Excel add-in by Robert Nau CADDIS Volume 4: Data Analysis (EPA) The little handbook of statistical practice by Gerard E. Stat Trek Tutorial Statistics at square 1 by T. Concepts and applications of inferential statistics by Richard Lowry of Vassar College CAST by W. SticiGui by P. SurfStat by Keith Dear of the University of Newcastle. Introductory statistics: Concepts, models, and applications by David W. Multivariate statistics: Concepts, models, and applications by David W. Electronic textbook by StatSoft A new view of statistics by Will Hopkins of the University of Otago The knowledge base: An online research methods textbook by William M.

IPE Institutional Investment: Expertenbeitrag: Diversifikation von Risikofaktoren – Eine Einführung Der US Ökonom Harry M. Markowitz tat der Finanzindustrie mit seiner Dissertation „Portfolio Selection“ (1952) einen großen Gefallen. Er gab ihr mit dem Mean-Variance-Optimizer– als Kernstück der Modernen Portfoliotheorie - ein Werkzeug in die Hand, mit dessen theoretischem Unterbau und seiner praktischen Anwendung auch heute noch gutes Geld verdient werden kann. Einfach genug, um es Studenten an Business Schools zu vermitteln, komplex genug, um Investoren damit beeindrucken zu können. Sein Modell – damals noch als großer Fortschritt im Verständnis von Risiko und Return anerkannt – bildete den Ausgangspunkt für eine Reihe von Ein-Faktoren/Ein-Perioden-Modellen wie das Capital Asset Pricing Model (CAPM). Doch selbst alternative Assetklassen konnten sich nicht dem Trend steigender Korrelationen entziehen. Im Zuge des abrupten Liquiditätsentzuges quer über alle Assetklassen konnten erwartete Diversifikationspotenziale nicht gehoben werden. In Summe ergibt sich für die 2. ---*) Mag.

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