It's code and I have to find out what it means? I don't know were to start. Please help. Again, Inat please give up insulting Muslims. You could no longer love it if I had been 'anti-Semitic', and I am asking you kindly to give up your anti-Islamic phrases.
You are a most sensible contributor in faith, but all you appear to do is search out the Muslim similar inquiries to unfold insults and lies approximately the faith. As I have studied each Islam, and Judaism, amongst different religions, I can inform that you've got obviously no capabilities of Islam. It isn't your situation to be a hater, in an international in which there must be extra schooling and information.
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Tdi T5, ud fig ufTd. ES Fdt fud u]. F i"sa 3r 'tso qt nreg. E 3,lie. Id rd'ffi sl-fre' G u,-zfr qz i, dx sd, utd i fi]! J rrfr. Farffs fuq Ettd d qa. Ffr u. Jgi 6. Frr frfe 9" Agr. I'' H! Fsdfti Td I dfuaA fug d. E-E i i? FdHd dr? Et tB r:t. EaE se z- g,tzr ue. J-Al Ei eqs i fa rH 'History ofiheworldisthehistory of its -raa! Ffu e.Matt This is some good shot right here. I should print it off and put it on the wall above my mac vido Great advice. Mathew Fok Disagree with a few points, but agree with a lot for the most part.
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The strategies and tech tutorials you need to double your email list in 90 days. Pro strategies to tackle social media like a freakin' online superhero. Home About Contact Courses BloglovinFacebookInstagramPinterestTwitterYouTube. We're here to help you with that.For example, the mean score of our 100 students may be 65 out of 100.
However, not all students will have scored 65 marks. Rather, their scores will be spread out. Some will be lower and others higher. Measures of spread help us to summarize how spread out these scores are. To describe this spread, a number of statistics are available to us, including the range, quartiles, absolute deviation, variance and standard deviation.
When we use descriptive statistics it is useful to summarize our group of data using a combination of tabulated description (i. Join the 10,000s of students, academics and professionals who rely on Laerd Statistics. Please upgrade your browser or activate Google Chrome Frame to improve your experience. Jump to contentAre you providing data to BTS. Submit DataThe National Transportation Library is a repository for Department of Transportation information, providing library services and serving as a portal for transportation data.
As a principal statistical agency, BTS adheres to a number of standards and practices to assure the quality and comparability of its statistics. Search DataOn Time Statistics by Flight Number View DataSearch for Tarmac Times Highlights from the 2016 Census of Ferry Operations in the U. Read the latest report from our National Census of Ferry Operators On Time Statistics by Flight Number Search Data Search for Tarmac Times View Data Explore Transportation Topics Are you providing data to BTS.
Visit the Library News December 8, 2017 National Transportation Atlas Database Fall 2017 Update November 21, 2017 September 2017 Passenger Airline Employment Data November 21, 2017 September 2017 North American Freight Numbers View the BTS Statistical Release Schedule Did You Know U. Learn More Events List Monday, December 11, 2017 11:00 a.
Department of Transportation1200 New Jersey Avenue, SEWashington, DC 20590800-853-1351 Sign up for Email Updates. And every 8 minutes, that victim is a child. Meanwhile, only 6 out of every 1,000 perpetrators will end up in prison. More Statistics Scope of the ProblemVictims of Sexual ViolenceChildren and TeensPerpetrators of Sexual ViolenceThe Criminal Justice SystemCampus Sexual ViolencePeople Helped by RAINNAbout RAINN's Statistics DNA evidence can increase likelihood of holding a perpetrator accountable.
Read MoreSexual violence has fallen by half in the last 20 years. More StatsThe National Sexual Assault Hotline will always be free with your help.However, if you try to delete a batch topic distribution that is being used at the moment, then BigML.
To list all the batch topic distributions, you can use the batchtopicdistribution base URL. By default, only the 20 most recent batch topic distributions will be returned. You can get your list of batch topic distributions directly in your browser using your own username and API key with the following links. You can also paginate, filter, and order your batch topic distributions. Evaluations Last Updated: Monday, 2017-10-30 10:31 An evaluation provides an easy way to measure the performance of a predictive model.
The type of an evaluation can vary. It can be timeseries type if it is created using a time series. The performance measures provided by BigML will vary depending on the type of evaluation. You can also list all of your evaluations. All the fields in the dataset Specifies the fields in the dataset to be considered to create the evaluation. Specifies the type of ordering followed to pick the instances of the dataset to evaluate the model or ensemble.
There are three different types that you can specify: 0 Deterministic 1 Linear 2 Random For more information, see the Section on Shuffling for more details. The range of successive instances to evaluate the model. Example: "MySample" tags optional Array of Strings A list of strings that help classify and index your evaluation. Note that their use is deprecated, and maintained only for backwards compatibility. For example, to create a new evaluation named "my evaluation" using the first 50 instances in the dataset.
Once an evaluation has been successfully created it will have the following properties. That is, each measure is computed with respect to each class, then the computed values are averaged to get the average measure. You can read more on macro vs.
The full set of matrices is used to construct the rest of the measures. The first threshold is always nil, indicating the case where everything is classified positively. Ranking Measures measure the quality of the ranking provided by the classifier, as estimated from the performance at different operating thresholds. The canonical curve of this sort is the ROC curve, which shows the false positive rate and the recall at each threshold.As one of our top contributors of authentic lifestyle footage, we spoke to Ruslan Mykhalets of MStockAgency to get his top tips and tricks for ditching the cheesy look and producing Read more about Avoid the Cheesy Look: Tips for Directing Talent from Videographer Ruslan MykhaletsFiled Under: Contributors Tagged With: Authenticity, directing, stock videoOctober 1, 2017 By Alex ReffieFrom designing animations and special effects to working with AE templates or stylizing and color correcting footage, Adobe After Effects opens the door to creative possibilities for filmmakers of every skill level.
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As one of our top contributors of authentic lifestyle footage, we spoke to Ruslan Mykhalets of MStockAgency to get his top tips and tricks for ditching the cheesy look and producing Read more about Avoid the Cheesy Look: Tips for Directing Talent from Videographer Ruslan MykhaletsFrom designing animations and special effects to working with AE templates or stylizing and color correcting footage, Adobe After Effects opens the door to creative possibilities for filmmakers of every skill level.
We'd like to thank you for visiting our blog by offering you a Free Subscription to VideoBlocks. Thanks for stopping by. Discover Unlimited SavingsSign up now for unlimited downloads from our Member Library. Successful and pleasurable bottoming takes time and practice through dilation exercises, training of your self-awareness, and control of the pelvic floor. Of course, it may be uncomfortable at first and you might initially question how there could ever be pleasure in it something that happens with vaginal sex the first time as well but like anything it takes practice, patience, and following a few simple guidelines to enhance this sexual practice.
I often tell patients that great bottoms have been doing it for quite some time, with many first experiencing it in their youth. Unfortunately, no one showed us the right way to bottom in our high school sexual education class. Use a water-based lubricant and start with the smallest plug. Insert just to the point of pressure.
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To improve the forecasting power, this paper constructs macro indices from large datasets and adaptively chooses optimal indices to predict stock returns. I find that adaptive macro indices explain a substantial fraction of the short-term variation in future stock returns, and have more forecasting power than both the historical average of stock returns and commonly used predictors.
The forecasting power exhibits a strong cyclical pattern, implying the ability of adaptive macro indices in capturing time-varying economic conditions.
This finding highlights the importance of using dynamically-measured economic conditions to investigates empirical linkages between equity premium and macroeconomic fundamentals. We estimate the common macroeconomic factors using asymptotic principal component analysisdeveloped by Connor and Korajczyk (1986) and widely implemented for large macroeconomic panels (see Stock and Watson (2002a Watson (2002b Watson (2006), Ludvigson and Ng (2007, 2010), among others).
For a large number of macroeconomic time series this methodology can effectively distinguish noise from signal and summarize information into a small number of estimated common factors.
Macro Variables and the Components of Stock ReturnsArticleMar 2015J Empir FinanceViewShow abstract. Bulmash and Trivoli (1991) felt that long-term unemployment was related to capital market activity. Bai (2008) found that unemployment had 1. Regime Switching Allocation PoliciesArticleDec 2017Kevin C KaufholdView. Backward induction used with dynamic programming could be used to determine optimal allocations.
Bai (2008) felt that considerations of utility would produces a strong cyclical pattern: reduced investment in risky stocks at the beginning of recession and increased investment at the end of recession.
Allocations based on relative risk aversion showed a time-varying pattern across the business cycle. Forecasting is restricted to short term investment because most of the investors aim to gain profit in short period of time.
This study focusses on small sized companies because the asset prices are lower, hence the asset are affordable for all level of investors. These expectations are updated on the basis of regularly occurring surprises in macroeconomic announcement data.
The response of asset prices to positive or negative announcement surprises has been a regular feature of the literature for more than 20 years. These articles suggest that these managers prefer pessimistic.