Choose The Correct Option Teen Animal Club

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As you research whether or not OptionsANIMAL’s course is the right investment for you, we’ve found it helpful to share with you some of the common questions we get asked prior to joining our course.
There is risk associated with any trading instrument. However, buying options is essentially insurance. Would you consider your car, homeowner, or life insurance to be risky? You run the risk of losing your premiums if you don’t make a claim. But, in exchange for those premiums, you get the comfort of having protection life’s most important assets. 
Buying options allows you to protect the assets in your portfolio – which is another one of your important assets. 
Options traders have the ability to buy and sell options. In the case of selling options, you would be the one providing the insurance – the insurance company. In exchange for providing protection, you collect a premium. But it’s important to realize that the buyer’s protection is the sellers risk. Without having some other risk mitigating instrument, i.e., long options or shares of the equity, a trader could be exposed to significant risks. 
That is why we teach people the important fundamentals of spread trading – both buying and selling options and stock. This allows traders to take on exactly the risk profile that is comfortable for them. Almost always, the risk associated with spread trading is far less than trading a stock alone. 
Using a combination of these spread trades, our members understand how to generate income, achieve capital appreciation, and protect their portfolios in any market direction.
Collectively, our staff has over a hundred years of experience trading options. Seven days a week, they share their insights, experience, and coaching with our members – things that cannot be read in a book and only come from practical hands-on trading. 
We teach all of the basic and advanced options strategies. However, our unique approach to trading allows members to fix losing trades. Our success ratio of profitable trades exceeds 90% since we began tracking our performance six years ago. 
We are only able to achieve this sort of performance by using our proprietary adjustment technology. By following our straight-forward six-step trading plan, members structure trades that can be fixed when the market turns against them. 
Members also benefit from the most vibrant and active options community in the world. Live online classes and coaching sessions allow members to interact with our staff every day. Our Mid-Week and Weekly shows give members unique insight and ideas to trade the current market. All of these are available as archives if you miss the live sessions. 
We share real money trades with our members so they can see exactly how we are trading the current market. 
We also have an online community forum where members engage with our entire community – asking questions, getting feedback, sharing ideas, and improving their knowledge. 
OptionsANIMAL is also proud to offer live in-person summits throughout the year. These seminars are the industry benchmark in providing effective learning and real-time actionable trading ideas. These seminars are valued at over $2,500 each and are provided at no additional cost to our members.
The emotions of fear and greed are primal and cause traders to make bad decisions. The OptionANIMAL trade adjustment technology allows our member to consider the possible outcomes and plan for all contingencies. Imagine your confidence when you understand that you can manage your trade to profit, even if it doesn’t follow the expected path. This confidence allows OptionsANIMAL Traders to eliminate those primal emotions and trade rationally. It gives our you the peace and comfort to be able to sleep at night, knowing that you can be successful in any trend. 
In almost all cases, the answer is yes here. You can also use them in RESP’s if you reside in Canada. There are some limitations in 401k’s and RRSP’s. We would recommend you call in to find out how this works for your situation.
If you plan to trade options, it is important that you are using a broker who specializes in options trading. This ensures that you get access to all the possible trading strategies; smooth execution of trades; and good customer service. There are several excellent brokers who offer a broad spectrum instruments to trade, including options, futures, commodities, and currencies. A few good brokers to consider include:
No, absolutely not. There are several methods we teach that involve minimal commitment of time to trade successfully in the stock market. We find our average students are spending 30 minutes to an hour a day looking at the market.
We have taught thousands of members to trade options. Our diverse community spans the spectrum of age, location, and experience. Our youngest members are in their teens and our most experienced members are in their nineties. We have members from nearly every walk of life, including single stay-at-home parents, retired professors, plumbers, artists, engineers, firefighters, executive chefs, nurses, pet sitters, photographers, doctors, ballerinas, and more. All of these people have learned to master the OptionsANIMAL process and it has changed their lives forever. 
Our program is structured so that you can set the pace and learn at the rate that is best for you. Many of our members are successfully trading the market in only a few short months. 
OptionsANIMAL is unique and does not have any direct competition. While there are other training companies that offer options education, no other company has the unique trade adjusting technology that OptionsANIMAL has developed. 
OptionsANIMAL’s robust, learn-at-your-own-pace instructional platform offers our members the most comprehensive set of learning resources available. This includes daily live stream classes, daily coaching, recorded archives, twice weekly market insights, live in-person seminars, a vibrant peer community, and more!
One of our most unique attributes is that we are the only company that shares real-time, real-money trades and can demonstrate a success ratio that is greater than 90%, over our six-year track record. While some companies may offer examples of their winning trades, we share all of our trades. When a trade is placed, using our six-step process, coaches provide the exact details of their trading plan. This includes the analysis of the stock direction, an evaluation of potential strategies, the selection of the strikes and actual fill prices, along with a detailed trading plan. Members follow the trades in real-time and ask questions as our coaches turn these into winners. The average duration of our trades is about six-weeks and typically yields 20%, or more, Return On Risk on an annualized basis. 
Finally, no other company will guarantee your success at applying these options strategies and make money in the market. 
This answer really depends on your investing needs, risk tolerance, etc. We would recommend you call in to see what we might suggest depending on your situation. Short answer: you can trade some options with just a few hundred dollars.
There are four main benefits of trading options:
The real benefits of options trading for you come in the form of more vacations, less time trading, making more money, sleeping better at night, and realizing an eventual financial freedom.
Ready to get started? Contact us today!
Give us a call and ask for a free consultation on how you can start enjoying these benefits today!
1982 W. Pleasant Grove Blvd. Pleasant Grove, UT 84062
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Our main focus is to help people reach their investing goals whether it's capital preservation, wealth creation, or simply taking control of their own lives through financial security.
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How to choose the right statistical test?
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Wolters Kluwer -- Medknow Publications
Today statistics provides the basis for inference in most medical research. Yet, for want of exposure to statistical theory and practice, it continues to be regarded as the Achilles heel by all concerned in the loop of research and publication – the researchers (authors), reviewers, editors and readers.
Most of us are familiar to some degree with descriptive statistical measures such as those of central tendency and those of dispersion. However, we falter at inferential statistics. This need not be the case, particularly with the widespread availability of powerful and at the same time user-friendly statistical software. As we have outlined below, a few fundamental considerations will lead one to select the appropriate statistical test for hypothesis testing. However, it is important that the appropriate statistical analysis is decided before starting the study, at the stage of planning itself, and the sample size chosen is optimum. These cannot be decided arbitrarily after the study is over and data have already been collected.
The great majority of studies can be tackled through a basket of some 30 tests from over a 100 that are in use. The test to be used depends upon the type of the research question being asked. The other determining factors are the type of data being analyzed and the number of groups or data sets involved in the study. The following schemes, based on five generic research questions, should help.[1]
 Question 1: Is there a difference between groups that are unpaired? Groups or data sets are regarded as unpaired if there is no possibility of the values in one data set being related to or being influenced by the values in the other data sets. Different tests are required for quantitative or numerical data and qualitative or categorical data as shown in Fig. 1. For numerical data, it is important to decide if they follow the parameters of the normal distribution curve (Gaussian curve), in which case parametric tests are applied. If distribution of the data is not normal or if one is not sure about the distribution, it is safer to use non-parametric tests. When comparing more than two sets of numerical data, a multiple group comparison test such as one-way analysis of variance (ANOVA) or Kruskal-Wallis test should be used first. If they return a statistically significant p value (usually meaning p < 0.05) then only they should be followed by a post hoc test to determine between exactly which two data sets the difference lies. Repeatedly applying the t test or its non-parametric counterpart, the Mann-Whitney U test, to a multiple group situation increases the possibility of incorrectly rejecting the null hypothesis.
Tests to address the question: Is there a difference between groups – unpaired (parallel and independent groups) situation?
 Question 2: Is there a difference between groups which are paired? Pairing signifies that data sets are derived by repeated measurements (e.g. before-after measurements or multiple measurements across time) on the same set of subjects. Pairing will also occur if subject groups are different but values in one group are in some way linked or related to values in the other group (e.g. twin studies, sibling studies, parent-offspring studies). A crossover study design also calls for the application of paired group tests for comparing the effects of different interventions on the same subjects. Sometimes subjects are deliberately paired to match baseline characteristics such as age, sex, severity or duration of disease. A scheme similar to Fig. 1is followed in paired data set testing, as outlined in Fig. 2. Once again, multiple data set comparison should be done through appropriate multiple group tests followed by post hoc tests.
Tests to address the question: Is there a difference between groups – paired situation?
 Question 3: Is there any association between variables? The various tests applicable are outlined in Fig. 3. It should be noted that the tests meant for numerical data are for testing the association between two variables. These are correlation tests and they express the strength of the association as a correlation coefficient. An inverse correlation between two variables is depicted by a minus sign. All correlation coefficients vary in magnitude from 0 (no correlation at all) to 1 (perfect correlation). A perfect correlation may indicate but does not necessarily mean causality. When two numerical variables are linearly related to each other, a linear regression analysis can generate a mathematical equation, which can predict the dependent variable based on a given value of the independent variable.[2] Odds ratios and relative risks are the staple of epidemiologic studies and express the association between categorical data that can be summarized as a 2 × 2 contingency table. Logistic regression is actually a multivariate analysis method that expresses the strength of the association between a binary dependent variable and two or more independent variables as adjusted odds ratios.
Tests to address the question: Is there an association between variables?
 Question 4: Is there agreement between data sets? This can be a comparison between a new screening technique against the standard test, new diagnostic test against the available gold standard or agreement between the ratings or scores given by different observers. As seen from Fig. 4, agreement between numerical variables may be expressed quantitatively by the intraclass correlation coefficient or graphically by constructing a Bland-Altman plot in which the difference between two variables x and y is plotted against the mean of x and y. In case of categorical data, the Cohen’s Kappa statistic is frequently used, with kappa (which varies from 0 for no agreement at all to 1 for perfect agreement) indicating strong agreement when it is > 0.7. It is inappropriate to infer agreement by showing that there is no statistically significant difference between means or by calculating a correlation coefficient.
Tests to address the question: Is there an agreement between assessment (screening / rating / diagnostic) techniques?
 Question 5: Is there a difference between time-to-event trends or survival plots? This question is specific to survival analysis[3](the endpoint for such analysis could be death or any event that can occur after a period of time) which is characterized by censoring of data, meaning that a sizeable proportion of the original study subjects may not reach the endpoint in question by the time the study ends. Data sets for survival trends are always considered to be non-parametric. If there are two groups then the applicable tests are Cox-Mantel test, Gehan’s (generalized Wilcoxon) test or log-rank test. In case of more than two groups Peto and Peto’s test or log-rank test can be applied to look for significant difference between time-to-event trends.
It can be appreciated from the above outline that distinguishing between parametric and non-parametric data is important. Tests of normality (e.g. Kolmogorov-Smirnov test or Shapiro-Wilk goodness of fit test) may be applied rather than making assumptions. Some of the other prerequisites of parametric tests are that samples have the same variance i.e. drawn from the same population, observations within a group are independent and that the samples have been drawn randomly from the population.
A one-tailed test calculates the possibility of deviation from the null hypothesis in a specific direction, whereas a two-tailed test calculates the possibility of deviation from the null hypothesis in either direction. When Intervention A is compared with Intervention B in a clinical trail, the null hypothesis assumes there is no difference between the two interventions. Deviation from this hypothesis can occur in favor of either intervention in a two-tailed test but in a one-tailed test it is presumed that only one intervention can show superiority over the other. Although for a given data set, a one-tailed test will return a smaller p value than a two-tailed test, the latter is usually preferred unless there is a watertight case for one-tailed testing.
It is obvious that we cannot refer to all statistical tests in one editorial. However, the schemes outlined will cover the hypothesis testing demands of the majority of observational as well as interventional studies. Finally one must remember that, there is no substitute to actually working hands-on with dummy or real data sets, and to seek the advice of a statistician, in order to learn the nuances of statistical hypothesis testing.
Indian J Ophthalmol. 2011 Mar-Apr; 59(2): 85–86.
P. D. Hinduja National Hospital, Veer Savarkar Marg, Mumbai - 400 016, India
1Department of Pharmacololgy, Institute of Postgraduate Medical Education & Research (IPGME&;R), 244B Acharya J. C. Bose Road, Kolkata - 700020, India E-mail: moc.liamg@rotide.oji
Copyright © Indian Journal of Ophthalmology
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article has been cited by other articles in PMC.
Articles from Indian Journal of Ophthalmology are provided here courtesy of Wolters Kluwer -- Medknow Publications
1. Parikh MN, Hazra A, Mukherjee J, Gogtay N, editors. Research methodology simplified: Every clinician a researcher. New Delhi: Jaypee Brothers; 2010. Hypothesis testing and choice of statistical tests; pp. 121–8. [Google Scholar]
2. Petrie A, Sabin C, editors. Medical statistics at a glance. 2 nd. London: Blackwell Publishing; 2005. The theory of linear regression and performing a linear regression analysis; pp. 70–3. [Google Scholar]
3. Wang D, Clayton T, Bakhai A. Analysis of survival data. In: Wang D, Bakhai A, editors. Clinical trials: A practical guide to design, analysis and reporting. London: Remedica; 2006. pp. 235–52. [Google Scholar]
Indian J Ophthalmol. 2011 Mar-Apr; 59(2): 85–86.
Tests to address the question: Is there a difference between groups – unpaired (parallel and independent groups) situation?
Indian J Ophthalmol. 2011 Mar-Apr; 59(2): 85–86.
Tests to address the question: Is there a difference between groups – paired situation?
Indian J Ophthalmol. 2011 Mar-Apr; 59(2): 85–86.
Tests to address the question: Is there an association between variables?
Indian
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