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SPS-100 exam Dumps Source : IBMSPSSSTATL1P - IBM SPSS Statistics flush 1

Test Code : SPS-100
Test designation : IBMSPSSSTATL1P - IBM SPSS Statistics flush 1
Vendor designation : IBM
: 70 existent Questions

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IBM IBMSPSSSTATL1P - IBM SPSS

Monster Merger: IBM Buys SPSS For Approx. $1.2 Billion In cash Deal | killexams.com existent Questions and Pass4sure dumps

IBM is buying analytics software and solutions company SPSS in an everything cash transaction at a value of $50/share – a forty two percent top class to Monday’s closing fee of $35.09 on Nasdaq – leading to a complete cash consideration within the merger of approximately $1.2 billion. The acquisition is realm to SPSS shareholder approval, regulatory clearances and other closing situations, and is expected to shut later within the 2d half of 2009.

massive Blue talked about the acquisition of the publicly-held Chicago company become anticipated to fortify its tips-agenda initiative, which helps businesses grasp information and revolve it into a strategic asset. IBM shares fell sixty seven cent to $116.ninety six in pre-market trading, while SPSS shares jumped 41 percent to $49.fifty nine.

A message from SPSS Chairman, CEO & President Jack Noonan:

We and IBM view this as a extremely-complementary movement from each a technology and a market spot viewpoint.

We’re enthusiastic about this agreement and the positive prospects that SPSS and IBM can achieve together in continuing to lead an business that they helped shape. The depth and breadth of IBM’s components, its client and market reach can simplest raise their capacity to tackle the transforming into market for Predictive Analytics.

In becoming a member of with IBM, they can increase Predictive Analytics as a competitive learning for groups and groups international. They see this as a transformative adventure if you want to accelerate the adoption of Predictive Analytics.

Between now and the acquisition close, they are able to continue to assist their valued clientele and partners in commonplace vogue. current contracts will continue to breathe in impact, account relationships and assist infrastructure will continue to breathe unchanged.

Predictive analytics application captures and analyzes information about individuals’s attributes, attitudes and behaviors to profit a replete figuring out of expected future behaviors, so groups could Make smarter decisions for more desirable company results.

IBM says it will proceed to aid and enhance SPSS technologies whereas allowing clients to grasp potential of its personal product portfolio. SPSS will become a allotment of the assistance management division in the utility group enterprise unit, led via Ambuj Goyal, time-honored manager, IBM tips management.

replace – In different information: IBM additionally bought Ounce Labs, a provider of enterprise supply code protection testing and intends to integrate it into its Rational utility company. pecuniary phrases had been not disclosed.


IBM is rushing up SPSS with Apache Spark | killexams.com existent Questions and Pass4sure dumps

IBM nowadays announced that it is improving several of its present application items with the Apache Spark open-supply facts processing engine, including the SPSS predictive analytics software.

IBM purchased SPSS for $1.2 billion in 2009. SPSS itself begun at Stanford school in 1968 and is usual in records lessons at universities.

IBM is chiefly incorporating Spark into SPSS Modeler and SPSS Analytic Server, a spokesman advised VentureBeat in an e mail.

Spark is too being applied to IBM’s BigInsights, Streams, and DataWorks utility, in keeping with a press release.

The Sparkification of IBM comes after great Blue introduced an immense commitment to the open-source software in June. on the time, IBM introduced Spark as a carrier on its Bluemix cloud; that carrier is now often available.

IBM has made greater than 60 contributions to Spark on the grounds that the June announcement, in keeping with the statement.


a glance on the IBM SPSS Modeler and IBM SPSS data analytics tools | killexams.com existent Questions and Pass4sure dumps

IBM's SPSS predictive analytics tools embrace IBM SPSS Modeler and IBM SPSS records. SPSS Modeler provides...

records mining and textual content evaluation utility, while SPSS statistics is an integrated household of items. each tools enable users to build predictive models and execute different analytics initiatives.

The IBM SPSS Modeler goals clients who abide puny or no programming knowledge. users are offered with a drag-and-drop consumer interface, enabling them to build predictive models and operate other data analytics. Modeler can apply distinct techniques and algorithms to assist the user find counsel hidden in the information. The device can additionally serve in integrating and consolidating every kind of information sets from dispersed statistics sources throughout the organization.

The IBM SPSS statistics suite is an integrated set of items geared toward extra expert facts analysts. SPSS facts addresses the finished analytical manner, from planning to statistics collection, evaluation, reporting and deployment.

IBM SPSS Modeler aspects

edition 18 offers birthright here facets:

  • more than 30 foundation computing device gaining learning of algorithms.
  • Extensions that deliver endured advancements to breathe used with open supply items, equivalent to R and Python.
  • better assist for a number of multithreaded analytical algorithms, together with Random bushes, Tree-AS, Generalized Linear Engine, Linear-AS, Linear back Vector computing device and Two-Step-AS clustering.
  • The means to sprint loads of Python and Spark laptop getting to know, as well as other Python analytics libraries natively in Modeler with out requiring using the Analytic Server, as was required in the used version.
  • SPSS Modeler bundles are deployed on premises, and SPSS Modeler Gold is available as a cloud providing. The customer entrance conclusion of SPSS Modeler runs beneath windows and macOS, whereas the server allotment runs on Unix, Linux and home windows.

    IBM SPSS Modeler gives here versions:

  • SPSS Modeler personal: A single-person computer product.
  • SPSS Modeler skilled: A desktop product that works with IBM SPSS Analytic Server, providing better scalability and efficiency and enabling purposes for expend across an organization.
  • SPSS Modeler top rate: This version comprises superior algorithms and capabilities, akin to text analytics, entity analytics and sociable community analysis, that enhance model accuracy with unstructured statistics.
  • SPSS Modeler Gold: This edition provides analytical election administration, collaboration and deployment capabilities. SPSS Modeler Gold is too attainable as a cloud providing.
  • IBM SPSS statistics features

    SPSS statistics version 24 includes here current elements:

  • The ability to access greater than one hundred extensions, enabling clients to grasp talents of free libraries written in R, Python and SPSS syntax.
  • The IBM SPSS Extension Hub to browse, download, update, remove and generally maneuver extensions.
  • a huge upgrade to the customized Dialog Builder, enabling clients to more effectively build and install their personal extensions. Enhancements embrace current controls and current homes for existing controls and several different improvements to the consumer interface.
  • improvements that permit clients to more without hardship and birthright away import and export data into SPPS statistics.
  • improvements to the customized Tables module, including current statistical functionality and client-requested elements.
  • IBM SPSS statistics offers the following three versions (each and every with extra modules):

  • SPSS statistics general tools give superior statistical techniques that back linear and nonlinear statistical fashions, as well as predictive simulation modeling, which bills for unclear inputs, geospatial analytics and customised tables.
  • SPSS information skilled apparatus aid information instruction, lacking values and data validity, resolution trees, and forecasting.
  • SPSS data premium adds advanced analytical concepts, together with structural equation modeling, in-depth sampling evaluation and testing. This bundle additionally includes methods that target direct advertising and excessive-conclusion charts and graphs.
  • Pricing for the SPSS Modeler and SPSS records predictive analytics apparatus disagree counting on the bundle alternatives, the variety of clients and the license period. SPSS information is now purchasable as a subscription alternative or a perpetual license. IBM presents free trials of each IBM SPSS Modeler and IBM SPSS facts.

    subsequent Steps

    Why the time age unstructured records is a misnomer

    How massive data is changing information modeling ideas

    massive records systems pose current challenges to records governance

    connected materials View more

    SPS-100 IBMSPSSSTATL1P - IBM SPSS Statistics flush 1

    Study sheperd Prepared by Killexams.com IBM Dumps Experts


    Killexams.com SPS-100 Dumps and existent Questions

    100% existent Questions - Exam Pass Guarantee with tall Marks - Just Memorize the Answers



    SPS-100 exam Dumps Source : IBMSPSSSTATL1P - IBM SPSS Statistics flush 1

    Test Code : SPS-100
    Test designation : IBMSPSSSTATL1P - IBM SPSS Statistics flush 1
    Vendor designation : IBM
    : 70 existent Questions

    Less effort, distinguished knowledge, guaranteed success.
    I wound up the exam with a satisfying eighty four% marks in stipulated time. thank you very a distinguished deal killexams. by means of and via, it became tough to outcome pinnacle to bottom examine proceeding with a complete-time work. At that factor, I grew to become to the of killexams. Its concise solutions helped me to sight a few intricate subjects. I selected to sit down for the examination SPS-100 to gain further advancement in my profession.


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    Real Test SPS-100 questions.
    I were given 76% in SPS-100 exam. pass to the group of killexams.Com for making my attempt so easy. I advocate to current customers to set aside together via killexams.Com as its very complete.


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    passed the SPS-100 exam with 99% marks. awesome! thinking about most effectual 15 days education time. everything credit score goes to the question & retort by pass of killexams. Its distinguished material made training so smooth that I may want to even understand the difficult subjects cozy. thanks a lot, killexams.com for offering us such an clean and powerful commemorate manual. wish your team maintain on developing greater of such courses for other IT certification exams.


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    I requisite existent test questions of SPS-100 exam.
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    Emergency department visits by uninsured patients drop in Illinois after Medicaid expansion | killexams.com existent questions and Pass4sure dumps

    ORLANDO, Fla. - current research adds to a growing corpse of evidence suggesting that the expansion of Medicaid under the Affordable custody Act (ACA) helped low-income families depend less on emergency department visits for medical care.

    The study abstract, "Effect of Affordable custody Act Medicaid Expansion on Emergency Department Visits by Uninsured Patients in Illinois 2009-2015," will breathe presented on Friday, Nov. 2, at the American Academy of Pediatrics (AAP) 2018 National Conference & Exhibition in Orlando, Fla.

    In Illinois, according to the abstract, Medicaid expansion was associated with a significant drop in uncompensated custody in emergency department by patients without insurance between 2009 and 2015. The ACA extended Medicaid coverage eligibility to adults with incomes up to 133 percent of the federal poverty level.

    "As a result of the ACA, 850,000 people in Illinois gained health insurance during the study period," said abstract author Peter Nguyen, MD, a Pediatric Emergency Medicine Fellow at Michigan status University's Helen Devos Children's Hospital who previously studied in Illinois. "During the same time, they saw a significant drop in emergency department visits by patients without insurance."

    Researchers analyzed emergency department visits using data from the Healthcare Cost and Utilization Project and establish there were a total of 31.2 million emergency department visit in Illinois during the study period. Of these, 4.1 million were visits by uninsured patients.

    Uninsured emergency department visits in the status peaked birthright before ACA implementation, Dr. Nguyen said, when they accounted for 16 percent the visits. Post-ACA implementation, there was a 40 percent reduction in uninsured emergency department visits.

    "This study adds to the growing corpse of evidence that the ACA can breathe beneficial in promoting patient-centered care, shifting it from the emergency department to a patient's medical home for ongoing, comprehensive care. This is a healthier situation for everyone," Dr. Nguyen said.

    Dr. Nguyen said that proposed policy changes may unhurried the reduction in uncompensated emergency department visits. "With increasing mistrust about the long-term draw for the ACA, enrollment has started to decline," he said. "So, it will breathe exciting to see whether we'll see a mount again in uninsured emergency department visits."

    Dr. Nguyen will present an abstract of the study, available below, between 3:15 and 3:30 p.m. ET on Friday, Nov. 2, in Orlando Ballroom L of the Orange County Convention hub in Orlando, FL.

    Please note: only the abstract is being presented at the meeting. In some cases, the researcher may abide more data available to share with media, or may breathe preparing a longer article for submission to a journal.

    ###

    The American Academy of Pediatrics is an organization of 67,000 primary custody pediatricians, pediatric medical subspecialists and pediatric surgical specialists dedicated to the health, safety and well-being of infants, children, adolescents and immature adults. For more information, visit http://www. aap. org. Reporters can access the meeting program and other apropos meeting information through the AAP meeting website at http://www. aapexperience. org/

    Abstract Title:

    Effect of Affordable custody Act Medicaid Expansion on Emergency Department Visits by Uninsured Patients in Illinois 2009-2015

    Peter Nguyen

    Introduction: Medicaid expansion was one of the key provisions of the Affordable custody Act (ACA) designed to reduce the number of people without health insurance. The ACA extended Medicaid coverage to everything adult citizens with annual incomes up to 133% of the federal poverty level. Purpose: Their study objective was to study the impact of ACA on Uninsured Emergency Department Visits (UiEDV). Methods: They downloaded aggregated EDV from the Healthcare Cost and Utilization Project (HCUP) website and extracted status of Illinois EDV and sorted the data by year and quarter. They looked for trends in the quarterly UiEDV data and calculated summary statistics to determine the variance and mean. They used generalized linear modeling (Poisson and a customized negative binomial regression (NB)) to model UiEDV using quarterly UiEDV weigh as a subject variable and pre and post ACA implementation periods as independent factors. They used log as the link function, and the software calculated the estimated parameter. From the model, they derived the Incidence Rate Ratio (IRR) and its corresponding 95% self-confidence Interval (95%CI); they compared both models using Goodness of apt tests Akaike Information Criterion (AIC) and Bayesian Information Citerion (BIC). They used IBM SPSS Version 25â„¢ and Microsoft outdo â„¢ 2016 for data preparation and analysis. Results: For the study period, there were 31,368,200 EDVs. Of these, 4,120,200 were uninsured (mean (SD) 147,150 (6376); variance 1,138,281,481)). The ratio of UiEDV to total EDVs was between 7% and 16%; the peak occurred before ACA implementation. NB modelling demonstrated a IRR of 1.67 (95% CI, 1.53-1.83) of UiEDV pre-ACA compared post-ACA with a 40 percent reduction of UiEDV. Goodness of apt demonstrated lower AIC (629 vs 40361) and BIC 626 vs 40360) when compared both models were compared indicating NB a better model fit. Conclusion: Insurance is a gateway to healthcare access; because of ACA, cross of uncompensated EDVs decreased substantially in Illinois during the study period. Additional studies to sight at regional trends, specific groups, continued coverage is needed to quantify the overall effects of ACA.

    Disclaimer: AAAS and EurekAlert! are not answerable for the accuracy of advice releases posted to EurekAlert! by contributing institutions or for the expend of any information through the EurekAlert system.


    Unfriendly Skies: Predicting Flight Cancellations Using Weather Data, allotment 2 | killexams.com existent questions and Pass4sure dumps

    Ricardo Balduino and Tim Bohn

    Early Flight, Creative Commons Introduction

    As they described in allotment 1 of this series, their objective is to serve call the probability of the cancellation of a flight between two of the ten U.S. airports most affected by weather conditions. They expend historical flights data and historical weather data to Make predictions for upcoming flights.

    Over the course of this four-part series, they expend different platforms to serve us with those predictions. Here in allotment 2, they expend the IBM SPSS Modeler and APIs from The Weather Company.

    Tools used in this expend case solution

    IBM SPSS Modeler is designed to serve ascertain patterns and trends in structured and unstructured data with an intuitive visual interface supported by advanced analytics. It provides a range of advanced algorithms and analysis techniques, including text analytics, entity analytics, conclusion management and optimization to deliver insights in near real-time. For this expend case, they used SPSS Modeler 18.1 to create a visual representation of the solution, or in SPSS terms, a stream. That’s right — not one line of code was written in the making of this blog.

    We too used The Weather Company APIs to retrieve historical weather data for the ten airports over the year 2016. IBM SPSS Modeler supports calling the weather APIs from within a stream. That is accomplished by adding extensions to SPSS, available in the IBM SPSS Predictive Analytics resources page, a.k.a. Extensions Hub.

    A proposed solution

    In this blog, they pose one viable solution for this problem. It’s not meant to breathe the only or the best viable solution, or a production-level solution for that matter, but the discussion presented here covers the typical iterative process (described in the sections below) that helps us accumulate insights and refine the predictive model across iterations. They hearten the readers to try and Come up with different solutions, and provide us with your feedback for future blogs.

    Business and data understanding

    The first step of the iterative process includes understanding and gathering the data needed to train and test their model later.

    Flights data — We gathered 2016 flights data from the US Bureau of Transportation Statistics website. The website allows us to export one month at a time, so they ended up with 12 csv (comma separated value) files. They used IBM SPSS Modeler to merge everything the csv files into one set and to select the ten airports in their scope. Some data clean-up and formatting was done to validate dates and hours for each flight, as seen in figure 1.

    Figure 1 — gathering and preparing flights data in IBM SPSS Modeler

    Weather data — From the Extensions Hub, they added the TWCHistoricalGridded extension to SPSS Modeler, which made the extension available as a node in the tool. That node took a csv file listing the 10 airports latitude and longitude coordinates as input, and generated the historical hourly data for the entire year of 2016, for each airport location, as seen in figure 2.

    Figure 2 — gathering and preparing weather data in IBM SPSS Modeler

    Combined flights and weather data — To each flight in the first data set, they added two current columns: inception and DEST, containing the respective airport codes. Next, flight data and the weather data were merged together. Note: the “stars” or SPSS super nodes in figure 3 are placeholders for the diagrams in Figures 1 and 2 above.

    Figure 3 — combining flights and weather data in IBM SPSS Modeler Data preparation, modeling, and evaluation

    We iteratively performed the following steps until the desired model qualities were reached:

    · Prepare data

    · effect modeling

    · Evaluate the model

    · Repeat

    Figure 4 shows the first and second iterations of their process in IBM SPSS Modeler.

    Figure 4 — iterations: prepare data, sprint models, evaluate — and outcome it again First iteration

    To start preparing the data, they used the combined flights and weather data from the previous step and performed some data cleanup (e.g. took custody of null values). In order to better train the model later on, they filtered out rows where flight cancellations were not related to weather conditions (e.g. cancellations due to technical issues, security issues, etc.)

    Figure 5 — imbalanced data establish in their input data set

    This is an exciting expend case, and often a difficult one to solve, due to the imbalanced data it presents, as seen in figure 5. By “imbalanced” they imply that there were far more non-cancelled flights in the historical data than cancelled ones. They will contend how they dealt with imbalanced data in the following iteration.

    Next, they defined which features were required as inputs to the model (such as flight date, hour, day of the week, inception and destination airport codes, and weather conditions), and which one was the target to breathe generated by the model (i.e. call the cancellation status). They then partitioned the data into training and testing sets, using an 85/15 ratio.

    The partitioned data was fed into an SPSS node called Auto Classifier. This node allowed us to sprint multiple models at once and preview their outputs, such as the area under the ROC curve, as seen in figure 6.

    Figure 6 — models output provided by the Auto Classifier node

    That was a useful step in making an initial selection of a model for further refinement during subsequent iterations. They decided to expend the Random Trees model since the initial analysis showed it has the best area under the curve as compared to the other models in the list.

    Second iteration

    During the second iteration, they addressed the skewedness of the original data. For that purpose, they chose one of the SPSS nodes called SMOTE (Synthetic Minority Over-sampling Technique). This node provides an advanced over-sampling algorithm that deals with imbalanced datasets, which helped their selected model travail more effectively.

    Figure 7 — distribution of cancelled and non-cancelled flights after using SMOTE

    In figure 7, they notice a more balanced distribution between cancelled and non-cancelled flights after running the data through SMOTE.

    As mentioned earlier, they picked the Random Trees model for this sample solution. This SPSS node provides a model for tree-based classification and prediction that is built on Classification and Regression Tree methodology. Due to its characteristics, this model is much less recumbent to overfitting, which gives a higher likelihood of repeating the same test results when you expend current data, that is, data that was not allotment of the original training and testing data sets. Another advantage of this method — in particular for their expend case — is its ability to handle imbalanced data.

    Since in this expend case they are dealing with classification analysis, they used two common ways to evaluate the performance of the model: confusion matrix and ROC curve. One of the outputs of running the Random Trees model in SPSS is the confusion matrix seen in figure 8. The table shows the precision achieved by the model during training.

    Figure 8 — Confusion Matrix for cancelled vs. non-cancelled flights

    In this case, the model’s precision was about 95% for predicting cancelled flights (true positives), and about 94% for predicting non-cancelled flights (true negatives). That means, the model was redress most of the time, but too made wrong predictions about 4–5% of the time (false negatives and erroneous positives).

    That was the precision given by the model using the training data set. This is too represented by the ROC curve on the left side of figure 9. They can see, however, that the area under the curve for the training data set was better than the area under the curve for the testing data set (right side of figure 9), which means that during testing, the model did not effect as well as during training (i.e. it presented a higher rate of errors, or higher rate of erroneous negatives and erroneous positives).

    Figure 9 — ROC curves for the training and testing data sets

    Nevertheless, they decided that the results were noiseless agreeable for the purposes of their discussion in this blog, and they stopped their iterations here. They hearten readers to further refine this model or even to expend other models that could decipher this expend case.

    Deploying the model

    Finally, they deployed the model as a leisure API that developers can muster from their applications. For that, they created a “deployment branch” in the SPSS stream. Then, they used the IBM Watson Machine Learning service available on IBM Bluemix here. They imported the SPSS stream into the Bluemix service, which generated a scoring endpoint (or URL) that application developers can call. Developers can too muster The Weather Company APIs directly from their application code to retrieve the forecast data for the next day, week, and so on, in order to pass the required data to the scoring endpoint and Make the prediction.

    A typical scoring endpoint provided by the Watson Machine Learning service would sight fondness the URL shown below.

    https://ibm-watson-ml.mybluemix.net/pm/v1/score/flights-cancellation?accesskey=<provided by WML service>

    By passing the expected JSON corpse that includes the required inputs for scoring (such as the future flight data and forecast weather data), the scoring endpoint above returns if a given flight is likely to breathe cancelled or not. This is seen in figure 10, which shows a muster being made to the scoring endpoint — and its response — using an HTTP requester tool available in a web browser.

    Figure 10 — actual request URL, JSON body, and response from scoring endpoint

    Notice in the JSON response above that the deployed model predicted this particular flight from Newark to Chicago would breathe 88.8% likely to breathe cancelled, based on forecast weather conditions.

    Conclusion

    IBM SPSS Modeler is a powerful tool that helped us visually create a solution for this expend case without writing a lone line of code. They were able to ensue an iterative process that helped us understand and prepare the data, then model and evaluate the solution, to finally deploy the model as an API for consumption by application developers.

    Resources

    The IBM SPSS stream and data used as the basis for this blog are available on GitHub. There you can too find instructions on how to download IBM SPSS Modeler, merit a key for The Weather Channel APIs, and much more.


    A simple Play On Self-Service colossal Data Prep And Analytics: Wait For Smarter Valuation Entry Point | killexams.com existent questions and Pass4sure dumps

    No result found, try current keyword!We would wait for a more attractive valuation flush to initiate positions ... open source statistical programming language R (which is supported by Alteryx), IBM SPSS Statistics, the SAS programming l...


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