Data for analysis

Sign ting your first project is a major milestone on the road to becoming a data scientist. You should decide how large and how messy a dataset you want to work with; while cleaning data is an integral part of data science, you may want to start with clean dataset for your first project so that you can focus on the analysis rather than on cleaning the on the learnings from our foundations of data science workshop and the data science career track, we’ve selected datasets of varying types and complexity that we think work well for first projects (some of them work for research projects as well! These data-sets cover a variety of sources: demographic data, economic data, text data, and corporate states census data: the united states census publishes reams of demographic data at the state, city, and even zip code level. The data set is fantastic for creating geographic data visualizations and can be accessed on the census website. In general, this data is very clean and very crime data: the fbi crime data set is fascinating. If you’re interested in analyzing time series data, you can use it to chart changes in crime rates at the national level over a 20 year period. Alternatively, you can look at the data cause of death: the center for disease control control maintains a database on cause of death. The data can be segmented in almost every way imaginable: age, race, year, and so re hospital quality: medicare maintains a database on complication rates by hospital that provides for interesting cancer incidence: the us government also has data about cancer incidence, again segmented by age, race, gender, year, and other of labor statistics: many important economic indicators for the united states (like unemployment and inflation) can be found on the bureau of labor statistics website. Most of the data can be segmented both by time and by bureau of economic analysis: the bureau of economic analysis also has national and regional economic data, like gdp and exchange economic data: if you want a view of international data, you can find it on the imf jones weekly returns: predicting stock prices is a major application of data analysis and machine learning. One dataset to explore is the weekly returns of the dow jones housing data: the boston housing data set contains median housing prices in boston suburbs as well as 13 attributes that contribute to those prices.

It’s an excellent set for experimenting with various types of emails: after the collapse of enron, a dataset of roughly 500,000 emails with message text and metadata were released. The dataset is now famous and provides an excellent testing ground for text related analysis. It has the messiness of real world n-grams: if you’re interested in truly massive data, the google n-grams dataset counts the frequency of words and phrases by year across a huge number of text sources. If you’re interested in classifying text, this is a great place to comments: reddit released a dataset of every comment that has ever been made on the site. That’s over a terabyte of data uncompressed, so if you want a smaller dataset to work with kaggle has hosted the comments from may 2015 on their dia: wikipedia provides instructions for downloading the text of english language g club: lending club provides data about loan applications it has rejected as well as the performance of loans that it issued. The dataset lends itself both to categorization techniques (will a given loan default) as well as regressions (how much will be paid back on a given loan. This is an excellent data for time series analysis and has interesting seasonal components as : this website offers different datasets related to airbnb and listings related to different : yelp releases an academic dataset that contains information for the areas around 30 – now it’s time to get cracking! If you want to jumpstart your data science career today, i’d recommend checking out our 12-week online workshop – foundations of data science. If you wanted even more resources, check out the springboard home science career we learned doing data science on those learning data science16 great online courses on astronomy and the universelearn the fundamentals of art and art history with these 33 courses15 awesome courses you can start this week (9-15th june 2014). Of students are improving their skills by using our and regional statistics, national data, maps and releases of new datasets and data updates from different sources around the data and visualizations relevant to major events happening around the ch and crime trends not so clear r testing: north korea breaking status of insights and data insights library goes deeper into hot topics and critical world issues.

Learn about how we integrate data and expert visualization services with our intelligent tools, custom situation rooms, and enterprise data individuals and teams who need unlimited access to our data library and tools making their research businesses relying on data and analytics to gain greater insights into their markets and universities and schools recognizing the importance of data discovery, visualization and analysis skills for their error occured. Restore browser is not may continue using your current browser, however, you may experience unexpected digital data assistant. And federal prisoners and prison correctional nt defense court caseload court characteristics and ing crimes to ch and service s and al justice data improvement al criminal history improvement justice statistics nics improvement amendments act of -related law l law ic enforcement training -public law ment and country justice ations & and product ations prior to al justice data improvement ment and country justice oming publications & al justice data improvement ment and country justice overnmental personnel act mobility te research fellowship y research fellowship data analysis tool home page (updated with 2013 and 2014 data). Statistical analysis tool (csat) - tions statistical analysis tool (csat) - tions statistical analysis tool (csat) - m crime reporting (ucr) statistics data l criminal case processing statistics (fccps). Crime victimization survey (ncvs) er recidivism analysis tool - 1994 home er recidivism analysis tool - 2005 home al justice data improvement ment and country justice by primary al justice data improvement ment and country justice ch and development bjs-funded research. All data analysis site requires a javascript-enabled browser,Click here for additional data analysis data analysis dynamic data analysis tool allows you to generate trend tables and figures data since 1980,Including national arrest estimates and agency-level counts by offense, age, sex, are from the fbi's uniform crime reporting (ucr) program. Codebooks and tions statistical analysis tool (csat) - dynamic analysis tool allows you to examine data collected by the annual on persons sentenced as adults who were conditionally released to ision, by parole board decision, by mandatory conditional release, through of post-custody conditional supervision, or as the result of a sentence to a supervised release. Statistical analysis tool (csat) - dynamic analysis tool allows you to examine national and jurisdictional for both federal and state correctional authorities. Statistical analysis tool (csat) - dynamic analysis tool allows you to examine data collected by bjs's ion survey on all adults, regardless of conviction status, who have been the supervision of a probation agency as part of a court order. Access - office of juvenile justice and delinquency prevention (ojjdp) data analysis access is a family of web-based data analysis tools on juvenile crime and le justice system provided by the office of juvenile justice and tion (ojjdp).

S uniform crime reporting (ucr) data tool, developed by bjs in collaboration with the fbi, provides access to national,State, and local ucr statistics. The federal criminal case processing statistics (fccps) tool online analysis of suspects and defendants processed across stages of the al justice system from 1994. The tool gives you instant access to victimization estimates from the most recent year that ncvs data are available. Ncvs data describe the frequency,Characteristics, and consequences of criminal victimization in the united states. Recidivism analysis tool - analysis tool enables users to calculate recidivism rates for persons state prisons. Recidivism rates may be generated for a large sample of for releasees with specific demographic, criminal history, and sentence tool uses data collected by bjs on a sample of persons released from s in 1994 and followed for a 3-year period. Recidivism analysis tool - dynamic data analysis tool allows you to calculate recidivism rates of ed from state prisons in 2005. Of justice data protection data quality statistical principles and policies and freedom of information ific integrity and product ment of and l bureau of l justice statistics resource al archive of criminal justice data (nacjd). Last revised on 08/28/p a research g the proposal - data your research proposal, you will also discuss how you will conduct an analysis of your data. By the time you get to the analysis of your data, most of the really difficult work has been done.

If you have done this work well, the analysis of the data is usually a fairly straightforward you look at the various ways of analyzing and discussing data, you need to review the differences between qualitative research/quantitative research and qualitative data/quantitative do i have to analyze data? The analysis, regardless of whether the data is qualitative or quantitative, may:Describe and summarize the fy relationships between fy the difference between r, you distinguished between qualitative and quantitative research. Source of confusion for many people is the belief that qualitative research generates just qualitative data (text, words, opinions, etc) and that quantitative research generates just quantitative data (numbers). Sometimes this is the case, but both types of data can be generated by each approach. For instance, a questionnaire (quantitative research) will often gather factual information like age, salary, length of service (quantitative data) – but may also collect opinions and attitudes (qualitative data). It comes to data analysis, some believe that statistical techniques are only applicable for quantitative data. There are many statistical techniques that can be applied to qualitative data, such as ratings scales, that has been generated by a quantitative research approach. Even if a qualitative study uses no quantitative data, there are many ways of analyzing qualitative data. For example, having conducted an interview, transcription and organization of data are the first stages of analysis. Manchester metropolitan university (department of information and communications) and learn higher offer a clear introductory tutorial to qualitative and quantitative data analysis through their analyze this!!!

In additional to teaching about strategies for both approaches to data analysis, the tutorial is peppered with short quizzes to test your understanding. The site also links out to further te this tutorial and use your new knowledge to complete your planning guide for your data are many computer- and technology-related resources available to assist you in your data general ing research (lots of examples of studies, and lots of good background, especially for qualitative studies). Data tative data analysis rice virtual lab in statistics also houses an online textbook, hyperstat. The site also includes a really useful section of case studies, which use real life examples to illustrate various statistical sure which statistical test to use with your data? The diagram is housed within another good introduction to data statistical analysis and data management computer-aided qualitative data analysis are many computer packages that can support your qualitative data analysis. The following site offers a comprehensive overview of many of them: online r package that allows you analyze textual, graphical, audio and video data. No free demo, but there is a student has add-ons which allow you to analyze vocabulary and carry out content analysis. Questions are addressed by researchers by assessing the data collection method (the research instrument) for its reliability and its ility is the extent to which the same finding will be obtained if the research was repeated at another time by another researcher. The following questions are typical of those asked to assess validity issues:Has the researcher gained full access to the knowledge and meanings of data? Procedure is perfectly reliable, but if a data collection procedure is unreliable then it is also invalid.

The other problem is that even if it is reliable, then that does not mean it is necessarily ulation is crosschecking of data using multiple data sources or using two or more methods of data collection. The many sources of non-sampling errors include the following:Researcher error – unclear definitions; reliability and validity issues; data analysis problems, for example, missing iewer error – general approach; personal interview techniques; recording dent error – inability to answer; unwilling; cheating; not available; low response section was discussed in elements of the proposal, where there are many online resources, and you have reflective journal entries that will support you as you develop your ideas for reliability and validity in your planning guide.