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I highly recommend this course to folks involved in clinical study design-- Dewan Zeng, Director, Clinical Research at Gilead SciencesBest course I ever took on Sample Size and Power Determination-- Dalia Rimawi, King Hussein Cancer CenterI loved the new option to send assignments to the teaching assistant for suggestions before submitting the work to be marked. Both courses are well designed and build up over the weeks in a such a manner that they make learning new concepts easy to handle-- Charalambos Kollias, Senior Assessment Officer, Hellenic American UniversityThis course has given me a good understanding of the basics in Rasch analysis.
I feel confident moving forward onto the next section of R programming-- Trish Shewokis, Drexel UniversityDr. This will be very helpful for the type of data analysis work I do-- Lesley Painchaud, Scientist at US NavyThis course is an excellent follow up to the R basic course. A lot of new and helpful material was added and contributed to a more advanced understanding of R programming-- David LaBarre, Risk Analyst at USDA-FSISDr Lau's classes are superb as usual-- Rocio Dominguez Vidana, Baylor College of MedicineProfessor John Verzani is excellent.
I am really blessed to be part of such an institute :)-- Vinuth Tulasi, Juniper NetworksBoth professor Verzani and the TA's were always ready to answer questions. You've made my fear of R vanish-- the pace of the course definitely helped with building confidence-- Kathleen Gobush, Vulcan, IncI took the course to get starting using R, thus I think this will help with my use of statistics in the future.
Discussions initiated by other students were also very valuable - esp for PCA and Clusters-- Satish Rao, IBMInstructor gave good, understandable answers on the board, and several nice summaries of topics we were covering. Santiago, IBMThe videos are excellent. The information is presented in a very clear and effective way.
Ev's role as instructor made a huge difference-- Francisco Conejo, University of Colorado DenverI enjoyed the course guidance from Everett.
I'd love to take additional politically orientated statistics classes-- Jake Lowen, Kansas Grassroots Consulting, LLCI highly recommend this course for anyone new to R but planning to take GLM, Logistic regression etc as it gives such a great foundation. I am an actuary and all the concepts dealt with in this course are highly applicable to everyday modelling work-- Shadreck Mapfumo, IFC - International Finance CorporationI need all the modeling practice I can get in R.
This will help me in my work as I am a principal of an elementary school and want to know which strategies have the greatest impact on student achievement-- Debra Prenkert, Monroe County Community School CorporationThis is an excellent course with a lot covered (beyond expectation). The tutor has been very responsive to queries and comments-- Sanjay Rao, Monroe County Community School CorporationDr. Questions on the discussion forums were very, very good-- Jo Azzarello, University of Oklahoma Health Sciences CenterThe instructor, Dr.Daikin tech support
It would be hard or impossible to get this information on my own-- Milan Hejtmanek, Seoul National UniversityThis is a very well prepared course. The instructor not only pointed out the right book for statisticians but also provided very useful lecture notes that helped a lot-- Elena Rose, Data Scientist, NinthDecimalExcellent course. Smith is very dedicated, always available to answer questions, and makes this online course feel almost face-to-face-- Fabiana MacMillan, Rosetta StoneI was very anxious about taking this course.
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I'm looking forward using these concepts in my business pretty soon-- Yannick Messiaux, AgieCharmilles Management SAThis class was very interesting and practical. The instructor's lecture notes were written very clearly and were easy to read-- Alisa Boehme, QDNRA very nice introduction to Hadoop.
I was forced to dig in and found that very rewarding-- Jeff Crawford, Jackson National Life Insurance CompanyI thought the course was well organized and I liked the selected readings and text by Stephen Few-- Susan Stachler, DePaul UniversityVisualizing data interactively will be useful when performing any type of data analysis.
The TA was also excellent with good feedback on the homework-- John Riley, Walmart eCommerceI really liked how the instructors coordinated the course. I found their textbook Practical Spreadsheet Modelling an excellent resource-- Shadreck Mapfumo, IFC - International Finance CorporationThe modeling techniques learned in this course will greatly assist me in understanding the use of models in the banking industry.
Indrayan has put together a very good on-line learning package. I cannot praise this course highly enough-- Milan Hejtmanek, Seoul National UniversityThis course will help me handle statistical analyses and related consultancy in a correct, professional and intelligent way.
Those problems help me to apply the skills in the field-- Yonetaro Kawada, ABeam ConsultingExcellent format, with flexibility to work whenever time is available, and work a bit ahead as needed to work around other committments-- Michelle MacKinnon, SanDiskI have to say that I learned more about statistics in one month with Statistics.
What is much more important than these numbers is an internal dynamic for which there are no statistics. For passengers, beyond the statistics lies a puzzle that has persisted for years.
This may appear incredible, but it is a fact as statistics will show. This commonly held belief is based on statistics of longevity and sanitation. These figures are drawn from statistics published in July 1914. Meaning "numerical data collected and classified" is from 1829.
Abbreviated form stats first recorded 1961. Statistics is especially useful in drawing general conclusions about a set of data from a sample of the data.The winner of the Arcana giveaway: Alex Kreik His comment: "Muhkuh made me gucci again" Hahaha My next Arcana giveaway game: - Like this post - Spam on Vpgame on All 3 matches above in the comment section: "fb.
Mouz odds are fucking good. HR is trash for the old finem Team in my opinion. Both are super hard to predict.
Newbee is amazing strong lately but FY strategys cant be ignored. I have a small feeling Newbee got this, handicap newbee that they win at least one round. My next Arcana giveaway game: - Like this post - Spam on Vpgame on All 3 matches above in the comment section: "fb.
Winner will be announced in the end of the day. Continue on to create your Steam account and get Steam, the leading digital solution for PC, Mac, and Linux games and Software. Not recommend for those who don't like taking risks and cries when lose after following free predictions. It is fun but it can also be tricky. Many handicappers will want long into the season before they start to bet, handicap or even research college basketball.
That is acceptable since many basketball handicappers want to completely focus on football. With just one game on the schedule this week, it's pretty obvious we'll be looking at the Army vs. Navy game, where the Midshipmen are favored by 2. The total on the game has been bet down to 46 after opening 51. One of the most unique factors about the bowl season is that teams go through the prep period and then hit the field with an interim head coach.
Interim Head Coaches in College Football Bowl Games One of the most unique factors about the bowl season is that teams go through the prep period and then hit the field with an interim head coach.
Betway is a brand managed by Betway Limited (C39710), a Maltese registered company whose registered address is 9 Empire Stadium Street, Gzira, GZR 1300, Malta. Betway Limited is registered with I. The app may include account creation, location detection, user generated content, advertisements, infrequent or mild references to violence, profanity, or crude themes, or other content not suitable for all ages. The app may include account creation, location detection, user generated content, advertisements, explicit references to or images of drugs, alcohol, tobacco, graphic violence, profanity, or crude humor, mild sexual and suggestive themes, nudity within medical, informational, or artistic contexts, simulated gambling, or other content only suitable for mature audiences.
The app may include account creation, location detection, user generated content, advertisements, explicit references to or images of drugs, alcohol, tobacco, graphic violence, profanity, or crude humor, sexual and suggestive themes, nudity, simulated gambling, or other content only suitable for adult audiences.The batting average doesn't tell you whether the batter is hitting home runs or singles.
It doesn't tell whether she's been in a slump or on a streak. The GPA doesn't tell you whether the student was in difficult courses or easy ones, or whether they were courses in their major field or in other disciplines. Even given these limitations, descriptive statistics provide a powerful summary that may enable comparisons across people or other units. The distribution is a summary of the frequency of individual values or ranges of values for a variable.
The simplest distribution would list every value of a variable and the number of persons who had each value. For instance, a typical way to describe the distribution of college students is by year in college, listing the number or percent of students at each of the four years.
Or, we describe gender by listing the number or percent of males and females. In these cases, the variable has few enough values that we can list each one and summarize how many sample cases had the value. But what do we do for a variable like income or GPA.
With these variables there can be a large number of possible values, with relatively few people having each one. In this case, we group the raw scores into categories according to ranges of values. For instance, we might look at GPA according to the letter grade ranges. Or, we might group income into four or five ranges of income values.
One of the most common ways to describe a single variable is with a frequency distribution. Depending on the particular variable, all of the data values may be represented, or you may group the values into categories first (e.
Rather, the value are grouped into ranges and the frequencies determined. Frequency distributions can be depicted in two ways, as a table or as a graph. Table 1 shows an age frequency distribution with five categories of age ranges defined.
The same frequency distribution can be depicted in a graph as shown in Figure 1. This type of graph is often referred to as a histogram or bar chart. Frequency distribution bar chart. Distributions may also be displayed using percentages. For example, you could use percentages to describe the:Central Tendency. The central tendency of a distribution is an estimate of the "center" of a distribution of values. There are three major types of estimates of central tendency:The Mean or average is probably the most commonly used method of describing central tendency.
To compute the mean all you do is add up all the values and divide by the number of values.
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For example, the mean or average quiz score is determined by summing all the scores and dividing by the number of students taking the exam. For example, consider the test score values:The Median is the score found at the exact middle of the set of values. One way to compute the median is to list all scores in numerical order, and then locate the score in the center of the sample. Since both of these scores are 20, the median is 20. If the two middle scores had different values, you would have to interpolate to determine the median.
The mode is the most frequently occurring value in the set of scores.Example: 500 category filterable, sortable, updatable One of the categories in the table of categories that help classify this resource according to the domain of application. This will be 201 upon successful creation of the dataset and 200 afterwards.
Make sure that you check the code that comes with the status attribute to make sure that the dataset creation has been completed without errors. A dictionary that informs about the number of fields of each type. A dictionary with an entry per field (column) in your data. A dictionary with meta information about the fields dictionary. Specifies the locale for this field if it is different from the dataset's locale.
Name of the field. It will be the same as in the source if has not been specified here. Specifies the operational type of the field. It can be numeric, categorical, or text.
Numeric or categorical summary of the field. An array that represents an approximate histogram of the distribution. It consists of value pairs, where the first value is the mean of a histogram bin and the second value is the bin population.[Parlez vous Assurance Maladie] ACS
For more information, see our blog post or read this paper. An array of pairs where the first element of each pair is one of the unique values found in the field and the second element is the count. Only available when the number of distinct values is less than or equal to 32. A measure of 'peakiness' or heavy tails in the field's distribution. A status code that reflects the status of the dataset creation.
Number of milliseconds that BigML. Information about ill-formatted fields that includes the total format errors for the field and a sample of the ill-formatted tokens.
Example: "category": 1 description optional A description of the dataset up to 8192 characters long. Example: "description": "This is a description of my new dataset" fields optional Updates the names, labels, and descriptions of the fields in the new dataset. Example: "description": "This field is a transformation" descriptions optional A description for every of the new fields generated.
Example: "fields": "(window Price -2 0)" label optional Label of the new field. Example: "label": "New price" Labels for each of the new fields generated. Example: "name": "Price" names optional Names for each of the new fields generated. Example: "This is a description of my new sample" name optional The name you want to give to the new sample.
This will be 201 upon successful creation of the sample and 200 afterwards. Make sure that you check the code that comes with the status attribute to make sure that the sample creation has been completed without errors and that it is still available in the in-memory cache.
This is the date and time in which the sample was created with microsecond precision. True when the sample has been created in the development mode. In a future version, you will be able to share samples with other co-workers. It includes the fields' dictionary describing the fields and their summaries and the rows. A description of the status of the sample.
This is the date and time in which the sample was updated with microsecond precision. Each entry includes the column number in the original dataset, the name of the field, the type of the field, and the summary. See this Section for more details.
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