Search results “Analysis of data sample”
Fundamentals of Qualitative Research Methods: Data Analysis (Module 5)
Qualitative research is a strategy for systematic collection, organization, and interpretation of phenomena that are difficult to measure quantitatively. Dr. Leslie Curry leads us through six modules covering essential topics in qualitative research, including what it is qualitative research and how to use the most common methods, in-depth interviews and focus groups. These videos are intended to enhance participants' capacity to conceptualize, design, and conduct qualitative research in the health sciences. Welcome to Module 5. Bradley EH, Curry LA, Devers K. Qualitative data analysis for health services research: Developing taxonomy, themes, and theory. Health Services Research, 2007; 42(4):1758-1772. Learn more about Dr. Leslie Curry http://publichealth.yale.edu/people/leslie_curry.profile Learn more about the Yale Global Health Leadership Institute http://ghli.yale.edu
Views: 150000 YaleUniversity
How to analyze your data and write an analysis chapter.
In this video Dr. Ziene Mottiar, DIT, discusses issues around analyzing data and writing the analysing chapter. The difference between Findings and Analysis chapters is also discussed. This video is useful for anyone who is writing a dissertation or thesis.
Views: 65416 ZieneMottiar
Analysis of Complex Sample Survey Data
Excerpt from Summer 2008 workshop titled "Integrating Cultural and Ethnic Influences on Mental Health" as part of the Collaborative Psychiatric Epidemiology Surveys (CPES) project. Patricia Berglund, Harvard Medical School PowerPoint files are available here: http://www.icpsr.umich.edu/files/CPES/berglund.ppt
Views: 4231 ICPSR
How to select a sample using Data Analysis in Excel 2013
Visit us at http://www.statisticshowto.com for more Excel and statistics videos and tips.
Views: 19958 Stephanie Glen
6.6 Analysis of Sample Data
Analyze Sample Data using a Tally Chart.
Views: 345 CHPSFlippedMath
Qualitative analysis of interview data: A step-by-step guide
Note for December 2018: Please support this project (I did): https://www.gofundme.com/hjalpa-pa-plats The guy behind it is Luai, and you can watch him in this video (only Swedish): https://www.youtube.com/watch?v=fKcb1Tfuoqs The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends. The steps are also described in writing below (Click Show more): STEP 1, reading the transcripts 1.1. Browse through all transcripts, as a whole. 1.2. Make notes about your impressions. 1.3. Read the transcripts again, one by one. 1.4. Read very carefully, line by line. STEP 2, labeling relevant pieces 2.1. Label relevant words, phrases, sentences, or sections. 2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant. 2.3. You might decide that something is relevant to code because: *it is repeated in several places; *the interviewee explicitly states that it is important; *you have read about something similar in reports, e.g. scientific articles; *it reminds you of a theory or a concept; *or for some other reason that you think is relevant. You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you. It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds. STEP 3, decide which codes are the most important, and create categories by bringing several codes together 3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand. 3.2. You can create new codes by combining two or more codes. 3.3. You do not have to use all the codes that you created in the previous step. 3.4. In fact, many of these initial codes can now be dropped. 3.5. Keep the codes that you think are important and group them together in the way you want. 3.6. Create categories. (You can call them themes if you want.) 3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever. 3.8. Be unbiased, creative and open-minded. 3.9. Your work now, compared to the previous steps, is on a more general, abstract level. You are conceptualizing your data. STEP 4, label categories and decide which are the most relevant and how they are connected to each other 4.1. Label the categories. Here are some examples: Adaptation (Category) Updating rulebook (sub-category) Changing schedule (sub-category) New routines (sub-category) Seeking information (Category) Talking to colleagues (sub-category) Reading journals (sub-category) Attending meetings (sub-category) Problem solving (Category) Locate and fix problems fast (sub-category) Quick alarm systems (sub-category) 4.2. Describe the connections between them. 4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study. STEP 5, some options 5.1. Decide if there is a hierarchy among the categories. 5.2. Decide if one category is more important than the other. 5.3. Draw a figure to summarize your results. STEP 6, write up your results 6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results. 6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example: *results from similar, previous studies published in relevant scientific journals; *theories or concepts from your field; *other relevant aspects. STEP 7 Ending remark Nb: it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.) Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze: *notes from participatory observations; *documents; *web pages; *or other types of qualitative data. STEP 8 Suggested reading Alan Bryman's book: 'Social Research Methods' published by Oxford University Press. Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE. Text and video (including audio) © Kent Löfgren, Sweden
Views: 677716 Kent Löfgren
Quick Data Analysis Workflow Sample
Quick Data Analysis Workflow from data import, visual data inspection to dashboard presentation and more ...
Views: 615 ANKHORFlowSheet
2 Sample T Test using Excel Data Analysis Tool Pak
We check the significance of the difference in means between 2 samples using a T Test (in Excel). Dataset can be downloaded at www.learnanalytics.in/blog/wp-content/uploads/2014/02/car_sales.xlsx
Views: 13461 Learn Analytics
Data Analysis with Javascript and Chartjs - Part 1 (Getting a Sample)
Data Analysis with Javascript and Chartjs - Part 1 (Getting a Sample) In This Video Ive chosen a dataset that has all of the Companies committed to RechargeNY. Ive Taken A sample Of All of The Companies in Brooklyn and added it To a Single Array Check Out Recharge NY and follow along! Knowledge of Basic Programming is required....
Views: 502 Ty Reddick
Student's Web Data: Sample analysis
Using a student's data, I show you how you can create some simple visuals, how to deal with some of the tricky parts of data formatting and some basic calculations to produce. Formatting can always be the save or the impediment when working in Excel. If you have troubles with time and date formats, you may simply have to reset the formats or even retype some data.
Views: 174 Heidi Baez
H6Q1: Two-sample t-test with the Data Analysis add-on
If you don't know how to install the Data Analysis Toolpak (PCs only), check the other video I uploaded. Here, the Data Analysis add-on to Excel 2007 (PC) is used to perform a two sample t-test. You might be able to get similar results just as easily with the Mac version and StatPlus, but I'm not sure. I doubt it. I didn't show this in the video, but the original data is on Sheet 1. The Data Analysis output goes on a new sheet (Sheet 2).
Views: 4604 UIUCEconTA
research paper data analysis sample
Get 15% Promo code: https://goo.gl/TIo1T2?52513
Compositional data analysis: How important are the sample space and its structure?
AUTHORS: V. Pawlowsky-Glahn and J.J. Egozcue SPEAKER: V. Pawlowsky-Glahn EVENT: Probabilistic Microbial Modeling Symposium San Diego (USA) June 21-22, 2018 DESCRIPTION: The sample space of observed data is usually explicitly or implicitly assumed to be the multidimensional real space or a subset of the same. In both cases the geometry is taken to be the usual Euclidean geometry. This basic aspect plays an essential role in the analysis of data, and very specially in the case of compositional data, where it can lead to spurious results or to poor approximations. We present a summary of the present attempts to analyse compositional data in the field of microbiome data, as well as the implications of the different approaches.
6.5 - Preparing Data for Analysis of a Complex Sample
This video is part of a course at Simon Fraser University and is intended for students in the course. In it, students will learn how to prepare their data to allow proper analysis accounting for the complex sampling design of NHANES.
Views: 9131 Scott Venners
9. Network analysis of Expression data – sample-sample correlation graph 1 (Practical Session) -
Lecture by professor Tom Freeman Filmed during a half-day training course held at The Roslin Institute, January 2015 (Recommended Youtube playback settings for the best viewing experience: 1080p HD) ********************************* Content list: 9. Network analysis of Expression data – sample-sample correlation graph 1 (Practical Session) Example dataset 2 – GNF mouse tissue atlas dataset - minimum correlation setting - preprocessing; transpose data - graph topology
Download data analysis venn digram questions http://careerstudydefence.com/afcat-reasoning-3/
Views: 3353 Career Study
Choosing which statistical test to use - statistics help.
Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties. There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.
Views: 695339 Dr Nic's Maths and Stats
BROWSE The Internet EASY way with The Audiopedia owned Lightina Browser Android app! INSTALL NOW - https://play.google.com/store/apps/details?id=com.LightinaBrowser_8083351 What is DESCRIPTIVE STATISTICS? What does DESCRIPTIVE STATISTICS mean? DESCRIPTIVE STATISTICS meaning - DESCRIPTIVE STATISTICS definition - DESCRIPTIVE STATISTICS explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Descriptive statistics are statistics that quantitatively describe or summarize features of a collection of information. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. This generally means that descriptive statistics, unlike inferential statistics, are not developed on the basis of probability theory. Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented. For example in papers reporting on human subjects, typically a table is included giving the overall sample size, sample sizes in important subgroups (e.g., for each treatment or exposure group), and demographic or clinical characteristics such as the average age, the proportion of subjects of each sex, the proportion of subjects with related comorbidities etc. Some measures that are commonly used to describe a data set are measures of central tendency and measures of variability or dispersion. Measures of central tendency include the mean, median and mode, while measures of variability include the standard deviation (or variance), the minimum and maximum values of the variables, kurtosis and skewness. Descriptive statistics provide simple summaries about the sample and about the observations that have been made. Such summaries may be either quantitative, i.e. summary statistics, or visual, i.e. simple-to-understand graphs. These summaries may either form the basis of the initial description of the data as part of a more extensive statistical analysis, or they may be sufficient in and of themselves for a particular investigation. For example, the shooting percentage in basketball is a descriptive statistic that summarizes the performance of a player or a team. This number is the number of shots made divided by the number of shots taken. For example, a player who shoots 33% is making approximately one shot in every three. The percentage summarizes or describes multiple discrete events. Consider also the grade point average. This single number describes the general performance of a student across the range of their course experiences. The use of descriptive and summary statistics has an extensive history and, indeed, the simple tabulation of populations and of economic data was the first way the topic of statistics appeared. More recently, a collection of summarisation techniques has been formulated under the heading of exploratory data analysis: an example of such a technique is the box plot. In the business world, descriptive statistics provides a useful summary of many types of data. For example, investors and brokers may use a historical account of return behavior by performing empirical and analytical analyses on their investments in order to make better investing decisions in the future. Univariate analysis involves describing the distribution of a single variable, including its central tendency (including the mean, median, and mode) and dispersion (including the range and quantiles of the data-set, and measures of spread such as the variance and standard deviation). The shape of the distribution may also be described via indices such as skewness and kurtosis. Characteristics of a variable's distribution may also be depicted in graphical or tabular format, including histograms and stem-and-leaf display.
Views: 11721 The Audiopedia
Hypothesis t-test for One Sample Mean using Excel’s Data Analysis
This video shows how to conduct a one-sample hypothesis t-test for the mean in Microsoft Excel using the built-in Data Analysis (from raw data). How to load Data Analysis in Excel: https://youtu.be/SqpSwxJ9t2k
Views: 81098 Joshua Emmanuel
Simple Data Analysis for Teachers Using Excel
Exploring some basic data analysis in excel
Views: 44213 Jon Jasinski
Sample data analysis
Views: 52 Darren Morton
Analysing Questionnaires
This video is part of the University of Southampton, Southampton Education School, Digital Media Resources http://www.southampton.ac.uk/education http://www.southampton.ac.uk/~sesvideo/
Types of Data: Nominal, Ordinal, Interval/Ratio - Statistics Help
The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 799164 Dr Nic's Maths and Stats
Using the Terminal 4: A Sample Data Analysis
This video demonstrates a sample data analysis using the data described in our second video. Here we perform an "in silico Northern" using grep.
Views: 1164 David Coil
Analyzing Quantitative PCR Data
Relative and absolute methods of qPCR analysis. Created for an assignment for BIOC3001: Molecular Biology at the University of Western Australia. ****SCRIPT**** [I know it's a bit fast] qPCR or quantitative real-time PCR… ….is simply classic PCR monitored using fluorescent dyes or probes. qPCR is accurate, reliable and extremely sensitive, it can even detect a SINGLE copy of a specific transcript. qPCR is commonly coupled to reverse transcription to measure gene expression. No wonder it is so important for molecular diagnostics, life sciences, agriculture, and medicine. Firstly, let's go over the NUTS and BOLTS of qPCR. For this you use a fluorescent dye which binds to the DNA. As qPCR progresses, the fluorescent signal increases. Ideally the signal should double with every cycle, which is then plotted. Because there are few template strands to start with, initially there’s a faint signal. Eventually, usually after 15 cycles, the signal rises above the background noise and can be detected. We call this the THRESHOLD CYCLE, Ct, the point from which all quantitative data analysis begins. But how do you analyse qPCR data? You can either use an absolute quantification method, with a standard curve, OR a relative method, using one or more reference genes to standardize and compare the differences in Ct values between two treatments. The absolute standard curve method determines ORIGINAL DNA concentration by comparing the Ct value of the sample of interest with a standard curve. To create the standard curve, you need to make DNA samples of different KNOWN concentrations. After doing PCR on these, you will see different PCR plots for each standard ….. and unsurprisingly they have different Ct values. The GREATER the concentration of the original DNA sample, the SMALLER the Ct value. So if you plot ORIGINAL DNA concentration against the Ct values. You will have a standard curve like this….. Now let’s say the PCR plot of your unknown DNA sample is somewhere here….. ...which corresponds to this Ct value on the standard curve here…. Using the standard curve you can figure out the log concentration of your DNA sample to be x. As this is in log scale, you can simply calculate your sample DNA concentration to be 10 to the power of x. Absolute analysis is suitable when you want to determine the ACTUAL transcript copy number, that is the level of gene expression. On the other hand, Relative quantification is used when you want to COMPARE the difference in gene expression BETWEEN two treatments, for example light or dark treated Arabadopsis thaliana. This is done using one or more reference genes, such as actin, which are expressed at the SAME level for both treatments. You then perform qPCR on both your samples and the reference genes, find out the DIFFERENCE between the two Cts values, delta Ct, in EACH treatment. Now the RATIO of the two delta Cts …[pause a bit] . tells you how much gene expression has changed. For instance, in the dark treatment, the Ct value of your reference gene is at THIS level, the Ct value of your target gene is THIS Level. So you have this delta Ct which is the difference in Cts in the first treatment. in the dark treatment, the Ct value of your reference gene is STILL at THIS level, but the Ct value of your target gene may become only this much. So the ratio of the two Ct values is.. delta Ct(dark treatment) divided by delta Ct(light treament) equals one third ….showing the delta Ct has DECREASED by a factor of 3, which means that gene expression of the target gene is GREATER in the dark treated sample. This is how relative quantification using a reference gene helps detect change in the expression of your target gene. In conclusion, there are two ways to quantify transcripts using qPCR: absolute quantification using a standard curve, and relative quantification using a reference gene. The method used depends on whether you want to determine the ACTUAL number of transcripts or the RELATIVE change in gene expression.
Views: 183771 TARDIStennant
Excel Data Analysis Toolpak: How to generate a Random Sample of Data Values
This short video details how to generate a random sample of data values using Excel's Data Analysis Toolpak. In particular, we generate two types of random sample. The first being a pure random sample, and the second being a systematic or periodic sample.
Views: 339 Maths and Stats
Compositional data analysis: How important are the sample space and its structure?
Speaker: Vera Pawlowsky-Glahn Abstract: The sample space of observed data is usually explicitly or implicitly assumed to be the multidimensional real space or a subset of the same. In both cases the geometry is taken to be the usual Euclidean geometry. This basic aspect plays an essential role in the analysis of data, and very specially in the case of compositional data, where it can lead to spurious results or to poor approximations. We present a summary of the present attempts to analyze compositional data in the field of microbiome data, as well as the implications of the different approaches.
Views: 201 Jamie Morton
Practice 4 - Analyzing and Interpreting Data
Science and Engineering Practice 3: Analyzing and Interpreting Data Paul Andersen explains how scientists analyze and interpret data. Data can be organized in a table and displayed using a graph. Students should learn how to present and evaluate data. Intro Music Atribution Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License
Views: 59889 Bozeman Science
The "z Test: Two Sample for Means" Analysis in Excel
This video demonstrates how to use the “z-Test: Two Samples for Means” analysis in Microsoft Excel. This z-test analysis is used to determine if there is a statistically significant difference between two sets of scores when the population variance is known.
Views: 16043 Dr. Todd Grande
Single sample diversity analysis on a metagenomics data set (BioNumerics 7)
In this video you will learn how to perform a single sample diversity analysis on processed metagenomics data in a BioNumerics Seven database.
Views: 1655 BioNumerics
Exploring the Retail Analysis Sample
***This is an updated version of the Retail Analysis Sample video.*** Explore the Retail Analysis Sample, based on real data from obviEnce (http://www.obvience.com), and learn the ins and outs of Power BI while you are at it! Sign up for the Power BI Preview at https://powerbi.com/dashboards and log in at https://app.powerbi.com
Views: 4903 Microsoft Power BI
Perform a complex sample analysis
Epi Info 7 allows users to rapidly develop questionnaires, customize data entry, analyze data and create custom reports. As part of the CDC's supported data tools, Epi Info provides interactive analysis of surveillance system data. Epi Info features case cluster mapping using Google maps, contact tracing using social network diagrams, SQL Server compatibility for large databases and multiuser applications, requires no IT support to install and future compatibility with hand-held devices. Comments on this video are allowed in accordance with our comment policy: http://www.cdc.gov/SocialMedia/Tools/CommentPolicy.html This video can also be viewed at http://www.cdc.gov/ophss/csels/videos/epiinfo/18/18_Epi_Info_7_Complex_sample_analysis_low_res.mp4
Hypothesis z-test for One Sample Mean using Excel’s Data Analysis
This video shows how to conduct a one-sample hypothesis z-test for the mean in Microsoft Excel using the built-in Data Analysis (from raw data). How to load Data Analysis in Excel: https://youtu.be/SqpSwxJ9t2k Data used: Age 25 30 23 21 24 22 24 25 22 21 22 18 20 24 24 22 23 19 21 20 21 21 19 21 19 24 20 20 20 23 22 23 19 22 19
Views: 40395 Joshua Emmanuel
SPSS for Beginners 1: Introduction
Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.
Views: 1385551 Research By Design
Student's t-test
Excel file: https://dl.dropboxusercontent.com/u/561402/TTEST.xls In this video Paul Andersen explains how to run the student's t-test on a set of data. He starts by explaining conceptually how a t-value can be used to determine the statistical difference between two samples. He then shows you how to use a t-test to test the null hypothesis. He finally gives you a separate data set that can be used to practice running the test. Do you speak another language? Help me translate my videos: http://www.bozemanscience.com/translations/ Music Attribution Intro Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License Outro Title: String Theory Artist: Herman Jolly http://sunsetvalley.bandcamp.com/track/string-theory All of the images are licensed under creative commons and public domain licensing: Critical Values of the Student’s-t Distribution. (n.d.). Retrieved April 12, 2016, from http://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm File:Hordeum-barley.jpg - Wikimedia Commons. (n.d.). Retrieved April 11, 2016, from https://commons.wikimedia.org/wiki/File:Hordeum-barley.jpg Keinänen, S. (2005). English: Guinness for strenght. Retrieved from https://commons.wikimedia.org/wiki/File:Guinness.jpg Kirton, L. (2007). English: Footpath through barley field. A well defined and well used footpath through the fields at Nuthall. Retrieved from https://commons.wikimedia.org/wiki/File:Footpath_through_barley_field_-_geograph.org.uk_-_451384.jpg pl.wikipedia, U. W. on. ([object HTMLTableCellElement]). English: William Sealy Gosset, known as “Student”, British statistician. Picture taken in 1908. Retrieved from https://commons.wikimedia.org/wiki/File:William_Sealy_Gosset.jpg The T-Test. (n.d.). Retrieved April 12, 2016, from http://www.socialresearchmethods.net/kb/stat_t.php
Views: 419011 Bozeman Science
StatQuest: Principal Component Analysis (PCA), Step-by-Step
Principal Component Analysis, is one of the most useful data analysis and machine learning methods out there. It can be used to identify patterns in highly complex datasets and it can tell you what variables in your data are the most important. Lastly, it can tell you how accurate your new understanding of the data actually is. In this video, I go one step at a time through PCA, and the method used to solve it, Singular Value Decomposition. I take it nice and slowly so that the simplicity of the method is revealed and clearly explained. If you are interested in doing PCA in R see: https://youtu.be/0Jp4gsfOLMs For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
Sample Memo Analysis
This video analysis a sample memo
Views: 4675 Ellie Bunting
Introduction to Text Analysis with NVivo 11 for Windows
It’s easy to get lost in a lot of text-based data. NVivo is qualitative data analysis software that provides structure to text, helping you quickly unlock insights and make something beautiful to share. http://www.qsrinternational.com
Views: 118693 NVivo by QSR
Interview with a Data Scientist
This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000
Views: 285183 Udacity
How to analyze a case study?
This presentation describes an approach to analyze a case study - especially case studies from management discipline. Dr. Pradeep Racherla, Program Director & Associate Professor Marketing, Woxsen School of Business, elucidates different components of a case study and offers a framework to analyze a case study.
Views: 167422 Sanjay
Data Analysis Sample using microsft PowerBI Service
This a sample for analyzing a volunteers data and their statistics in different kind of skills(the legend and labels are in Arabic)
Views: 12 Hani Mounla
Data Interpretation techniques | Sample Data Interpretation questions | TalentSprint
Preparing for Bank, SSC or Govt Exams? Join TalentSprint and Succeed like 6000+ students. TalentSprint's Video and LIVE Courses help aspirants get ready for Bank, SSC and Govt Exams from the comfort of their home. Learn from expert LIVE classes and videos along with Practice on latest pattern questions in real exam interface to Perfect your preparation for the hyper-competitive world. Visit: https://goo.gl/FZhBbf or Call 040 67763553 Our Courses: Bank & SSC Exams LIVE Course: 2500 Videos | 1500 ebooks | 500+ Practice Tests | 3 Months Validity Price: 4500 Bank & SSC Exams Video Course: 2500 Videos | 1500 ebooks | 500+ Practice Tests | 3 Months Validity Price: 3600 Quantitative Aptitude Video Course: 1600 Videos | 400 ebooks | 100+ Practice Tests | 3 Months Validity Price: 1800 Reasoning Ability Video Course : 950 Videos | 300 ebooks | 70+ Practice Tests | 3 Months Validity Price: 1800 English Language Video Course: 1800 Videos | 450 ebooks | 110+ Practice Tests | 3 Months Validity Price: 1800 General Knowledge Video Course: 136 Videos | 158 ebooks | 80+ Practice Tests | 3 Months Validity Price: 1800 Current Affairs Video Course: 60 Videos | 52 ebooks | 375+ Practice Tests | 3 Months Validity Price: 1800 #BankandSSCExamsVideoCourses #StartingAtJustRs1800 #Call_04067763553 #TalentSprint
Datalab setup in the GCloud platform and sample data analysis in datalab by Dr  N Senthil Madasamy
Datalab setup in the google Cloud platform and sample data analysis in datalab by Dr N Senthil Madasamy Associate Professor
Webinar: LC-MS-based Metabolomics: Workflows, Strategies and Challenges
Metabolomics is the comprehensive analysis of endogenous metabolites in biological specimens. Metabolomics technologies are increasingly used to study metabolism in model systems and for discovery of disease signatures using samples from clinical cohorts. It is a technically challenging field owing to the wide dynamic of concentrations that must be measured as well as the diversity of physical properties among the molecules that constitute the metabolome, for example ranging from polar and acidic compounds of the TCA cycle to nonpolar and neutral compounds like triglycerides. Liquid chromatography tandem mass spectrometry (LC-MS) is an analytical technology that is well matched to this challenge and has found wide use in the field. In this webinar, Dr. Clary Clish (Broad Institute of MIT and Harvard) will discuss scientific challenges posed by metabolomics and LC-MS-based measurements and provide an overview of LC-MS workflows. He will describe the utility and limitations of LC-MS methods, what information can be obtained from each, and how to match techniques with experimental questions about the metabolome. What you will learn in this webinar: The primary challenges encountered in LC-MS-based metabolomics Methods for preparing samples, including quality measures The types of information that can be obtained using this method Who should attend: Those needing a more complete understanding of the complexities involved in LC-MS-based metabolomics Bench scientists and clinicians who need to become knowledgeable about designing experiments or studies in which metabolomics will be used View more webinars on currentprotocols.com!
Views: 19109 CurrentProtocols
Coding Part 1: Alan Bryman's 4 Stages of qualitative analysis
An overview of the process of qualitative data analysis based on Alan Bryman's four stages of analysis. Reference Bryman, A (2001) Social Research Methods, Oxford: Oxford University Press This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) http://creativecommons.org/licenses/by-nc-sa/4.0/
Views: 194088 Graham R Gibbs
Excel 2013 Statistical Analysis #25: Probability Basics: Sample Points, Events & Event Probabilities
Download files: http://people.highline.edu/mgirvin/excelisfun.htm Topics in this video: 1. (00:12) Review Handwritten PDF Notes about Probability, Random Events, Sample Points, Sample Space, Count Rule For Size of Sample Space, Listing all Sample Points with Tree Diagram and Table, Methods of Probability such as Classical, Relative Frequency and Subjective, Requirements for Probability, Events and Probability of Events 2. (14:30) In Excel: Experiment of Flipping Coin Three Times: Find all Sample Points, Calculate Probabilities and practice finding Probabilities of Events by listing all the sample points and then adding all the probabilities for each Sample Point to get the Probability of the Event 3. (21:09) Frequency Distribution Built from Sample Space in order to find Probabilities for Events 4. (23:46) In Excel: Experiment of Rolling Two Die: Find all Sample Points, Calculate Probabilities and practice finding Probabilities of Events by listing all the sample points and then adding all the probabilities for each Sample Point to get the Probability of the Event
Views: 14674 ExcelIsFun

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