Home
Search results “Data analysis with r studio”
Basic Data Analysis in RStudio
 
25:56
This clip explains how to produce some basic descrptive statistics in R(Studio). Details on http://eclr.humanities.manchester.ac.uk/index.php/R_Analysis. You may also be interested in how to use tidyverse functionality for basic data analysis: https://youtu.be/xngavnPBDO4
Views: 132572 Ralf Becker
Introduction to Data Science with R - Data Analysis Part 1
 
01:21:50
Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 970544 David Langer
Data Analysis in R
 
27:20
Here are two examples of numeric and non numeric data analyses. Both files are obtained from infochimps open access online database.
Views: 41435 Ani Aghababyan
R Studio: Importing & Analyzing Data
 
07:22
Tutorial on importing data into R Studio and methods of analyzing data.
Views: 180247 MrClean1796
Exploratory Data Analysis in RStudio with ggplot
 
11:02
In this video I show you how to quickly and easily do some exploratory data analysis with graphs in RStudio using ggplot and the tidyverse library. I start by showing you how to load in the tidyverse library and be sure to be careful about spelling and uppercase and lowercase letters as R is very picky with that. Then I load in the data set and I use ggplot to create some cool graphs based on registered and new (casual) users. The data set I use for this is the bike sharing data set which is available from the University of California Irving. This is a public domain and freely available data set. But I could've used any data set it would've mattered. I show you a basic graph and then I add a color variation to it so we can start drawing some insights. From the final graph I show you it's you to see that there's a big area where there's a lot of registered or subscriber usage and then there is also an area with lower temperatures that is more predominantly new users. With this data we can then see two opportunities - obviously the large one is to market to new users during the main season for bike sharing (warmer weather). And we can also see the opportunity to increase registered users during the off-season (cold weather - i.e. below 40 degrees or so. This is not a complete everything tutorial on exploratory data analysis and data science. I just want to show you how easy and quick it is with RStudio, ggplot and a few formulas which are easy to use to get meaningful data and to start drawing valuable and reproducible insights. I hope you found this video interesting and helpful. Please take a moment to subscribe, like and leave me a comment. I love to hear from my viewers and subscribers. Let me know how this worked for you or if you took it on a different angle or use a different data set. Thanks for watching. God bless.
Views: 2740 Tech Know How
R programming for beginners – statistic with R (t-test and linear regression) and dplyr and ggplot
 
15:49
R programming for beginners - This video is an introduction to R programming. I have another channel dedicated to R teaching: https://www.youtube.com/c/rprogramming101 In this video I provide a tutorial on some statistical analysis (specifically using the t-test and linear regression). I also demonstrate how to use dplyr and ggplot to do data manipulation and data visualisation. Its R programming for beginners really and is filled with graphics, quantitative analysis and some explanations as to how statistics work. If you’re a statistician, into data science or perhaps someone learning bio-stats and thinking about learning to use R for quantitative analysis, then you’ll find this video useful. Importantly, R is free. If you learn R programming you’ll have it for life. This video was sponsored by the University of Edinburgh. Find out more about their programmes at http://edin.ac/2pTfis2 This channel focusses on global health and public health - so please consider subscribing if you’re someone wanting to make the world a better place – I’d love to you join this community. I have videos on epidemiology, study design, ethics and many more.
R Introduction: Data Analysis and Plotting
 
14:15
This video uses a complex, yet not to large, data set to conduct a simple manipulation of data in R and RStudio. We will introduce data frames, matrices and variables. It demonstrates how to plot charts in R and how to gradually build them out of basic visual elements. The explanation will carefully avoid more complex statistical concepts. The data for this lesson can be obtained from (note different file name): * http://visanalytics.org/youtube-rsrc/r-data/Vic-2013-LGA-Profiles-NoPc.csv The source for the R code of this video can be found here (with some small discrepancies): * http://visanalytics.org/youtube-rsrc/r-intro/Demo-A2-Basic-Data-Analysis-and-Plotting.r Videos in data analytics and data visualization by Jacob Cybulski, visanalytics.org.
Views: 24862 ironfrown
Making a panel dataset in R studio
 
11:10
Hello researchers, This video will help you making a panel dataset in R from cross-section and time-series data available.
Views: 11797 Sarveshwar Inani
Transforming Data - Data Analysis with R
 
03:01
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 52589 Udacity
Social Network Analysis with R | Examples
 
26:25
Social network analysis with several simple examples in R. R file: https://goo.gl/CKUuNt Data file: https://goo.gl/Ygt1rg Includes, - Social network examples - Network measures - Read data file - Create network - Histogram of node degree - Network diagram - Highlighting degrees & different layouts - Hub and authorities - Community detection R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 19885 Bharatendra Rai
RStudio Layout - Data Analysis with R
 
00:39
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 2085 Udacity
Transforming Data - Data Analysis with R
 
02:42
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 13253 Udacity
Text Analytics With R | How to Connect Facebook with R | Analyzing Facebook in R
 
07:59
In this text analytics with R tutorial, I have talked about how you can connect Facebook with R and then analyze the data related to your facebook account in R or analyze facebook page data in R. Facebook has millions of pages and getting emotions and text from these pages in R can help you understand the mood of people as a marketer. Text analytics with R,how to connect facebook with R,analyzing facebook in R,analyzing facebook with R,facebook text analytics in R,R facebook,facebook data in R,how to connect R with Facebook pages,facebook pages in R,facebook analytics in R,creating facebook dataset in R,process to connect facebook with R,facebook text mining in R,R connection with facebook,r tutorial for facebook connection,r tutorial for beginners,learn R online,R beginner tutorials,Rprg
Regression in R(Studio)
 
16:41
This clip demonstrates how to use R to run a regression. This clip is a companion to the following website which gives an introduction to R programming for econometricians. The dataset used is also available from that website: http://eclr.humanities.manchester.ac.uk/index.php/R Table of Contents: 00:00 - Introduction 04:01 - Regression Output 06:53 - Accessing Regression Results 10:09 - no dataframe 12:53 - no constant 13:37 - Subsets/Subsamples
Views: 21319 Ralf Becker
R Markdown Documents - Data Analysis with R
 
02:33
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 15363 Udacity
Introduction to Data Science with R - Data Analysis Part 2
 
59:48
Part 2 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 143170 David Langer
Introduction to Cluster Analysis with R - an Example
 
18:11
Provides illustration of doing cluster analysis with R. R File: https://goo.gl/BTZ9j7 Machine Learning videos: https://goo.gl/WHHqWP Includes, - Illustrates the process using utilities data - data normalization - hierarchical clustering using dendrogram - use of complete and average linkage - calculation of euclidean distance - silhouette plot - scree plot - nonhierarchical k-means clustering Cluster analysis is an important tool related to analyzing big data or working in data science field. Deep Learning: https://goo.gl/5VtSuC Image Analysis & Classification: https://goo.gl/Md3fMi R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 104884 Bharatendra Rai
Rstudio - an introduction for data analysis
 
24:25
RStudio for beginners doing data analysis -R environment - creating objects -loading data (a txt file) - saving your code -How to refer to variables | plots for univariate continuous variables (histogram, boxplot) -Comments with # - Altering a commands default settings (eg 1 sample t-test)
Views: 6218 Phil Chan
RStudio Layout - Data Analysis with R
 
02:23
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 14924 Udacity
Read and Subset Data - Data Analysis with R
 
03:51
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 8620 Udacity
R: Exploratory Data Analysis (EDA), Univariate analysis
 
30:01
One of the first steps to data analysis is to perform Exploratory Data Analysis. In this video we go over the basics of univariate data analysis, or analyzing each variable to better get to know our data. Here's the dataset used in this video: https://drive.google.com/open?id=0B67hcgV97X0mbnRYNzhYLU53X2c
Views: 4821 James Dayhuff
R: Exploratory Data Analysis (EDA), Multivariate Analysis
 
29:51
One of the first steps to data analysis is to perform Exploratory Data Analysis. In this video we go over the basics of multivariate data analysis, or analyzing the relationship between variables Here's the dataset used in this video: https://drive.google.com/open?id=0B67hcgV97X0mbnRYNzhYLU53X2c
Views: 8318 James Dayhuff
Introduction to Data Science with R - Data Analysis Part 3
 
55:33
Part 3 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 64213 David Langer
Exploratory data analysis 1
 
27:40
Three R scripts showing some simple exploratory data analyses in R: contingency tables, histograms, boxplots/dotplots, and groupwise means.
Views: 29856 James Scott
Install RStudio on Windows - Data Analysis with R
 
02:12
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 20972 Udacity
Missing Data Analysis : Multiple Imputation in R
 
14:22
Paper: Advanced Data Analysis Module: Missing Data Analysis : Multiple Imputation in R Content Writer: Souvik Bandyopadhyay
Views: 21349 Vidya-mitra
Getting Stock Data In R
 
08:59
In this tutorial, we will use the quantmod package to obtain stock data. If you don't have R and R Studio installed, you can get them here: R Studio: https://www.rstudio.com/products/rstudio/download/ R: https://cran.r-project.org/mirrors.html Source Code and Blog Post: http://programmingforfinance.com/2017/10/different-ways-to-obtain-and-manipulate-stock-data-in-r-using-quantmod/ My Website: http://programmingforfinance.com/
Views: 9068 codebliss
Business Analytics With R | Data Analytics with R | Analytics with R | Programming with R | Edureka
 
01:36:12
This tutorial will deep dive into data analysis using 'R' language. This video is specially designed for beginners intending to get into the analysis domain. To learn more about R, click here: http://goo.gl/uHfGbN The topics related to ‘R’ language are extensively covered in our ‘Mastering Data Analytics with R’ course. For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 14542 edureka!
Time Series Analysis - 1 | Time Series in R | Time Series Forecasting | Data Science | Simplilearn
 
32:49
This Time Series Analysis (Part-1) in R tutorial will help you understand what is time series, why time series, components of time series, when not to use time series, why does a time series have to be stationary, how to make a time series stationary and at the end, you will also see a use case where we will forecast car sales for 5th year using the given data. Link to Time Series Analysis Part-2: https://www.youtube.com/watch?v=Y5T3ZEMZZKs You can also go through the slides here: https://goo.gl/RsAEB8 A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this video and understand what is time series and how to implement time series using R. Below topics are explained in this " Time Series in R Tutorial " - 1. Why time series? 2. What is time series? 3. Components of a time series 4. When not to use time series? 5. Why does a time series have to be stationary? 6. How to make a time series stationary? 7. Example: Forcast car sales for the 5th year To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment. Why learn Data Science with R? 1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc 2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019 3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709 4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies, and includes R CloudLab for practice. 1. Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. 2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing. 3. As a part of the data science with R training course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and the Internet. Four additional projects are also available for further practice. The Data Science with R is recommended for: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Time-Series-Analysis-gj4L2isnOf8&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 24045 Simplilearn
Time Series In R | Time Series Forecasting | Time Series Analysis | Data Science Training | Edureka
 
34:00
( Data Science Training - https://www.edureka.co/data-science ) In this Edureka YouTube live session, we will show you how to use the Time Series Analysis in R to predict the future! Below are the topics we will cover in this live session: 1. Why Time Series Analysis? 2. What is Time Series Analysis? 3. When Not to use Time Series Analysis? 4. Components of Time Series Algorithm 5. Demo on Time Series For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 79333 edureka!
Advanced Analytics with R and SQL
 
59:22
R is the lingua franca of Analytics. SQL is the world’s most popular database language. What magic can you make happen by combining the power of R and SQL for Data Science and Advanced Analytics? Imagine the power of exploring, transforming, modeling, and scoring data at scale from the comfort of your favorite R environment. Now, imagine operationalizing the models you create directly in SQL Server, allowing your applications to use them from T-SQL, executed right where your data resides. Come learn how to build and deploy intelligent applications that combine the power of R, SQL Server, thousands of open source R extension packages, and high-performance implementations of the most popular machine learning algorithms at scale.
Introduction to R Data Analysis: Data Cleaning
 
01:04:00
Data Cleaning and Dates using lubridate, dplyr, and plyr
Views: 45900 John Muschelli
RQDA 1. Introduction of Qualitative Data Analysis with RQDA
 
04:48
Learn basic level qualitative data analysis with RQDA. If you face difficulty in installing R and R studio watch following clip on youtube: https://youtu.be/aSGujXXLu-U
Views: 1463 Atiq Rehman
Correlation Plots : Exploratory Data Analysis with R
 
06:38
Correlation Plots : Exploratory Data Analysis with R
Factor Variables - Data Analysis with R
 
01:48
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 6608 Udacity
Intro to Data Visualization with R & ggplot2
 
01:11:15
The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s rich and powerful data visualization capabilities. While tools like Excel, Power BI, and Tableau are often the go-to solutions for data visualizations, none of these tools can compete with R in terms of the sheer breadth of, and control over, crafted data visualizations. As an example, R’s ggplot2 package provides the R programmer with dozens of print-quality visualizations – where any visualization can be heavily customized with a minimal amount of code. In this webinar Dave Langer will provide an introduction to data visualization with the ggplot2 package. The focus of the webinar will be using ggplot2 to analyze your data visually with a specific focus on discovering the underlying signals/patterns of your business. Attendees will learn how to: • Craft ggplot visualizations, including customization of rendered output. • Choose optimal visualizations for the type of data and the nature of the analysis at hand. • Leverage ggplot2’s powerful segmentation capabilities to achieve “visual drill-in of data”. • Export ggplot2 visualizations from RStudio for use in documents and presentations. Repository: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Introduction%20to%20Data%20Visualization%20with%20R%20and%20ggplot2 -- Learn more about Data Science Dojo here: https://hubs.ly/H0dTtFq0 See what our past attendees are saying here: https://hubs.ly/H0dTtFw0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 105101 Data Science Dojo
R Tutorial For Beginners | R Programming Tutorial l R Language For Beginners | R Training | Edureka
 
01:33:00
( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Tutorial (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R tool and help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Why do we need Analytics ? 2. What is Business Analytics ? 3. Why R ? 4. Variables in R 5. Data Operator 6. Data Types 7. Flow Control 8. Plotting a graph in R Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 472800 edureka!
Analyze European survey data statistics in R (Rstudio)
 
13:09
Prepare, clean, wrangle, and analyze political science data in R. Code and walkthrough for students or beginners learning quantitative, statistical analysis in R. This shows you how to do common data cleaning tasks, make a plot of country averages over time, and estimate a basic linear regression model with Eurobarometer data. How important is religion in different European countries? Which variables predict the probability individuals will vote in the European Parliament elections? Data for this script can be downloaded here: https://www.dropbox.com/s/5bdhel8l7c5r59z/eurobarometer_trends.dta?dl=0 The script can be found here: https://gist.github.com/jmrphy/9020745 Newsletter: https://tinyletter.com/jmrphy Blog: http://jmrphy.net/blog Twitter: http://twitter.com/jmrphy Podcast: http://jmrphy.libsyn.com/ Facebook: https://www.facebook.com/otherlifenow/ Periscope: https://www.pscp.tv/jstnmrphy Instagram: https://www.instagram.com/jstnmrphy/
Views: 3232 Justin Murphy
Conditional Means - Data Analysis with R
 
04:51
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 10873 Udacity
R - Sentiment Analysis and Wordcloud with R from Twitter Data | Example using Apple Tweets
 
23:01
Provides sentiment analysis and steps for making word clouds with r using tweets about apple obtained from Twitter. Link to R and csv files: https://goo.gl/B5g7G3 https://goo.gl/W9jKcc https://goo.gl/khBpF2 Topics include: - reading data obtained from Twitter in a csv format - cleaning tweets for further analysis - creating term document matrix - making wordcloud, lettercloud, and barplots - sentiment analysis of apple tweets before and after quarterly earnings report R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 17070 Bharatendra Rai
R for Biologists: Your First Plot
 
18:10
Get the code and the data at marianattestad.com/blog How to make a nice plot quickly using ggplot in R. Quickly get awesome results from a large dataset of biological data. If you want to see more videos like this, you can go to http://marianattestad.com/blog/
Views: 7534 Maria Nattestad
Predictive Modelling Techniques | Data Science With R Tutorial
 
03:10:36
This lesson will teach you Predictive analytics and Predictive Modelling Techniques. Watch the New Upgraded Video: https://www.youtube.com/watch?v=DtOYBxi4AIE After completing this lesson you will be able to: 1. Understand regression analysis and types of regression models 2. Know and Build a simple linear regression model 3. Understand and develop a logical regression 4. Learn cluster analysis, types and methods to form clusters 5. Know more series and its components 6. Decompose seasonal time series 7. Understand different exponential smoothing methods 8. Know the advantages and disadvantages of exponential smoothing 9. Understand the concepts of white noise and correlogram 10. Apply different time series analysis like Box Jenkins, AR, MA, ARMA etc 11. Understand all the analysis techniques with case studies Regression Analysis: • Regression analysis mainly focuses on finding a relationship between a dependent variable and one or more independent variables. • It predicts the value of a dependent variable based on one or more independent variables • Coefficient explains the impact of changes in an independent variable on the dependent variable. • Widely used in prediction and forecasting Data Science with R Language Certification Training: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=Predictive-Analytics-0gf5iLTbiQM&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice. Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing. As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice. Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 211802 Simplilearn
Introduction to RStudio for data analysis
 
14:30
While R can be used for a huge range of statistical analysis and graphics, it has a very basic user interface. Hence, most R users prefer to use an alternative Integrated Development Environment (IDE) like RStudio or a programmer's editor. RStudio is free and open source and runs on all popular operating systems including Windows, OSX and linux. If you don't already use a programmer's editor then RStudio is an ideal choice because it is highly customised for using R. Even if you use another editor, you may find RStudio better since it may be more tailored to R. This video provides a brief introduction to RStudio including customising RStudio, reusing R syntax, working with multiple projects and producing basic HTML reports via the notebook option. An accompanying document may be found at https://sites.google.com/site/drpetebaker2/home/uq-related
Views: 10961 Peter Baker
Introduction to Bayesian data analysis - part 1: What is Bayes?
 
29:30
Try my new interactive online course "Fundamentals of Bayesian Data Analysis in R" over at DataCamp: https://www.datacamp.com/courses/fundamentals-of-bayesian-data-analysis-in-r ---- This is part one of a three part introduction to Bayesian data analysis. This first part aims to explain *what* Bayesian data analysis is. See here for part 2: https://youtu.be/mAUwjSo5TJE Here are links to the exercises mentioned in the video: R - https://goo.gl/cxfnYK (if this link does not work for you try http://rpubs.com/rasmusab/257829) Python - https://goo.gl/ceShN5 More Bayesian stuff can be found on my blog: http://sumsar.net. :)
Views: 84763 rasmusab
Gene Expression analysis using R
 
17:34
The video displays gene expression data analysis using R. The code is available at github https://github.com/abhik1368/dsdht/tree/master/Microarray%20Data%20Analysis The code is available at IntroMicroarray.R
Views: 27523 Abhik Seal
Frequency Polygons - Data Analysis with R
 
03:17
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 9246 Udacity
Why Use R? - R Tidyverse Reporting and Analytics for Excel Users
 
06:43
https://www.datastrategywithjonathan.com Free YouTube Playlist https://www.youtube.com/playlist?list=PL8ncIDIP_e6vQ0uQofezvKv3yPnL5Unxe From Excel To Big Data and Interactive Dashboard Visualizations in 5 Hours If you use Excel for any type of reporting or analytics then this course is for you. There are a lot of great courses teaching R for statistical analysis and data science that can sometimes make R seem a bit too advanced for every day use. Also since there are many different ways of using R that can often add to the confusion. The reality is that R can be used to make your every day reporting analytics that you do in Excel much faster and easier without requiring any complex statistical techniques while at the same time giving you a solid foundation to expand into those areas if you so wish. This course uses the Tidyverse standards for using R which provides a single, comprehensive and easy to understand method for using R without complicating things via multiple methods. It's designed to build upon the the skills you are already familiar with in Excel to shortcut your learning journey. If you're looking to learn Advanced Excel, Excel VBA or Databases then you need to check out this video series. In this videos series, I will show you how to use Microsoft Excel in different ways that will make you far more effective at working with data. I'm also going to expand your knowledge beyond Excel and show you tips, tricks, and tools from other top data analytics tools such as R Tidyverse, Python, Data Visualisation tools such as Tableau, Qlik View, Qlik Sense, Plotly, AWS Quick Sight and others. We'll start to touch on areas such as big data, machine learning, and cloud computing and see how you can develop your data skills to get involved in these exciting areas. Excel Formulas such as vlookup and sumifs are some of the top reasons for slow spreadsheets. Alternatives for vlookup include power query (Excel 2010 and Excel 2013) which has recently been renamed to Get and Transform in Excel 2016. Large and complex vlookup formulas can be also done very efficiently in R. Using the R Tidyverse libraries you can use the join functions to merge millions of records effortlessly. In comparison to Excel Vlookup, R Tidyverse Join can pull on multiple columns all at the same time. Microsoft Excel Power Query and R Tidyverse Joins are similar to the joins that you do in databases / SQL. The benefit that they have over relational databases such as Microsoft Access, Microsoft SQL Server, MySQL, etc is that they work in memory so they are actually much faster than a database. Also since they are part of an analytics tool instead of a database it is much faster and easier to build your analysis and queries all in the same tools. My very first R Tidyverse program was written to replace a Microsoft Access VBA solution which was becoming complicated and slow. Note that Microsoft Access is very limited in analytics functions and is missing things as simple as Median. Even though I had to learn R programming from scratch and completely re-write the Microsoft Access VBA solution it was so much easier and faster. It blew my mind how much easier R programming with R Tidyverse was than Microsoft Access VBA or Microsoft Excel VBA. If you have any VBA skills or are looking to learn VBA you should definitely checkout my videos on R Tidyverse. To understand why R Tidyverse is so much easier to work with than VBA. R Tidyverse is designed to work directly with your data. So If you want to add a calculated column that’s around one line of script. In Excel VBA, the VBA is used to control the DOM (Document Object Model). In Excel that means that you VBA controls things like cells and sheets. This means your VBA is designed to capture the steps that you would normally do manually in Microsoft Excel or Microsoft Access. VBA is not actually designed to work directly with your data. Note the most efficient path is to reduce the data pulled down from the database in the first place. This is referring to the amount of data you are pulling down from your data warehouse or data lake. It makes no sense to pull data from a data warehouse / data lake to pull into another database to query add joins / lookups to then pull it into Excel or other analysis tool. Often analyst build these intermediate databases because they either don’t have control of the data warehouse or they need to join additional information. All of these operations are done significantly faster in a tool such as R Tidyverse or Microsoft Excel Power Query.
Views: 12045 Jonathan Ng
Learning Data Analysis with R : Introducing the Raster Format | packtpub.com
 
05:07
This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2mIPNJq]. Raster data is fundamentally different from vector data, since its values refer to specific areas (cells) and no single locations. This video will clearly explain this difference and teach users how to import this data in R. • Explain what raster data is • Importing with rgdal • Introducing the raster package For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 2287 Packt Video
Microarray affymatrix data Analysis using R
 
09:16
Microarray affymatrix data Analysis using R studio.