data analysis Archives - DexLab Analytics | Big Data Hadoop SAS R Analytics Predictive Modeling & Excel VBA

## Let us Revise Regression Analysis

By now every business owner and manager is aware of the latest megatrend related to data analysis and knows that they should make data-driven decisions only at work. Gut feeling and winging it are now practices outdates as they have proved time and again that they fail. But the problem still remains in the know-how of parsing through all the layers of data streaming into your systems. Do you have the requisite know how?

Luckily for you, you may not be the one to crunch all the numbers (phew!). You pay other robotic data analytics personnel to do that for you. But you must correctly understand the analysis report that is handed over to you for interpretation after your colleagues are done with all the heavy lifting. A common practice is the realm of data analysis is regression analysis. Continue reading “Let us Revise Regression Analysis”

## Are You a Student of Statistics? – You must know these 3 things

We a premiere statistical and data analysis training institute offering courses on Big Data Hadoop, Business intelligence and Ai. We asked our faculty to tell us the three most important things that every student of elementary statistics should know.

#### So, let us get on with it:

1. The notion that statistics is about numbers, is in the context only: statistics involves a rich treasure trove of numeric and graphical representation of displaying data to quantify them also it is very important to be capable of generating graphs along with numbers. But that is not the half part of statistics and the main interesting aspect is related to making the big leap from numbers and graphs to the realistic worldly interpretations. Uncannily statistics also poses to be a fascinating philosophical tension raising the question and healthy skepticism about we believe in and what we do not.
2. The analysis part is not the most crucial part of a statistical study, the most important part lies with the when, where and how of gathering the data. We must not forget when we enter each number or data, calculate and plot the strategies we build on our understanding, but many a times at the time of interpretation that each every graph, data or number is a product of a fallible machine, be it organic or mechanical. If we are able to take proper care at the stage of sampling and observation we will be able to obtain great dividends at the final stage of interpretation and analysis of all our statistical efforts.
3. All statistical functions off all kinds of mathematical sciences are based on a two-way communication system. This communication system should be between the statistician and non-statistician end. The main aim of statistical analysis is to put forward important social, public and scientific questions. A good statistician knows how to communicate with the public especially with those who are by and large not statisticians. Also the public here plays an important role and must possess simple idea of statistical conclusions to grasp what the statisticians have to say to them. This is an important criterion to be incorporated in the K-12 and college curriculum for elementary statistical students.

If you agree with our views and would like to discuss further on statistics and its application on data analysis then feel free drop by DexLab Analytics and stay updated on the latest trends in data management and mining.

## Data analysis resources to keep you updated

One should always be proactive about building upon what they already know and have learnt, and with explosion of the web such resources can be obtained fairly easily. The problem is not the availability of resources but the abundance from it. Due to the availability of too many choices it often becomes difficult to gauge if the sources are actually authentic.

#### To stay on top of the latest trends and analyses reports and what’s new in the realm of analytics here are the best latest blogs:

• FiveThirtyEight: the main man behind this blog is Nate Silver, a data whiz kid, this blog is the place to find out data analysis and visualizations of political, economic and cultural issues. The content in his blogs are usually light-hearted and interactive yet pointed with illustrative examples of data can be used in day-to-day activities.
• Flowing Data: this is an interesting blog where Dr. Nathan Yau, PhD reveals how the data personnel – like designers, analysts, scientists and statisticians can analyze and visualize data to gather a better understanding of the world around us. It is especially fun to read as Yau offers a funny approach about the regular challenges faced by a data professional in this field. One can also find job recommendations, tutorials and other resources in this blog.
• Simply statistics: this is another blog that is managed by expert professors each from Ivy League colleges like Johns Hopkins University, Harvard University and the Dana Ferber Cancer Institute. These professors also talk about how data is being used or misused around the world in different industries.
• Hunch: this blog has been created by John Langford from Microsoft Research, he is the doctor of learning there and his blog talks about machine learning basics of what we know and how we use what we know. This is a good read for those who are new in the field of machine learning and do not yet know how things work in machine learning as it provides an in-depth view of new ideas and events going on in this industry.

To connect to other fellow data scientists and analysts to inquire about questions that may arise while you try the tread the treacherous roads of the data world, these are few communities of data analysts you can follow.

1. Kaggle competitions: this is a popular community that all data scientists are likely to come across. This is a platform where one can find data prediction competitors. This is a platform where one can search for upcoming competitions in data analysis the website also features a forum where a visitor can ask any question or find a partner for the competition, share resources and ask for support to make a good career in data science.
2. Metaoptimize: this is a question and answer community for people who are into machine learning, natural language processing, data mining and more. Badges are awarded as per votes on questions are awarded. Thus, making it becomes simpler for the visitors to discover the most popular helpful answers to the questions.
3. Datatau: this website is best described as hacker news for data scientists and it lives up to this description to the last word. People share career advice with each other; interesting articles are shared amongst the users and then commented upon also the people here share useful information to those new to the world of data analytics.
4. DexLab Analytics blogs: while DexLab Analytics is one of the leading data analytics training institute in Gurgaon, but they maintain regular blogs about the latest developments in the field of data science and provide India-specific as well global data related news. For students pursuing or aspiring to pursue a career in data science must follow the daily posts from this institute.

In conclusion we would like to add that while there are several resources from where one can obtain valuable information about data analysis. Thus, keeping this list as a starting point you can find several other experts out there to help you learn more about data analytics.