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It's like this thread is meant for me, I'm a statistics student currently in 200 level, but I love analysis, as I already have an idea of what statistics entails during my national diploma, which I used for direct entry, but there was a time I thought to become a better statistician one has to be a computer scientist and I've been nursing the idea of crossing to comp. Sci. nd repeating my 200level, but this thread seems to give me the reason to be a statistician, and all I need is the knownlege of important statistical pakages. So help me God.

please I dnt mind if someone is willing to help a data analyst in the embryo, coz I need real problems to prepare me for the challenging future, I'll take anything you think could help my career. I am risiding in Ibadan and schoolling @ the university of Ibadan.
God bless my Mentors.

I have used SAS in the past and Excel is always handy. Recently, i discovered Minitab and it is really helpful. To gather data in vast amount, i use KAPOW and of course it doesn't end there.

When i fisrt got the role of a analyst, i felt all i needed was data analysis and report writing skills. Turned out i also had to learn advanced Microsoft Access to structure my data before using SAS, Minitab, and Excel. These days, my advice to analysts is "you should learn everything from data mining, database structuring and administration, plus data analysis with the help of modern tools & software". Lastly, remember that the business of transforming raw data into reliable information & insight ultimately requires common sense too.

I'd be back to read more from other contributors. At least today we aren't bashing Igbo, Yoruba, and Hausa here but if anybody cares to start, i am fully ready and charged up as usual.


Sir, Please how can one learn these tools, in my current employment, i dont use these but would like to learn,m what do u suggest ?

the_cia: [b]I have used SAS in the past and Excel is always handy. Recently, i discovered Minitab and it is really helpful.

I also found Minitab very good and suitable for OLS Regression and Time series modeling. I love stats computing!

just to add some info to this thread, for those who want to learn more about data analysis you can visit Coursera.org . Go to courses and enrol for any course you think will shed more light on the topic for you.

Am happy for this thread but pls i wnt to master all this package especially minitab,spss,excel and r packaged am a statistician. God bless us.

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Great Statisticians, let's keep this thread alive!

How could all of you be talking about data and statistics without mentioning Machine Learning and Hadoop, web mining and text mining etc.There's a machine learning class going on at www.coursera.com. With machine learning, you could train your computer to recognize complex patterns in data and automate all your data management tasks with several algorithms that have now made a normal statistician's job obsolete.Machine learning can be described as AI(Artificial Intelligence) in the field of statistics.

If you are a statistician and shying away from machine learning because of linear algebra, calculus, programming and other complex numerical methods, then you are not doing yourself any good. I am a EE graduate who learnt statistics on the fly through machine learning. I don't have to learn how to derive all the statistical formulae. I just look at the data, apply my favorite ML algorithm and instantly start classifying and predicting things within minutes.The bigger the data, the more accurate my predictions are.

Data nowadays is becoming huge day by day, and using the now obsolete statistical methods to analyze your data is simply not going to cut.Here enters Hadoop,the big data open source analytic tool built with Java.It employs a technology first invented by Google called MapReduce.If you really want to become a Data Scientist or analyst, then you should definitely check out Hadoop -Data Analyst are being replaced by Data Scientist(or could they co-exist ?)

This is 2013 guys,My wish is for all of us to quit practicing with "left overs" kind of education where we are dealing with disused things and start thinking about the future of Data analysis and Data Science in Nigeria. The developed worlds are talking about Weka, Apache Mahout, Python, R,Machine Learning , Deep learning, Neural Networks, Hadoop, Bayesian Reasoning etc.Why should we be any different..

With your skills as a statistician, you won't find it difficult applying your expertise in the fields mentioned above. That said, I have a Statistics book(Schaum's series) that I am skimming through now, It uses softwares like MINITAB, SPSS, EXCEl and SAS to analyze data with a lot of examples and exercises. I can't help but to laugh at the most primitive way to do data analysis.However,no knowlegde is a waste, so it's not a waste of time either, rather I am combining the theory gleaned from the book with practical skills gained from taking machine learning course at coursera.

Lastly,your computers have been empty, idle and slow for a while - I mean by using Microsoft technologies you are apparently limiting yourself to a lot of opportunities. Let's Behind it up by first installing Linux(ubuntu is open source and free).Around 80% of the world's web servers run on linux. It is fast, secure and reliable.You can run ubuntu OS and windows7 side by side as the linux kernel is not memory greedy.You can boot from windows or linux anytime with all your files in both Operating systems intact.Also, booting time for linux is less than 10s.

And @nairaland owner,I want to suggest that you try and update your site by adding a voting scheme where users can upvote good answers and downvote irrelevant ones. You have alot of work to do, your site has come a long way.Is it because there's no competition yet?Wait until this nerds living in the future usurp your site and make it obsolete.Hope you don't want to see that happen ?

Thanks for listening....

Njord.....turning data into knowledge

Interesting thread. Kudos to all d contributors.
Funny enof, I don't think I came across any female here.

Well, here I am... Started wrking with spss few months ago. Its quite interestin cos I am self taught. And I'm earning a good part-time pay.
Tho I'v only wrked for about 5 pple.

I won't mind student referrals n researchers as well... Work to keep busy wit (cos I don't intend to pursue a career in it) till I get a full time job.

Njord: How could all of you be talking about data and statistics without mentioning Machine Learning and Hadoop, web mining and text mining etc.There's a machine learning class going on at www.coursera.com. With machine learning, you could train your computer to recognize complex patterns in data and automate all your data management tasks with several algorithms that have now made a normal statistician's job obsolete.Machine learning can be described as AI(Artificial Intelligence) in the field of statistics.

If you are a statistician and shying away from machine learning because of linear algebra, calculus, programming and other complex numerical methods, then you are not doing yourself any good. I am a EE graduate who learnt statistics on the fly through machine learning. I don't have to learn how to derive all the statistical formulae. I just look at the data, apply my favorite ML algorithm and instantly start classifying and predicting things within minutes.The bigger the data, the more accurate my predictions are.

Data nowadays is becoming huge day by day, and using the now obsolete statistical methods to analyze your data is simply not going to cut.Here enters Hadoop,the big data open source analytic tool built with Java.It employs a technology first invented by Google called MapReduce.If you really want to become a Data Scientist or analyst, then you should definitely check out Hadoop -Data Analyst are being replaced by Data Scientist(or could they co-exist ?)

This is 2013 guys,My wish is for all of us to quit practicing with "left overs" kind of education where we are dealing with disused things and start thinking about the future of Data analysis and Data Science in Nigeria. The developed worlds are talking about Weka, Apache Mahout, Python, R,Machine Learning , Deep learning, Neural Networks, Hadoop, Bayesian Reasoning etc.Why should we be any different..

With your skills as a statistician, you won't find it difficult applying your expertise in the fields mentioned above. That said, I have a Statistics book(Schaum's series) that I am skimming through now, It uses softwares like MINITAB, SPSS, EXCEl and SAS to analyze data with a lot of examples and exercises. I can't help but to laugh at the most primitive way to do data analysis.However,no knowlegde is a waste, so it's not a waste of time either, rather I am combining the theory gleaned from the book with practical skills gained from taking machine learning course at coursera.

Lastly,your computers have been empty, idle and slow for a while - I mean by using Microsoft technologies you are apparently limiting yourself to a lot of opportunities. Let's Behind it up by first installing Linux(ubuntu is open source and free).Around 80% of the world's web servers run on linux. It is fast, secure and reliable.You can run ubuntu OS and windows7 side by side as the linux kernel is not memory greedy.You can boot from windows or linux anytime with all your files in both Operating systems intact.Also, booting time for linux is less than 10s.

And @nairaland owner,I want to suggest that you try and update your site by adding a voting scheme where users can upvote good answers and downvote irrelevant ones. You have alot of work to do, your site has come a long way.Is it because there's no competition yet?Wait until this nerds living in the future usurp your site and make it obsolete.Hope you don't want to see that happen ?

Thanks for listening....

Njord.....turning data into knowledge

Hi,

Machine learning is beyond the scope of this thread, but thanks for bringing onto the minds of forum members..A friend wants to do research in AI at Alberta. This was how I got interested in the field, myself.

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Coming Soon: POSTGRADUATE ANALYTICS FOCUS GROUP
Complex data underpins current research, while innovative analysis can prompt new discoveries. Excellent research can often be stalled due to a lack of expertise in conducting data analysis. The Postgraduate Analytics Focus Group is a Dataville Solutions initiative founded to support academic researchers, postgraduate scholars and professionals in various public and private institutions, industry, government agencies, NGOs and international organizations on the use of analytical tools and methods for research and policy and strategic decision making purposes.

dataville: Coming Soon: POSTGRADUATE ANALYTICS FOCUS GROUP
Complex data underpins current research, while innovative analysis can prompt new discoveries. Excellent research can often be stalled due to a lack of expertise in conducting data analysis. The Postgraduate Analytics Focus Group is a Dataville Solutions initiative founded to support academic researchers, postgraduate scholars and professionals in various public and private institutions, industry, government agencies, NGOs and international organizations on the use of analytical tools and methods for research and policy and strategic decision making purposes.

When is this comingf up? Specific time cos I'm intrested.

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We will PM you as soon as the link is up.

obasy09:

When is this comingf up? Specific time cos I'm intrested.

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Wow!!!......am happy dat thr is a thread like dis......but am scared cos al here are experts, either graduates or undergraduates.....
I am a new statistics student in a poly in dis country....though we r yet to start lectures.....
I wil love to knw the books dat I should get to get myself prepared befor resumin....nd as I heard pple wit thr say dat statistics is a very tough course.....bah I fink u pple here wil be of help to me........
Kudos to u all.........

Dcoolest: Wow!!!......am happy dat thr is a thread like dis......but am scared cos al here are experts, either graduates or undergraduates.....
I am a new statistics student in a poly in dis country....though we r yet to start lectures.....
I wil love to knw the books dat I should get to get myself prepared befor resumin....nd as I heard pple wit thr say dat statistics is a very tough course.....bah I fink u pple here wil be of help to me........
Kudos to u all.........

Not really tough, but interesting. Just be focused.

How to Learn SAS Online



How to Learn SAS Online
SAS is a statistical analysis software package developed by SAS Institute. It is used for data entry, data mining, statistical analysis, quality improvement, business planning, forecasting, and decision making. SAS is marketed toward programmers and relies heavily on a text-driven interface. Current versions of SAS are available for Microsoft Windows, IBM mainframes, Unix/Linux, and OpenVMS. Older versions supported PC-DOS, Apple Macintosh, VMS, and OS/2 systems.


If you do not already have a copy, download a copy of SAS Learning Edition 4.1. SAS Learning Edition is a less expensive version of SAS designed specifically for single users for educational purposes.

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Njord: How could all of you be talking about data and statistics without mentioning Machine Learning and Hadoop, web mining and text mining etc.There's a machine learning class going on at www.coursera.com. With machine learning, you could train your computer to recognize complex patterns in data and automate all your data management tasks with several algorithms that have now made a normal statistician's job obsolete.Machine learning can be described as AI(Artificial Intelligence) in the field of statistics.

Njord.....turning data into knowledge

You ca start a thread on Machine Learning.
I have used (and still using) ML and the possibilities are endless especially in these days of big data. I agree with you that and aspiring data analyst should step up his game, but na step by step nah.
I also completed Prof Ng's class on ML sometime in Feb 2013 although prior to that time, I already had about 2 years experience applying ML techniques. Whilst studying, I basically used Matlab for my analysis but now I've added R to my list. Also using Hadoop at the moment but won't say I'm an expert at that yet.

The key with ML is getting the right amount of reliable data. Once you can get this stage right, there are loads of models out there that aid with analysing the data.

haveworkskills:

Hi,

Machine learning is beyond the scope of this thread, but thanks for bringing onto the minds of forum members..A friend wants to do research in AI at Alberta. This was how I got interested in the field, myself.

Interested in analyzing financial, economic and business data for investment banks, private equity, commercial banks and bond dealers? Click the attached document!

If machine learning, NoSQL databases and Hadoop is beyond the scope of this thread, I will suggest we rename the topic to something else...This is because Data Analysis has gone beyond SPSS and Statistical modelling these days due to the volume of data being generated from an ever increasing list of channels.

Additionally, it is the introduction of these new modelling techniques coupled with complementary frameworks (like Hadoop) and the emergence of NoSQL (and graph based) databases that is actually behind the surge of interest in Data Analytics. We also have supporting technologies like grid and cloud computing (we can now use commoditized processing storage and power).

It is when you bring in Hadoop and NoSQL/Graph based databases plus text and web data mining that you can start talking about BigData. That is when an average developer will become interested (because of the possibility of writing MapReduce batch jobs or replacing my Oracle with Cassandra/CouchDB and store ANYTHING).

That is when retailers, telcos will start looking at real time customer behaviour analytics, that is when a company will see the necessity to set up a Data Science team in-house. Statistical modelling is still valid, just like any other relevant approach but I think we should emphasize what people might want to learn in the process of preparing for the future because as I can see it, the approach to storage, processing and analysis of data is changing... Let's get ready for the BigData revolution.

i use SPSS, Eviews and minitab. But d 1st is splendid

Q1:2014 Regional Hands-on Workshop

Location: Abuja and Lagos

Analytical tools: IBM SPSS and EViews

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