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How to get into the world of statistical analysis

I've received a number of questions on this in the past and felt that those who are interested should be able to know what is needed to become a statistician. There's a few criteria you need to be made aware of before you consider jumping into this career:
  1. Are you good with numbers? If not, it's not a big deal, but if numbers scare you in general, you might want to walk away from this. Statistics is both an art and science, but there's a lot of math involved that is required in order to understand the print outs. If you hated stats or math, again, this probably isn't for you.
  2. Do you enjoy coding/programming or would like to get into coding/programming? If so, statistical analysis does require knowledge of data manipulation and running different types of analysis. Most often you'll manipulate data in a database program then import that data into a statistical packaged program.
  3. Can you see the bigger picture of data? More often than not, statisticians have to come to some form of conclusion as to what the data is saying beyond trends. Is price of gas really impacting the price of bread or is it some kind of spurious correlation? That's the type of question you'll be asked and need to answer.

What are the programs that statisticians use?
That depends but there are a number of programs that are commonly used but each one has it's own drawbacks/issues. I'll list each below.
SPSS: This is a decent statistical program that has a similar feel to HTML but the programming is very easy to understand. However, good luck manipulating data in this program as it will often lock up and lag out if you're not using a fast enough computer. Training in this program is both online and offline and you can find free courses for it. This is probably the most basic of the programs to use and one of the cheaper ones.
SAS: This statistical program is by far the most expensive but the easiest to use and understand. The coding is very similar to C++ and much of the logic is the same. You could probably paste in C++ code into this program and it should work the same way. I've used this program the most and there's a great book that gives you a very simple break down of all of the functions of SAS called The Little SAS Book by Lora D. Delwiche and Susan J. Slaughter. Training in SAS isn't cheap and to acquire the program isn't cheap either. Expect to pay at least $100k per license.
R: There's a lot of people in the community that love R because of how much it can do, the fact it doesn't require nearly the amount of computer resources to run and data manipulation is relatively easy. The program isn't easy to learn though so unless you've got programming in your background or currently do stats, you'll have some difficulty learning it. The R Project has a lot of resources including free online training and you can download the program for a small donation to the company.
Excel: Excel does have statistical analysis capabilities, but it's often limited based upon how many cells there are (up to 3 million now) and data manipulation can be daunting the bigger the database you're using. It's best to use Excel for calculations after you run your models.
Others: There's a lot more out there. STATA, EViews, JMP, Minitab, Systat, etc. A lot of these programs are good in their own right, but I listed the three most commonly used programs that you'll run into.

But wait, there's more! Here's the database manipulation programs that you should become familiar with.
Access: Access is good for bringing in new data, maintaining access to the data, and doing some data manipulation. However, it's not nearly as intuitive to use and it does have some data limitations as the files can become large very quickly and you can easily mess up the files if you're not careful. You can find training for it, but you'll probably wind up paying out the nose for it as Microsoft will want their cut.
SQL: SQL or Sequel is great for database management, inputting new data and running basic analysis on data. The applications behind it are numerous and you can use it to examine billions upon billions of lines of data. Training is free through MySQL or you can pay Microsoft to learn SQL Server. Chances are if you work for a large corporation, they're using SQL server where as smaller companies will use MySQL. Both use the same programming language, it's just a difference of features. I highly recommend learning SQL.
Tableau: Tableau is a cool interactive tool if you want to show your data in interesting and creative ways. It also features a dashboard aspect where data can be posted online for others to view and manipulate. While it can be clunky to get in the data and make sure it's in correctly, it's a great visualization tool that many companies are starting to use.
Excel: Excel is widely available but it has severe limitations on database manipulation. Its good for small databases, but best for use of calculations and data validation.

Should you be certified in any of these programs?
It doesn't hurt, but at the same time, it isn't something required by most companies. Because there's just so many programs out there, you'd become overwhelmed with all of the programs. Stick to the top three, become familiar and maybe attend a training course or two on it. But save your money and skip the certification.
If you're wanting to go into high level research analysis, usually it requires an advanced degree of some sort, usually in economics, psychology, statistics, or mathematics where statistical analysis goes into theory.

What kind of jobs can you get with this?
Numerous companies across multiple industries use statistical analysis. Everyone from GE, Amazon, Exxon/Mobile, Citibank, Bank of America, Amerprise, Goldman Sachs, USAA, etc. use some form of statistical analysis. The jobs you're looking for: Statistician, Secondary Researcher, Marketing Research, Actuary, etc. Anything with statistician, research, or analysis will be your primary targets. Listing your skills in linkedin and indeed will net you looks and having some kind of experience will open up conversations.

What to watch out for when applying for these companies?
There's a number of companies that prey on newbies/recent graduates. Be ware of the type of people you're interviewing with. If you're walking into an interview where everyone is wearing casual and they're all in their twenties, chances are you're going to be working late nights/weekends and won't be paid the money you should be earning. However, while those jobs will suck, you'll land a job quickly anywhere after that making a decent salary. Turnovers for those places are high (usually within 1-2 years). Just be ware that there's a lot of companies that will do that to you.

If you have any questions, feel free to PM. I probably missed some things but I welcome the criticism and will change this post based on that feedback.
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