**1: You don’t have to feel like a “maths person” to succeed**

The single most common feeling I hear from new statistics learners is “I’m just not a maths person.” Luckily, for statistics-as-a-scientist, you don’t have to be particularly mathematical. A large part of learning how to analyse and interpret data is getting to grips with the *language* of statistics (see tip #3). Like learning any new language, statistics takes time and practice, which is probably why there is a course on offer in your degree. However, telling yourself you won’t understand it because “you’re not a maths person” can put you in the grips of a self-fulfilling prophecy. Calculators and software packages will kindly take care of most of the mathematics for you. Focus on understanding the concepts (like grammar in a language), and remember that these new concepts take time and practice to grasp.

**2: OK, but in saying that, you do need to know at least a little maths**

Thankfully, it’s not about numbers, but concepts again. There are three crucial ideas for an initial statistics-for-science course you will need. First, is understanding the order of operations, also known as BEDMAS. This tells you that in any equation you do operations (calculations) in the order: Brackets, Exponentials, Division, Multiplication, Addition, Subtraction. Second, is the use of representative symbols within equations or Algebra. This gets used because, for example, you might need to use the mean of a data set to calculate a statistic. In the equation this is often symbolized by “M.” We use the symbol instead, because the actual value used varies by the individual data set. The final concept is how equations can get rearranged, because sometimes you need to rearrange things to calculate an answer. All this entails is doing the same thing on either side of the ‘equals sign’ in an equation, whenever you do something to it. So, if you need to multiply by 2 on one side, you have to do the same thing on the other. You will be amazed how far those three concepts can take you.

**3: There is a lot of new jargon and it can be confusing**

Saying statistics is a language is not something I do just to trick you into thinking it’s not maths. Means, Medians, Modes, Distributions, Z-scores, Deviations, Sums of Squared Errors. It all sounds like gobbledygook the first time you hear it. Learning the jargon, and what it means is half of the battle. Start a glossary for yourself: every time a new term is used, note it down, and put a definition with it. Revise your list regularly. Like, a lot. Learning the terminology consistently will help you understand what is happening as concepts and analyses build up greater complexity.

**4: Do any problem sets or assigned work regularly**

This might seem obvious at a university level, but if you’re a sufferer of point #1, you might avoid this type of work. But, you can’t start to address point #1 without __trying __to do the mathematical problems. Shift your focus from getting the answer 100% mathematically correct, to understanding what the statistical formula is calculating; the *concept* as opposed to the numbers.

**5: Use. Your. Tutors.**

This cannot be said enough times. So much so, it might have deserved a higher ranking. Go to your tutors. Ask them questions. Pester them even (not too intensely). Their entire job as statistics tutors is to help you understand the course and improve. They want to see you succeed and have also been right there in your shoes in the not too distant past. Having known and worked with many of them, they are also super smart and nice and will happily talk to you about pretty much anything. Mostly, they love to talk about data and stats, so talk to them about that.

**6: Don’t be shy about asking for repeated information**

While I recognize that some people may find this irritating, common feedback following lectures includes “Something went too fast,” “Something was unclear” or “New concept was hard to follow.” As the tutor/lecturer, I would rather cover something again and address what was missed or try to clarify it, opposed to having 90% of the class dazed and confused. We honestly don’t mind, so if this is what you need speak up!

**7: Team up**

Some people might take to learning statistics and data analysis like the proverbial duck to water, whereas for others it might take more effort. Additionally, some individual topics might come easier to you than others. Teaching other people and discussing concepts are great ways to learn. If you happen to be an ace at correlations, but can’t figure out the t-test to save yourself, find someone who’s in the opposite situation and share with each other how you understand the concept.

**8: Start reading results sections**

Seeing examples of how other people report and interpret their data is one of the keys to learning how to do the same with your own. Results sections can be a little dry, and many people avoid reading them thoroughly because of this. But, if you’re going to write your own someday, you need to look at models of how it’s done. Doing this also starts getting you comfortable with conventions that may exist within a particular area for what statistical tests or methods are used and how they are reported.

**9: Always read the instructions carefully**

This is generally good life advice but I’ve seen many a student fall into pitfall traps in statistics assessments by rushing in. Also, statistics lecturers and tutors seem to be a special group that relish “trick” questions. Go over what you’re expected to do, then go over it again and double check. If it’s for a written assessment, and you want to make sure you’re on track, see point #5. If it’s a test or exam situation and you’re not sure, come back to the question so that you can be.

**10: Keep Calm and Carry On**

Many scientific disciplines have compulsory statistics components, for good reasons already mentioned. Perhaps because of the pressure induced by the compulsory nature of these courses, statistics seems to bring with it a bucket of stress. Hopefully, some of the above tips will help with this. Also remember…

**~If you get stuck: ask**

**~If you get overwhelmed: take a break and do something else**

**~If you don’t quite get something the first time around: try again**

Finally, if you’re like me or other stats tutors I know, and you don’t do as well as you hoped or even fail a requirement the first time around AND you still really love your science and want to make a go of it: Do it. Try again. Compulsory courses are always available. Who knows, they might let you be the teacher one day.