Statistical Analysis Questions

[psychologystudent501]

Okay, this probably makes me sound fairly stupid, as most people find these questions super easy, but I never seem to answer them correctly! Is there some kind of technique I'm missing out on or something? For example, if we are given questions with graphs on, I can read from the graph but when it comes to stating suggestions or reasons why the data is what it is, I'm lost...

If anyone can help me out here, I'd appreciate it a lot as I really want to do well in Biology Thanks in advance!

NB: I do Higher, if that helps with any advice

Edit: Sorry if there are existing threads/ this is in the wrong place, didn't see anything!

Edited May 5, 2013 by psychologystudent501

[Hens48]

It's worth making sure you are familiar with the 'ecology' module of the syllabus, including the bits about the arctic ecosystems, greenhouse gases, effects of global warming/ climate change. Often those sorts of topics come up in the data analysis and having a good knowledge of them can really help. There was a good example in 2010 (I think) on arctic ecosystems which knowing the ecology part of the syllabus would have really helped.

[Sandwich]

The suggestions and reasons section is actually one of the easiest bits. Basically, read the blurb at the beginning really well. Figure out what they're talking about, what all the results mean and so on. If the experiment has three arms - one mouse which is knocked out for a gene (-/-), one mouse which is heterozygous (+/-) and one mouse which is homozygous (+/+) then you already know that the thing they're investigating is the gene.

After that it's just your biological knowledge which is being tested - and that's what you've learnt in the whole of the rest of the syllabus. Your knowledge should hopefully tell you what knock out means, what heterozygous and what homozygous mean. You already know what a gene is. The blurb may well give you more information as to what exactly the gene does, or you may be able to figure it out from the information (e.g. if the experimental data is showing how well each mouse metabolises X thing, you can probably guess that the gene is going to be encoding something involved in that metabolism such as an enzyme, receptor etc.) So you already know a lot.

Say that the gene does encode an enzyme - well you know ALL about enzymes from the syllabus. You know they may have optimum conditions of function, you know all about the lock-and-key stuff, you know about allosteric inhibition, you know tonnes of facts which will help you interpret what is going on. Equally if the gene encodes a hormone, you know all about what hormones do. If it's nothing to do with mice and genes but is about plants and photosynthesis, you know all about photosynthesis! So what if it's not an enzyme, hormone or whatever you've come across before - you know a lot of principles. And if it IS a hormone you know about, for instance insulin, then you know what that does, you know where it's produced, you know why it does what it does and what it responds to - all of which you can utilise to interpret the data. And so on.

So, say the gene encodes something unknown. In the knock-out mouse the enzyme goes crazy making substrate, in the heterozygous mouse the enzyme produces just an average amount of substrate and in the homozygous mouse the enzyme also produces an average amount. Just using knowledge you already have you can come up with loads of stuff. Why might this gene have such a powerful effect on the actions of this enzyme? Well, you know about enzyme inhibitors, so perhaps the gene encodes an inhibitor. You know about enhancers and repressers and so on in the process of gene transcription, so perhaps the gene is for a represser and without it you get loads and loads of enzyme being transcribed and made. Why is it about the same in the homozygous and the heterozygous mouse? Perhaps it's a dominant gene so it gets expressed regardless of whether you have two copies, and if you do have two copies then this doesn't change the amount of enzyme produced.

I'm going on a bit, but literally, the data section is just taking the Biology syllabus and challenging you to look at data, apply what you already know from the syllabus about similar or related topics and come up with some reasonable suggestions.

I hope that helps.