30.6.16

SERIOUS STUFFS: IBM SPSS - Serious teensie guide for the dazed, the lost and the suicidal. Part 1

First off...I'm not a trained statistician. BUT! I am a student. So yeah...there are a few things I can tell you about this statistical software other than the fact that it is ridiculously expensive and overrated. But hey....everybody's using it and unless you have better option (like for example R or Excel or SigmaPlot) that you're good at doing, stick to that. This is just a little post I would like to share to people who was in the same position as I was back 6 months ago; clueless and scared to death. It took me almost 3 weeks of seriousness to study up statistics basics before I even dare to press a button in SPSS. Why? Cause I am a freak who has to know what she is doing when she does things she doesn't know about. When people tell me not to make it complicated, I used to agree. But don't do that to yourself cause, if it doesn't feel right doing it, it's not even close to being half-right.

INTRODUCTION

IBM SPSS is a software utilized mainly by social science academicians, business statisticians and students like some of us to analyze collective data. What does it mean by analyzing data? I can simply say that it is to validate the significance of the data. As to whether its pattern fits or syncs with another set of variable or data. Then, you correlate the extent of the relationship and quantify it. And then...you conclude an equation for future probable prediction.

You know all the hype in the science journals about people validating their data with all that confusing p>0.01 or r=3.495? Well, these are all the values that represent the stand your data make in your research.

OK. Statistics is just a tool to objectify your data and explain it with legit validation of your research. The tests I'll be talking about may be foreign but all of them all talking about fitting your data into a bivariate relationship; a linear model.

A linear model is actually a bivariate plot of two continuous variable. So, basically, you're just going to connect 2 datas one-to-one.

General linear model or equation or relationship is the foundation of many statistical tests; t-test, ANOVA, ANCOVA and regression analysis and also multiple factor analysis. This requires alot of reading and processing and reading again, so I'm not going to go there. Science students or social science student have at a certain point in their basic degree years, learned statistics and probabilities. Here, we started learning those when we were 13 (correct me if I'm wrong). So, relax and understand that you got this.

You wanna start analyzing your data but you don't know where to start; how to arrange your data, what test to use, what does 'p' even means, what the hell is regression analysis etc.

WHAT TYPE OF DATA DO YOU HAVE?

Well, start identifying the type of data you have. Just segregate it into these 2 types; categorical or continuous.

Categorical data is just a data that states a setting apart without any scale or number. For example:

You're analyzing the effect of plants on a slope erosion. So, to do that, you decided to show how it is without plants, with one type of plant and with mixed types of plants. This is categorical variable. Each and every one of this different 'treatment' is data.

Continuous data is a data that consist of an interval, ratio or plain numbers that you obtain from equipments; 212.3 mg/L of oxygen.....2.1 psu....18% mercury....

Say you're taking soil samples from differently treated soil; fertilized, burnt and natural soil. And you analyze their pseudo-total nutrients (after digestion...etc), the readings that you get correlates with their origin and the circumstances of their existence before you sample them. So, just how much can this variation in nutrients be connected to their 'setting' or land management?

Well, with this data, you can use analysis of variance (ANOVA). It is used to compare the means of differing variables and establish as to whether they are, in fact, different and statistically significant. In another language, it means that, the means@average of the data is different enough to warrant an 'eureka'; yes, they are connected to each other and the data did not come out like that by pure chances.

ANOVA is a hypothesis test to compare the means of more than two population.  

From the case above, the data you obtained of the total nutrients from each of the place could be understood as total nutrients from 3 different populations. Hence, you're going to be comparing their means to see if they are significantly different from each other!

Is this how your data looks like?

If so, then power up that SPSS, and segregate your data into differing columns.



How you guys holding up? Still here?

So, here I have land-use, depth and the concentration of K. Since I am an environmental geologist, we look at soil analyze their content. LAND USE and DEPTH are my categorical variable. K CONCENTRATION is my continuous variable. Since I am trying to see the effects of land-use on my soil total K, I will be using ONE-WAY ANOVA. Why? Cause it's only one factor; land-use against total K. Land use is the factor that affects total K. Land-use is the independent variable and total K is the dependent variable.

Well...let's just go straight to the analysis. Go to the following instruction:


ANOVA doesn't tell you to what extent is the mean difference, they just tell you whether it is significant or not. So, that's where Post-Hoc test comes along. Here, I am using Tukey HSD as my post-hoc test. It's commonly used and easier for me to understand although some may prefer LSD. Here, if you notice, the test will be conducted to the significance level of 0.05...which is quite common. You can go for 0.01 too. I take both into consideration.

So far....for the people with basics in ANOVA but a novice at SPSS, is the instructions clear?

Feel free to ask if there are things you're not too sure about :3

Interpretation of the data will be shown in the next post which will be...soon-ish. Below, I have attached the links to some quick review of what ANOVA is in case you can't wait for the next post.

All the best to research students nationwide and I hope this post opened a sort of understanding on...ANOVA.

References & Recommendations:
Prof. Serna
Laerd Statistics


10.6.16

Friday Post: Walk or Jump?

Salam Ramadhan to fellow Muslims and happy fasting to all. Does the fasting wear you down or does it coincidentally increases your productivity? Do tell me! at the poll below.

For me, I had a wonderful head-start into this holy month with my family where we made list of the things we overlooked in doing over the course of the year; Quran reciting, solah sunnah and of course, our own health. Despite the ill-fortunate of beginning to fast with a flu, I'm good. And as to answer my own question, I am more productive. Cause fasting means no escaping to food when my brain hit a dead-end with something. So, it's good and I love it.

To walk or to jump at something you're not familiar with has always been an issue for me. That is mainly caused by my slow move when it comes to starting something. I have to meticulously plan it, set the mood, rate the weight before I even start. And think endlessly as I do this. When I think, it's always a slow-cooking process. So, half of the time, I try jumping into doing things just to get it started. But this never really turned out well for me, although it never stopped me from doing it. I have this idea that when I jump into something and start doing it wherever I want to, it'll turn out OK. But really, it only makes me understand that, you can't do something you have no idea about and blindly pass up your work with discussions, interpretation and conclusions that you know, barely scratch the surface.

I have been hung up with my data analysis for the longest time. I've been going around asking people how to do it, even going as far as bugging my bestfriend in Japan to tell me what to do with a bunch of data I have. Eventhough I know what I want, I don't know how to get it. Statistical analysis isn't really a thing I understand or do on a daily basis. If you talk about music, now that's my language. But not statistics. For the longest time, I tried doing and failing and tried to do things according to my friend's instruction. I got the products of the analysis but I wasn't satisfied. Then, my colleagues started telling me that I'm being complicated. Was I? I didn't know and I still don't. Was my way of thinking too complicated and winded? I didn't think so. I thought it was only natural to ask what I want and to understand something so I am comfortable with discussing it.

After trying to find websites after websites and books after books to make me understand all those t-test, z-scores, simple linear regression, correlation coefficient, hypothesis testing and ANOVA, I realized that...it was close to futile. And I wanted to cry. But yesterday, I got fed up and went to YouTube looking for anybody that does what I did. I found one...although he is not a chemist. In fact, he is a Mathematics/Physics/Statistics former lecturer turned tutor; Prof. Serna. He was God-sent.

For every single thing that I haven't the faintest idea about, I got the free tutoring over the easy to understand step by step videos. And it didn't take long.

OK.

I am not here to promote any YouTubers or tutors and raise free ads at my corner here, but the point here is his teaching methods.

Step-by-step.

My impatience to learn something new has eaten me right from the beginning. The impatience to understand, the impatience in thinking and letting things sink it...it's deteriorating. The constant want to have things fast and right at the second you demand it is wrong and it is awfully shallow of me to demand such thing of my brain. I think this is was I read before in a book and I think it is called confidence bias. And it was born out of the sheer marketing of over-optimism by self-made public figures that said;

" If you want it...you can get it...If you demand it, you'll have it...Getting things done fast is how you move forward....bla bla bla,"

They didn't exactly say that but that is pretty much the idea.

Is that true?

Is there such thing as multi-tasking, really?

I mean, we've read books on why guys like bit*hes....and why man won't ask and woman can't read maps...but I think, being bossy to your own brain is quite pushing it.

I guess, what people forget is that, our brains work differently. Where most of these successful people got it right and with sheer confidence that their success came from their hard work, it is still a method personalized to their brain, body, spiritual, social and economical capacity.

Although I don't believe in always being suspicious and pessimistic about things, it is always wise for us to have constant reality checks before we jump into anything that seemed outrageous impossible but actually happened to someone. Like sheer genius in maths where he did calculus at the age of 3 or music prodigy practically cutting it with Rachmaninoff...they just have the fortune, capacity and time at it that most of us hasn't.

So start with the basics at your pace. Our brains work differently.

And I never said stop dreaming. You may reach the stars with your dreams. And it's not wrong to feel bad and defeated at times. There is no such thing as things being at the worst before it gets better. Constantly balance your optimism with reality-checks. It's not wrong to have certain doubts. It's not wrong to let an idea hang to dry and be probed all the time.

Now...let's fall in love with this beautiful piece composed by Chopin; Spring Waltz.