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From FrozenToothpaste.com
From my point of view, something bugs me. This video cries out “WE ARE IN CRISIS!”, it reminds me this quote from Michael Chricton:
Arda
Since this Blog is about stuff as the title shows( btw I really should consider major changes in this blog. Come on what’s a blog about stuff, how cheesy is thatJ ) , it’s time to dedicate this post to “stuff” itself. Or, maybe to its story.
“The Story about Stuff” is a documentary about the production-consumption and disposal process of every item that we use in our lives. The narrator Annie Leonard, a former Greenpeace employee with a envorinanmental studies degree, is the one who introduces us this story about what goes wrong in our production-consumption cycle and how we can improve it.
Link to: The Story of Stuff
The 20-minute documentary is definetly worth of watching( Animations rule!). Video looks nice persuasive but I wonder if that story is actually the right one?
Actually, there are many critiques to the Story, a quick research in Google and I found interesting results
First, start with the good news. The new school of thinking that Leonard suggest, are mostly accepted without any hesitations. In other words, there’s nothing wrong with “Green Chemistry, Zero Waste, Closed Loop Production, Renewable Energy, Local living Economies”.
Whereas the arguments of Leonard seem to attract more opposite views. For example:
From FrozenToothpaste.com
“Not everything about manufacturing is “toxic.” Make no mistake, I think there are plenty of dangerous chemicals in the things we produce, but you’re playing fast-and-loose with reality if you’re going to say that manufacturing is the simple practice of putting toxic chemicals onto stuff to produce toxic products.”
From Andybrain.com
“ Annie Leonard raised the freak-out level: We dip our pillows in BFR (brominated flame retardants), a horribly toxic man-made chemical, and we sleep on them!
Not knowing anything about BFRs, I did some research on this. I found two things:
One, BFRs are used primarily in electronics and electronics plastics. Things like computer circuit boards, the plastic casing around a TV set, around the rubber sheaths encasing wires in a computer, that kind of thing. And the BFRs are chemically bonded to those components. That means they’re not flying into the air, we’re not breathing them in.
Two, I was unable to find any evidence of companies dipping pillows or pillowcases in BFRs before selling them.”There is even an Alternate Story of Stuff video series. It critiques Story of Stuff, on Youtube.
From my point of view, something bugs me. This video cries out “WE ARE IN CRISIS!”, it reminds me this quote from Michael Chricton:
“The media did not make extensive usage of terms such as crisis, cataclysm,plague or disaster. For example during 1980’s, the word crisis appeared in news reports about as often as the word budget. In addition prior to 1989, adjectives such as dire, unprecedented, dreaded were not common in television reports or newspaper headlines. But then it all changed.
These terms started to become more and more common. The word catastrophe was used five times more often in 1995 than 1985. Its use doubled again by the year 2000. And the stories changed too. There was a heightened emphasis on fear, worry, danger, uncertainty, panic. “
Long word short, media sells catastrophe news and people buy it. That’s the thing that annoys me, I really can’t decide now. Does Anne Leonard really tells us the truth or sells some part of it?
I think the main problem about the Story of Stuff video is that, it lacks detail and explanation. I know, it's a full 20 minutes, but she needed to explain her points more. I guess she tought so, too. As of March 2010 the book of Story about Stuff is available. I hope this time we may really understand the story about stuff.
Arda
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Test the Signifance of Regression : It’s a basic F test. You do test to check whether regression analysis is really helping you explain a significant amount of variance on the response variable.
Diagnostics and Remedial Measures based on Selected Predictor variables
Validation of the Model : You initally save some of the observations and not include them in regression. Let’s say with 400 observations you calculated an apropriate regression line and for 100 samples you look at how does your regression line fits.
Well, you can use many statistical softwares for regression but I guess SPSS and Minitab are the most popular ones. I first started with SPSS thinking that it’s much more popular software and knowledge of Spss would be a plus because its widely used. At the beginning it looks simple, it is indeed but for some simple tasks Spss is just a waste of time.
I hope this blog post helps you in your analysis.
Posted on 4:36 PM by 4 8 15 16 23 42 and filed under
industrial engineering
Again last semester, for my Statistical Inference Course I was supposed to perform Multiple Regression Analysis on a dataset. In this post, I will share my notes on finding the data and steps of the study and about software selection.
1. Finding the Data:
At the beginning I thought it’s a great oppurtunity to investigate Global Warming. In regression analysis, you try to explain one variable as the function of others and make inferences. So you have several variables namely predictor variables( the ones you use in prediction of the response variable) and one response variable( the one you are interested in).
Coming back to Global Warming example, my initial idea was trying to predict temperature by using C02 level, deforrestation level etc. Why didn’t I do it? Maybe “searching for hours for these data and not finding as I wanted” is the reason.
The challenging part in finding data was that for each different data the sources are different. You have to find different official data from different sources since they are not published together in most of the cases. I could find Temperature Data but I was close to finding CO2 but 2 more problems:
1. There is need to organize the data / Time- Consuming + Time- Consuming+ Time- Consuming
2. I needed more predictor variables (10 would be enough but I had only 2) since in the analysis you decide on whether to keep or omit some variables.
So I gave up my idea on global warming which as a subject looked pretty interesting but finding data and organizing them seemed challenging thinking of the above problems. So what I did? Found a sample dataset.
Coming up with a data yourself, and organizing is not really the purpose of regression analysis. In most of the cases, you are supposed to apply regression techniques on a dataset, no matter what your dataset is. Apparently there are statistics websites presenting datasets for statistical purposes. The great part about that is they present you many sets and you can choose among them which one you are interested in.
http://lib.stat.cmu.edu/ is an example statistical website. (The one I found mydataset) The datasets presented here, are not made up to give nice results, instead they are taken from studies or research papers some time ago.
http://bus.utk.edu/Stat/DataMining/files.htm : This site also gives dataset which you may use for regression. I got the impression that Senic dataset is a very famous one and could be used without hesitation.
You may look at these websites also:
2. Steps of Multiple Linear Regression Analysis
Test the Signifance of Regression : It’s a basic F test. You do test to check whether regression analysis is really helping you explain a significant amount of variance on the response variable.
Diagnostics and Remedial Measures based on all predictor variables : Initially start with the full model where you put all your data. By looking at residual plots you decide whether assumptions below are violated or not, and if they are by transformations you try to correct them.
· Multicolinearity Between Predictor Variables
· Linearity of Error Terms
· Constant Variance of Error Terms
· Independence of Residuals
· Normality of Residuals
Selection of Significant Predictor Variables: After you made sure that full model satisfies all the regression assumtions, in a whole set of available variables you take the ones which helps you analyze a significant amount of variance on Y(response variable). You can either use Stepwise, Forward Selection or Backward Elimination in deciding which variables to include in your model.
Diagnostics and Remedial Measures based on Selected Predictor variables
· Linearity of Error Terms
· Removing Outliers
· Constant Variance of Error Terms
· Normality of Error Terms
Validation of the Model : You initally save some of the observations and not include them in regression. Let’s say with 400 observations you calculated an apropriate regression line and for 100 samples you look at how does your regression line fits.
3. Which Software to Use:
Well, you can use many statistical softwares for regression but I guess SPSS and Minitab are the most popular ones. I first started with SPSS thinking that it’s much more popular software and knowledge of Spss would be a plus because its widely used. At the beginning it looks simple, it is indeed but for some simple tasks Spss is just a waste of time.
For example you want to plot all the residual plots and copy them to Ms Word, Excel etc. , in Spss you have to copy manually each graph manually and it takes time. Editing Graphs,or plotting mutliple graphs in Spss is not easy either.
So I looked to Minitab and Result: Minitab Rules! You can plot variables against each other very easily and save them all in .jpg files. Plus it seems to me that in Minitab you have more options in regression, so I would definitely suggest you to use Minitab. Also, trial version of Minitab is available for 30 days( Way enough for regression projectJ ).
I hope this blog post helps you in your analysis.
End of Course-Related Blog Post Series!!
{ at least for a while}
Arda
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