wow, nice low blow at the assumption that i get my information from fox news or someone on talk radio (even though the only person on talk radio i listen to is matt drudge and that is only once a week, unless you count coasttocoastam and i rarely watch tv news since all of it, and i mean all of it is sensationalism). i guess i would be more informed if i got my information from cnn or nyt
i guess there i no way i could have gotten this information from researching and reading...
Sorry for the personal attack Puff. Sometimes I get carried away. You know I didn't mean anything by it
Let's follow this man's logic in another area. Cancer rates. We're trying to find out whether tobacco, recently introduced into a society that never had it, might increase cancer rates.
Colin Greenwood: "The truth is that it is total irrelevance. Cancer has been increasing continuously over the period, but the use of tobacco is neither here nor there in the equation."
Now put in that context it's hopefully even obvious to you, that Mr. Greewood's argument is flawed and he's just blowing (pun intended) smoke out of his ass. The truth is he doesn't know what part of the equation the ban on handguns play in the rising crime rate, if any. Just saying it was rising before the ban doesn't mean it had no effect. But like tobacco there is evidence that it does have an effect elsewhere. So it's logical to assume it might have an effect here.
Why has the crime rate and the use of guns been increasing in the UK? Because crime is a function of people's choices to disregard laws and harm others, not of the availability of guns. If, in fact, the ban had no effect, why then ban guns if the trend in the UK just continued rising like nothing had happened? More importantly, why blame guns, especially in the hands of the law-abiding, whose ability to protect themselves definitely went down with the ban?
I think you are working to justify your emotional responses instead of examining them in a logical manner.
You want proof? Here's my proof.
This is a graph of Greenwood's data of homocides by firearms in the UK since 1980:
Using Intercooled Stata 9.2, a high-powered statistical analysis program that I got for my ECON Stat class, I performed a least-squares regression analysis on the data to determine the impact of the gun ban on the homocide by firearm rates.
Testing just the correlation between the existence of a gun ban and the number of homicides each year, it appeared that there was some correlation. Here is my data:
Source | SS df MS Number of obs = 24
-------------+------------------------------ F( 1, 22) = 6.34
Model | 1448.58403 1 1448.58403 Prob > F = 0.0196
Residual | 5029.91597 22 228.632544 R-squared = 0.2236
-------------+------------------------------ Adj R-squared = 0.1883
Total | 6478.5 23 281.673913 Root MSE = 15.121
------------------------------------------------------------------------------
homocide | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
gunban | 17.09244 6.790491 2.52 0.020 3.009821 31.17505
_cons | 52.76471 3.667284 14.39 0.000 45.15922 60.37019
------------------------------------------------------------------------------
Now, I don't know how well that will format to the forum, but I'll explain the significant points. First, the R-squared variable in the top right is 0.2236, meaning that this test implies that the ban on guns accounted for about 22% of the rise in homocides by firearms. The small Prob > F stat above the R-squared implies that we can be confident that the ban has some effect. Even more important are the Coef., t, and P>|t| statistics for the variable gunban. The large coefficient implies that the variable has a large effect on homicides. A 2.069 (or -2.069) t-statistic from a data set with 23 degrees of freedom, as in this case, means that we could be 95% confident, the general goal to meet, that the variable is significant; here it's 2.52, meaning we can be about 98% confident, as the P>|t| value shows (confidence = 1 - P>|t|).
This analysis implies a strong correlation between the ban on guns and the rise in homocides by firearms.
However, this analysis is too simple, and we have more information that can account for the rise in homocides.
The other information we have from Greenwood's data is the year, which is significant because of his assertion that gun crime has been rising throughout time and not because of a single incident. Therefore, I performed a second analysis, and it revealed a lot of flaws in the original test.
Source | SS df MS Number of obs = 24
-------------+------------------------------ F( 2, 21) = 9.22
Model | 3028.62991 2 1514.31495 Prob > F = 0.0013
Residual | 3449.87009 21 164.279528 R-squared = 0.4675
-------------+------------------------------ Adj R-squared = 0.4168
Total | 6478.5 23 281.673913 Root MSE = 12.817
------------------------------------------------------------------------------
homocide | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
year | 1.90367 .6138305 3.10 0.005 .6271393 3.1802
gunban | -5.7516 9.348233 -0.62 0.545 -25.19231 13.68912
_cons | -3731.731 1220.299 -3.06 0.006 -6269.481 -1193.98
------------------------------------------------------------------------------
As you can see, the R-squared variable has risen to 0.4675, meaning that the ban and time alone account for almost half of the trend in homocides (although exactly how much each variable accounts for is unknown). The Prob>F variable is even smaller (0.0013), meaning we can be more confident in this test than the last one. Now, looking at the variables.
The most striking aspect of this test is the change in the Coef. (-5.7516), t (-0.62), and P>|t| (0.545) statistic of the gunban variable. Now that we have taken time into account, the presence of a gun ban actually
lowers the number of homocides by firearms per year, as represented by the coefficient.
This drastic change implies that the more factors that we take into account, the better we see that the ban has positive effect on gun crime and that the appearance of the raw data is simply masked by other factors. Take a look at the t-statistic. It's not even close to 2.069 or -2.069. Looking at the P>|t| statistic, we can only be 45.5% confident that the ban on guns has ANY impact on the rise in gun crime, and if it did, its impact was probably that it lowered gun crimes because the t-statistic is negative.
Even still, the second analysis was from from sufficient. 54% of the factors are still not taken into account. However, with each factor that we add into the equation, the observed impact of the other factors change. With that being said, the apparent direction of the effect of the gun ban is that it turns out to be a more positive than negative factor on gun crimes as we look at other explanations for the rise.
Is that logical enough for you?
Actually, they were invented (via the cannon) to defend people more easily.
Defend themselves how? By building a wall of cannons that attackers couldn't penetrate? Or by projecting a massive iron sphere at them, smashing and crushing their bodies?