Deltoid

In article none+1 stratos@crl.com (

In article ,

Janine K. Johnson wrote:

Recently, several postings discussed the Orlando Florida phenomena of 1966/67, in which a drop in the rape rate was noted after a much publicized program co sponsored by the local police and the Orlando Sentinel, in which 6,000 women were trained in the use of firearms.

Knox, and other experts who have analyzed the Orlando phenomenon, contend that the rape rate decreased because of the media publicity, and because women were armed and trained. (Paxton Quigley, Armed and Female, St. Martins Press.):

Mr. van Meurs rebutted this contention by showing data that demonstrate that when examined over a longer period of time, the drop between the 1966 and 1967 rape rate is not distinguishable from the noise of random variations in rapes in Orlando. Based on this, Mr. van Meurs believes he has proved the training program did not have any effect on the rape rate.

I think you have misunderstood him. The training program might have had an effect on the reported rape rate. However, you cannot reject the alternative explanation that the decrease was due to random variation in the rate.

Steve D. Fischer writes:

No, Mr Van Meurs did not prove his case. He failed to show that the previously observed drops in rape did not ALSO occur because of:

(1) Increased police vigilance due to public outrage over past increases in the rate of rape.

(2) Media attention given to the high magnitude of rape.

One simple explanation could be called the “pissed off” model. Rape continues to rise until it reaches a level at which the public becomes pissed off and pressures the police to do something about it. The increase in police activity either gets the rapists off the streets or scares them away to an area which is receiving less heat at the moment. Viewed in that way, the gun training program was simply one way the public showed its outrage. All the past decreases could have occurred through very deterministic ploys aimed at getting the rape rate down to “an acceptable level.”

Perhaps they did. However, this is an argument AGAINST the possibility of the gun training causing the decrease. If these other measures decreased the rate in the past then this suggests that they decreased the rate in 67 as well, and the gun training may not have had any effect.

The potential mistake Mr Van Meurs has made is in assuming that rape is totally random. The only way to test my hypothesis is to go back and read the news accounts each year in Orlando and determine if special efforts were taken in the years that the previous decreases in rape were noted.

There’s a big problem with your hypothesis. Let me illustrate with an example:

I’m going to roll a pair of dice to simulate a random crime rate. If the rate gets into double figures the community is outraged and demands that something be done to reduce it. I’ll respond by saying “Abracadabra” before rolling the dice to try to drive the crime rate. Here goes:

4 9 7 9 9 5 11 (Oh no! Crime has skyrocketed! Abracadabra!!) 6 (Phew! Got it back down.) 7 10 (Oh no! It wore off! Abracadabra!!) 6 6 10 (Abracadabra!!) 4 (Wow! reduced it 60%!) 7 8 etc etc.

Every time I said “Abracadabra” the rate went down. Do you think that I made it go down?

In article fkk@leland.stanford.edu writes:

In a recent post Pim cites Tim Lambert as support for his position on the Florida data. I’m sorry but Lambert’s analysis is flawed at its core.

No it isn’t. It appears that you don’t understand what statistical hypothesis testing is, or what it means.

Let’s see what he says: First of all Rick is stating that

     it is supportable only in the 'right' time span. Yet he fails
     to provide proof for such remarks. The time span is the same
     data as used by Kleck. It is Kleck however who is
     misleading the facts by carefully selecting his data. Yet
     even this is not going to help him since the data show no
     support for his thesis as well.

This is overstating things somewhat. The data does support his hypothesis, in that the reported rape rate did fall. However, this decrease was not statistically significant. This means that random variations in the reported rape rate provide an equally good explanation.

A crime rate two standard deviations from the mean would be statistically significant. However, The 67 rape rate was only 0.9 standard deviations less than the 58-66 mean, so this rate is not statistically significant. However the 66 rate was 1.7 standard deviations above the mean, so the change from 66 to 67 was 2.6 standard deviations (of the 58-66 rate). This is NOT significant because the standard deviation of the changes in the rates does not equal the standard deviation of the rates. For this data, the standard deviation of the rates from 58-66 is 12, and the standard deviation of the changes from one year to the next in the years 58-66 is 16. The change from 66 to 67 does NOT exceed 2 standard deviations (of the 58-66 changes in the rate).

In Kleck’s statistical analysis of the Orlando data, he wrote:

“It might be suggested that Orlando had experienced erratic ups and downs in its rape trends before and that the 1967 experience just happened to reflect one of the brief, sharp downward swings in the rape rate, which it had experienced before, and that the downward swing was therefore unrelated to the gun training program. However, this suggestion too is unlikely, since Orlando had not experienced so large a one-year change in rape rates in its recent past, and the decrease exceeded two standard deviations, a measure of the variability in rape rates over the 1958-1966 period (1958 was the first year the FBI reported rape data for the Orlando SMSA). In other words, the rape decrease was considerably larger than would be expected on the basis of variation in the rate in the recent past.”

This is mathematically incorrect. Kleck has confused “standard deviation of the rates” (a measure of the variability of the rates) with “standard deviation of the CHANGES in the rates” (a measure of the variability of the CHANGES). His conclusion about the decrease being considerably larger than expected is simply incorrect.

The notion that you can accurately assign a standard deviation to the data as Tim Lambert - and perhaps Kleck as well is fraught with hazards.

The problem is that there is no in this case there is no way to determine an accurate mean for the data - there is therefore no way to accurately determine a standard deviation.

In this case - the rape rate in each year is actually an INDEPENDENT and entirely different measurement - potentially reflecting entirely different conditions. An estimate of a mean and standard deviation when you really have only single data points to support a particular view is invalid in this case. You may make certain assumptions to arrive at a number but these assumptions can easily include observer bias.

This is confused. Statistical hypothesis testing works by DISPROVING hypotheses. In this case the null hypothesis is that the observations are drawn from the same normally distributed population. Under this hypothesis the sample mean and standard deviation are unbiased estimators of the underlying mean and standard deviation. The statistical test tells us that we cannot reject the null hypothesis. You are correct in that it might be false, but statistics can never prove it to be true.

Simply taking y number of years around any given data point and trying to calculate a mean and standard deviation is simply wrong without compelling reasons based in physical reality. One might make compelling reasons to select a particular time range but there are so many variables that can affect the rape rate in any given year it is easy to be wrong.

In this particular case 1958-66 was chosen by Kleck because it was all the UCR data available about rape rates in Orlando before the gun training.

Tim Lambert’s comments should be entirely discounted - his numbers are meaningless - he could select the range of data any way he pleases to get his numbers.

Utter nonsense. I didn’t select the range of data — Kleck did. I merely corrected the error in his calculations.

I also note that by the same reasoning Frank could also have said that Kleck’s numbers are meaningless, but he doesn’t. Is this the pro-gun double standard at work again?