I agree with you that that The State had no reason to take the child, but be careful. The State views those that use violence against it as the most vile criminals and would not hesitate to have you thrown in prison. If you are in prison how can you help your child?

What you say could be 100% true and the ACA could still be unconstitutional. What you are doing here is attacking the person (an imaginary person) rather than attacking the argument. If you want to argue that it is constitutional your best bet would be to go to the constitution and find the parts that you think would allow for this legislation. For help you could read what the supreme court justices said about the legislation.

For the record I don't think this should be modes as "Troll". His observation is correct. If anything I usually try hard to *thank* people who correct me. So, "thanks".... I appreciate that you took the time to correct my grammar.

Society allows police officers to use violence against members of society. They are supposed to only use that privilege under certain circumstances, but many officers have already demonstrated poor judgement and used violence when they should not of used it. The point of these cameras is to provide a control against people who can legally assault the public (police officers) as well as give officers a defense if they are ever accused of using violence inappropriately. This monitoring is necessary because police have already shown themselves to be irresponsible. Any police officer that is intentionally interfering with the recordings should be charged with destruction of evidence.

Mormons (at least the biggest group LDS) would not support any movement to strike down polygamy laws. Currently they excommunicate anyone who practices polygamy even if that person lives in an area of the world where polygamy is normal. Additionally, the LDS Mormons haven't practiced polygamy in so long that they wouldn't want to be in a polygamous relationship anymore than anyone else in this country.

Kosher is also commonly defined as "legitimate". "she consulted lawyers to make sure everything was kosher" is actually an example sentence if you type, "define: kosher" into google.

What you quoted doesn't say what you just said. "both groups were sampled from the same distribution" is not the same as "the means of the treatment group and control groups are exactly equal." The *expected* means of the groups is equal. The math behind the statistical models takes into account random group assignment and so there is no expectation that the groups start exactly the same (or change in similar ways over the course of the experiment).

And what point did you hope to make?

.....and your point is? And how does this relate to your initial statement that scientists "assume that the treatment group and control group were exactly the same at baseline"?

What you have in quotes isn't what I said. The assumptions in the part that I wrote that you quoted were that the treatment had no effect and that group assignment was random.

If you'd like to spell out the assumptions in your statement you are welcome to do that.

Dude, I am listening to you (and wasting my time apparently) trying to explain why your claim that scientists assume that "treatment group and control group were exactly the same at baseline" is false, false, FALSE.

You tried to back way from that by asking me if "two groups would have the exact same average if there were no treatment effect". That is once again false (but in my opinion less false). They would have the exact same expected average, but I wouldn't expect them to have the same exact average.

If you would like to explain to me what I said exactly that is incorrect you are welcome to do that. So far I don't think you've actually claimed that anything I've said is incorrect.

If you'd like to go to a third party that is fine with me to. I'd accept anyone that is really good at Math or Statistics. A PhD just to show they (probably) know what they are talking about would make them more acceptable.

You should study some statistics. You seem to some (very) incorrect ideas about what the tests mean.

This is how it works. In a randomized study scientists will assign subjects two a treatment group and a control group. As you might guess assignment to a group is done randomly.

Now we go to one of the big misconceptions you seem to keep going back to. You state that scientists assume "treatment group and control group were exactly the same at baseline." They do NOT! On purpose they are creating random groups. They are making no effort at all to make the groups equal and in fact if they made any effort to make the groups equal it would invalidate the math behind the statistics and the experiment would have no real value.

They have two groups and they are as sure as they can be that the two groups aren't equal because groups were assigned randomly. They do whatever it is they want to do and then they measure whatever it is they want to measure. Statistics tells the scientists how likely it is that any differences they see between the groups are caused by random chance. In other words, statistics might say something like, "If the treatment had no effect at all we'd expect to see results like this x% of the time just based on the randomness of group assignment."

At no point in this process did the scientists assume that the treatment group and the control group were exactly the same.....

And if you want to learn this stuff you most certainly can. Pick up a cheap textbook on statistics. Read it and try to understand it. Be careful to make sure that you are learning not just how to run a t-test, but the assumptions that are built into a statistical model.

The null hypothesis would probably normally be that the treatment has no effect. In some studies it might be that there is no relationship between the things that are being measured. The null hypothesis does not mean, "we assume that that the two groups are exactly the same". You thinking it means that once again shows that you know very little about statistics or how statistics is used in science.

You haven't studied statistics, have you? You might want to try and learn a little introductory statistics.

I don't know in particular which study you are referring to, but I've never seen or heard of a medical study where the doctors assumed the control group and the treatment group are exactly the same. Assuming proper statistical protocols were followed statistics tells us what the odds are that what we observed is just a random by-product of how people were assigned to groups.

In short, you don't understand the math behind these experiments and so you are convinced that the experimenters have made silly assumptions.

I would be careful about generalizing here. Some women probably discriminate against other women. Some men probably do the same thing. When you paint with too broad a brush you run the risk of fueling "sisterhood versus the patriarchy" arguments.