Why are statistics misleading?
467857
They can be spun anyway you want them to be.\n\nFor instance you can say we are concerned that 20% of the population is overweight.  But what we might not know is that this was 25% a few years ago and therefore we have spun the stat negatively.  (not even stressing that 80% are not overweight).
270990
Descriptive Statistics do no intend to "fit" a distribution on the data or to predict new observations given the data.\nInstead, it pretends to "describe" the data in terms of its central tendency measures (mean, median, etc.) as well as dispersion statistics (variance,  rank, inter-quartile rank, etc.), bias statistics, etc.\nSummaries like histograms are also a good example of descriptive statistics.
187791
I'm assuming the quote is meant to be a joke, but actually, it would be very surprising to find out that 50% of children are of below average intelligence. This would imply that the arithmetic mean of children's intelligence was identically equal to the median, an unusual observation.
458174
Actually, statistics books are notorious for being written in such a way that no normal human can understand them. The trick, generally, is trying to find a way to relate the problems to something you're interested in. For example, if you like basketball: one possible sampling distribution would be the number of free throws individual players make over a season. You could take a sample of, say, 10 of the players and find the mean and standard deviation. You could compute a 95% confidence interval with that information, which would allow you to say that you're 95% confident that the average number of free throws made by NBA players in a season will be between this number and that number. You could find the probability that a given player would make at least a certain number of free throws in a season by finding the z-score and looking it up on the normal probability distribution table, etc. If you're really struggling with the terminology, I recommend visiting your math help center on campus (most of them have one), or contacting a tutor.
318936
This is a very good question. In biology, where you are measuring things like length, height, number of bristles,  it is because they are determined by a large number of genes and environmental factors that tend to be additive in effect, rather than multiplicative. Not all things are distributed normally, which is why we somteimes need transformations to do statistics on them that assume normality. Those that aren't normal involve other than additive interactions, or some other factor that doesn't produce that kind of distribution.
224393
Not according to Myth Busters.
615933
Teaching graduate students the proper ways to analyze data statistically is one of the most difficult things- It isnt interesting to them, it's hard to grasp, and there are rules for variance, independent and dependent variables, sample populations and distribution, even and uneven sampling comparisons..on and on.
1156399
This is a good question even for a statistician.\nThe problem is your set is small and I do not know what the deviation between samples is, however the repeatability and reproducibility information can bind the window \nthrough which the third value will fall through or perhaps even remain in.  \n\nLet me know.
287369
Broadly, it means that the hypothesis was not sufficiently proven (or disproven). This could be because of flawed experimental design, weak or improper statistics, or incorrect interpretation of results.
739621
Statistics can be manipulated to prove or disprove anything you want.  If you want to trust them, you will have to trust whatever entity put them together or look at the same type of statistics from several reliable sources.
131097
marketeers use statistics to lie all the time. they simply adjust math to prove thier product is best. plus, they are always talking about THE BOTTOM LINE. it takes math to get there. I think sales is a dreadful profession.
488365
Try again Paul C.  The population doesn't need to look normal.\n\nThis all comes down to the Central Limit Theorem.  Let's assume that I take many samples of size 1004 from the population.  Well, each sample will have a percentage that is different from the population percent, because samples are going to look different from the population.  Also, each sample is going to look different from each other, because they are different samples.  If we were to draw a graph that looked at the "behavior" of these many samples, we would notice the following:\n\n1.  If I were to average out all of these sample percents, I would get the population percent.  Hopefully you can see why this would happen.  Sample percents will be around the population percent, but just be off by a little bit.\n\n2.  If I were to look at the spread of the percents, the spread would be smaller as bigger samples were taken.  In other words, if I had taken samples of size 500, the sample percents would be more spread out than for samples of size 1004.  That is because if were take larger samples, then we have more information about the population, so we should expect to get closer to the population percent.\n\n3.  As I take larger and larger samples, the shape of the graph of sample percents would look more and more like a normal curve.  A normal curve is shaped like a bell, where the middle of the bell is were the population percent is.\n\nSo Paul C, it doesn't matter that the population doen't look normal; all we need is a sample that is large enough.\n\nNow the margin of error on polls is typically going to be\n\n2*sqrt(p(1-p)/n))*100%\n\nwhere p is the sample proportion (the sample percent divided by 100%) and n is the sample size.  It can be shown that this margin of error would be at its largest if p = 0.5, so the largest the margin of error would be in this case would be\n\n2*sqrt(0.5*0.5/1004)*100% = 3.2%\n\nThis is typically associated with 95% confidence.  This basically means that if I were again to take many, many samples of size 1004,  95% of the sample percents would be within a margin of error away from the true population percent.\n\nThis of course depends on the sample that is taken.  The online polls that you see would not be good estimates for the population percent.  Below I have a link to a story that MSNBC has on each of its online polls.  The title is "How 1,000 people can be more representative than 200,000."  I think that it is a very good explaination of this topic.
707601
These are not equal.  They have different graphs.
44620
statistics are calculated for one reason: to persuade someone. for example the statistics of teen pregnancy are used to persuade teenage girls not to get pregnant.
96086
What's your question?  Applied statistics are critical for the successful evaluation of lab studies.  Without it  interpretations of experimental results are subjective.  Of course, an over reliance on statistics is just as dangerous as many statistics show at the end of the day is testing the probability of an event occuring against the random probability of chance.
1130931
In statistics, an outlier is a single observation "far away" from the rest of the data.\n\nIn most samplings of data, some data points will be further away from their expected values than what is deemed reasonable. This can be due to systematic error or faults in the theory that generated the expected values. Outlier points can therefore indicate faulty data, erroneous procedures, or areas where a certain theory might not be valid. However, a small number of outliers is expected in normal distributions.\n\nEstimators not sensitive to outliers are said to be robust.
472192
To elaborate further, your mode does tell you what the most common value in your data is, but, like the median, it's a somewhat arbitrary value.  For example, take the data set 1,2,2,3,7.  Both the mode and the median are 2, and the mean is 3.  Now take the data set 1,2,2,25,50.  Again, the mode and the median are both 2, but the mean is now 16.  Now, say that second data set represents the number of shark attacks that have happened in the past 5 years off the coast of a beachfront property you're thinking about buying.  I'd much rather know the mean number of shark attacks, not the mode or the median, wouldn't you?