# Search results

1. ### Least square estimation with one parameter ?

There is a trap that you might not have thought of. With least squares it is possible that the simple answer gives you a theta which is can't be true. For instance if the X's are 10, 10, 10, and 20, then the average is 12.5 and theta would be 10 + 2x2.5 = 15. But 20 is impossible in U(10, 15)...
2. ### Least square estimation with one parameter ?

Try drawing the distribution of U(10, 10+theta) and draw a line at the mean. If it makes things easier to see, draw U(10, 10+8) i.e. U(10, 18) and find the mean.
3. ### Least square estimation with one parameter ?

Can you find the mean of U(10, 10+theta)?
4. ### Can you help me with this exercise about p.m.f

Make a new row between X and P, labelled Z. Fill in the Z row. Ignore the X row and continue.
5. ### Poisson Regression Interpretation

I'm not suggesting that OLS is a better model, just that the results from OLS are easily interpreted and should give an indication of what you can expect from the Poisson after they have been manipulated to give real world meanings.
6. ### Poisson Regression Interpretation

Just to give you an idea of the sort of values you are likely to get when you finish you interpretation, you could try the usual OLS regression where the coefficients often have real world meanings which should be close to your final Poisson interpretations.
7. ### Expected value of chi-square distribution

X_1 and X_1 are not independent so E(X_1**2) does not = E(X_1)*E(X_1)

9. ### Why does bootstraping with 50% samplesize and no replacements always gives appropriate confidence intervals.

Interesting problem, though.
10. ### I have a Mean and Standard Deviation. If I multiply the Mean by a number (non-constant), do I have to multiply the Standard Deviation by that number?

A little, but I have no intuitive feel for this foreign and statistics intense game. All I can suggest is that you try both ways and see which has more success.
11. ### Why does bootstraping with 50% samplesize and no replacements always gives appropriate confidence intervals.

You're right - the jackknife should strictly use the means of all the subsamples. However, if there are too many to enumerate, then you will get a good approximation by taking a random sample of the subsample means. If, for instance, you have a sample of 50 and you consider all the subsamples of...
12. ### I have a Mean and Standard Deviation. If I multiply the Mean by a number (non-constant), do I have to multiply the Standard Deviation by that number?

I think we are talking at cross purposes here. The short answer, in my opinion, is that you can decrease the numbers to 85% and the variability will automatically decrease to 85% without you doing anything, or you can use the untouched numbers and decrease the mean and SD at the end. If this...
13. ### I have a Mean and Standard Deviation. If I multiply the Mean by a number (non-constant), do I have to multiply the Standard Deviation by that number?

Yes Do an experiment in Excel. Type some random numbers. Find the mean and SD. Multiply the numbers by 0.85. Find the mean and SD. Compare the means and SDs
14. ### Why does bootstraping with 50% samplesize and no replacements always gives appropriate confidence intervals.

I wouldn't dismiss the jackknife too quickly. The delete-d jackknife method has a factor ( n-d)/d which is just 1 in your case. The only real difference is that you are taking a random sample of possible deletions instead of listing them all.
15. ### Why does bootstraping with 50% samplesize and no replacements always gives appropriate confidence intervals.

Is this something to do with the jackknife?
16. ### Descriptively nterpreting data output

Typically you get a slope and an intercept. Often the slope has a real-world meaning such as a rate and means how much y increases for each unit increase in x. Sometimes the intercept also has a real-world meaning as a zero or starting level but this is less common.
17. ### probability density

If you know the form that your data takes, (normal say) then StatsSolver's suggestion is a good one. If you want the PDF of your actual data and you don't know the form, then a histogram of the values is a PDF once it has been scaled for an area of 1. Say you have 2000 readings and you make a...
18. ### Is this a regression?

When you have found a way to do it, what will the outcome look like?

Cheers. Kat
20. ### Normality test in data with multiple treatments

The normality applies to the residuals, not the data itself. Many folk are happy with looking at a normal plot of all the residuals as a group. If there is a strong pattern away from the straight line, then this may indicate that the model can be improved with a transformation, say, rather than...