Estimation Flashcards

1
Q

Central limit theorem

A

If we were to take repeat samples and calculate the mean each time…
Those sample means will be Normally distributed around the true population mean
…even if the population itself is not Normally distributed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Distribution of sample means

A

Normal distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Standard error

A

Standard deviation of the sampling distribution

indicates how different a sample mean is likely to be from the population mean

It tells us the precision of estimation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Standard deviation is for

A

Describing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Standard error is used for

A

Estimating

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Smaller standard error of the mean

A

More precise the estimate of our mean- closer it is likely to be to the true population mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Standard error of the mean equation

A

Standard deviation/ square root of sample size

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

precision is affected by these two things

A

how variable our data are (the SD) and how large our sample is (n)

The other thing being held constant…
The bigger the SD -the bigger the standard error
The bigger the sample size -the smaller the standard error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Confidence interval

A

We wish to estimate a population mean…
We have our observed estimate: the sample mean
We have our estimate of its precision: the standard error of the mean
We can use these two things and properties of the Normal distribution to calculate a range of values we can be confident includes the true mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

95% confidence interval for the mean

A

Mean + 1.96 * standard error

95% of the time our confidence interval will encapsulate the true (unknown) population value we are trying to estimate
Range of values within which the true mean lies 95% of the time- statistically significant if it doesn’t include 0 or 1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Factors affecting that confidence interval width:

A

Variability in the sample (SD)
Sample size (n)
The desired level of confidence
- typically we use 95% but it could be 90%, 99%, etc.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Greater variability of SE

A

Wider interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Greater sample size

A

Narrower interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Greater confidence level

A

Wider interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

If 95% confidence interval includes null value

A

Result would not be significant and p-value is greater than 0.05

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

If null value not included in 95% confidence interval

A

p<0.05

17
Q

Point estimate

A

Best estimate of parameter is the sample mean

18
Q

If confidence interval doesn’t include null value

A

Statistically significant difference

19
Q

Clinical significance

A

Magnitude of effect determined with confidence interval
Part of interval that lies higher than clinical importance
If threshold included in range, it is potentially clinically important depending where the true mean lies

20
Q

Interpretation of 95% confidence interval

A

a range of values that you can be 95% certain contains the true mean of the population

21
Q

What percentage of 95% CIs omit the true population mean

A

5%

22
Q

Reject null hypothesis is CI does not include…

A

0
1 = if ratio

23
Q

If point estimate falls within 95% CI,

A

Consistent with overall population

24
Q

Positive likelihood ratio equation

A

sensitivity/ (1-specificity)