5: Sampling, Random Error & Intervals ✅ Flashcards

1
Q

Sample

A

Selected subset of a source population

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2
Q

Source population

A

Group of all individuals that we are interested in assessing

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3
Q

Purpose of a sample

A

To study something that cannot be studied as a whole due to practical restrictions

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4
Q

Source population can be

A

Can be general population of a sub-population

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5
Q

Source population in descriptive research

A

It is important the sample reflects the source population

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6
Q

Source population in Analytic research

A

In analytic research it can be more general depending on the research question

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7
Q

Source population: when investigating the biological effect of a disease

A

Source population can be more general

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8
Q

Source population: investigating social/ cultural effects

A

Source population has to be more restricted from where the population is derived

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9
Q

What should the sample be representative of?

A

The source population

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10
Q

Sampling frame

A

List of all the individuals in a source population

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11
Q

Sampling units

A

Individuals to be potentially selected

Most often individual people but can be sometimes larger eg families, streets, hospitals

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12
Q

Statistical interference

A

When sample estimate is used to draw conclusions on the population

It involves using stats to determine the degree of uncertainty

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13
Q

What are we measuring when using samples?

A

We are measuring estimates which carry sampling error

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14
Q

Parameter

A

Measurement of a quantity in a population

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15
Q

Estimate

A

Measurement of a quantity in a sample which aims to represent the true quantity

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16
Q

What does the sample estimate aim to do?

A

To quantify the population parameter

17
Q

Sampling variation

A

Difference between different sample estimates

18
Q

Sampling error

A

Difference in magnitude between sample estimates and the actual population parameter

-> caused by measuring a quantity in a sample rather than in a sourced population

-this is due to chance so: random error
-sample size plays an important role

19
Q

Standard error describes..

A

The uncertainty of how well the sample estimate represents the population

20
Q

Standard error estimates..

A

The SD of the sampling distribution

“average error that can occur whenever we take a sample from a certain size”

21
Q

When does standard deviation exist?

A

For all statistical quantities

22
Q

How many samples does it take to estimate standard error?

23
Q

Standard error equation

A

For the mean:

SE = S / (square root)n

S= sample standard deviation
n= sample size

24
Q

Confidence interval

A

They indicate a range within we are confident the true population lies

25
95% confidence interval
We are 95% confident the population parameter is contained within the interval sample estimate +/- 1.96 standard error Lower confidence interval: Sample estimate - 1.96*standard error Upper confidence interval: Sample estimate + 1.96*standard error
26
What is the sample estimate in the 95% confidence interval?
The sample mean
27
If the difference between the lower and upper confidence interval is small..
Precise Aka low uncertainty regarding true population mean
28
If larger difference between lower and upper confidence interval..
Not very precise Aka HIGH uncertainty regarding true population mean