5: Sampling, Random Error & Intervals ✅

Question 1

Sample

Answer 1

Selected subset of a source population

Question 2

Source population

Answer 2

Group of all individuals that we are interested in assessing

Question 3

Purpose of a sample

Answer 3

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

Question 4

Source population can be

Answer 4

Can be general population of a sub-population

Question 5

Source population in descriptive research

Answer 5

It is important the sample reflects the source population

Question 6

Source population in Analytic research

Answer 6

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

Question 7

Source population: when investigating the biological effect of a disease

Answer 7

Source population can be more general

Question 8

Source population: investigating social/ cultural effects

Answer 8

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

Question 9

What should the sample be representative of?

Answer 9

The source population

Question 10

Sampling frame

Answer 10

List of all the individuals in a source population

Question 11

Sampling units

Answer 11

Individuals to be potentially selected

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

Question 12

Statistical interference

Answer 12

When sample estimate is used to draw conclusions on the population

It involves using stats to determine the degree of uncertainty

Question 13

What are we measuring when using samples?

Answer 13

We are measuring estimates which carry sampling error

Question 14

Parameter

Answer 14

Measurement of a quantity in a population

Question 15

Estimate

Answer 15

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

Question 16

What does the sample estimate aim to do?

Answer 16

To quantify the population parameter

Question 17

Sampling variation

Answer 17

Difference between different sample estimates

Question 18

Sampling error

Answer 18

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

Question 19

Standard error describes..

Answer 19

The uncertainty of how well the sample estimate represents the population

Question 20

Standard error estimates..

Answer 20

The SD of the sampling distribution

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

Question 21

When does standard deviation exist?

Answer 21

For all statistical quantities

Question 22

How many samples does it take to estimate standard error?

Answer 22

1

Question 23

Standard error equation

Answer 23

For the mean:

SE = S / (square root)n

S= sample standard deviation
n= sample size

Question 24

Confidence interval

Answer 24

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

Question 25

95% confidence interval

Answer 25

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

Question 26

What is the sample estimate in the 95% confidence interval?

Answer 26

The sample mean

Question 27

If the difference between the lower and upper confidence interval is small..

Answer 27

Precise

Aka low uncertainty regarding true population mean

Question 28

If larger difference between lower and upper confidence interval..

Answer 28

Not very precise

Aka HIGH uncertainty regarding true population mean