Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

STATS115 > Lecture 4 > Flashcards

Lecture 4 Flashcards

1
Q

Interpretation of results depends on

A

The study design

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

The study design should be tailored to..

A

..the research question

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

Methods of statically analysis and information produced will depend on

A

The study design

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

Two main types of study design

A
  • descriptive studies
  • analytic studies
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Descriptive studies

A
  • studies which describe things
    E.g surveys
  • descriptive studies are often simply referred to as surveys
  • generally use a sample from the population of interest
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Analytic studies

A
  • studies which test hypotheses

Experimental studies e.g. randomised controlled trials
Observational studied e.g. cohort studies; case-control studies

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

What is a population

A
  • a complete set of entities or elements or units people that we wish to describe or make inference about

Well-defined population:
- the collection of poems by W.B Yeats
Not well-defined population:
- the population of NZ

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

What is a sample

A
  • a subset of a population
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

How to provide a ‘ representative’ sample of the population

A
  • random sampling (random selection) of study units os important
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is random sampling is impossible ?

A
  • need to consider carefully how likely it is that our sampling procedure will produce a repressentiative sample
  • sometimes we can compare the characteristics of the sample to known facts about the population
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Sampling frame

A
  • list of items in a population from which a sample is drawen
  • rearely coincides with the entire population of interest
  • often doesn’t exist

Even without a list we can ensure an ‘unbiased’ sample if every individual has the known chance of being drawn

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

Random sampling to obtain a subgroup

A
  • choose the sample in such a way that every individual in the population has a known change of being selected
  • in a simple random sample, everyone has an equal chance of being chosen
  • this method is the best way of obtaining a sample which is represtiticve of the population
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Sample mean equation

A

Sample mean = population (true) mean + error

Error could be systematic or random

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

Random error occurs due to…

A

… natural variability

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

In regards to random error… increasing the sample size will….

A

Reduce the random fluctuations in the sample mean

Statistical methods allow us to quantify the influence of random error on our estimate

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

Two types of error

A
  • Random
  • systematic
17
Q

Systematic error in a destructive study (bias) occurs due to..

A

Aspects of the design or conduct of the study which systematically distort the results

18
Q

Systematic error in a descriptive study can/cant be reduced by increasing sample size

A

Can’t be reduced by increasing the sample size

19
Q

Two types of bias that cause systematic error in a descriptive study

A

Selection bias - if a sample is not representative of the population
Information bias - if the information collected from the sample members is incorrect

20
Q

We want out sampling frame to..

A

Match the population of interest

21
Q

Probability sampling is important because..

A

It helps justify the statistical models which roll be introduced in this course

22
Q

The key characteristic of probability sampling is..

A

That we know the probability of being selected for everyone in the sample frame

23
Q

Simple random sample

A
  • the simplest form of probability sampling
  • for a finite population of size N draw a sample of size n such that each possible sample has the same probability of being selected
24
Q

Simple random sample

A
25
Q

Stratified sampling - variation

A
  • much of statistical design theory is about controlling variation
  • more variation in the data means less precise inference
26
Q

When is stratified sampling useful?

A

When the population comprises of several groups of similar individuals
- take a simple random sample from within each stratum

  • sampled with probability proportional to size - everyone has the same chance of being selected
    OR
  • sampled with equal numbers from each strata - those in smaller strata are more likely to be selected
27
Q

What is a stratum?

A
  • a population sub-division of similar units
28
Q

Stratified random sample diagram - probability proportion to size

A
29
Q

Stratified random sample - equal numbers form each strata - those in smaller strata are more likely to be selected

A
30
Q

Stratified sampling vs simple random sample

A
  • stratified sampling gives a more precise estimate then for the same sample size from a simple random sample
  • can take different sized samples from different strata (this reduces overall variability)
  • useful is you are interested int eh results for each stratum and some of the strata are small
31
Q

Cluster samples

A

Cluster samples take a simple random sample of groups
- for a single stage cluster sample include all units in the selected groups

32
Q

Cluster sampling is used when

A

The population may be composed of similar and naturally occurring groups

33
Q

Cluster random sample diagram

A

Everyone in each sampled cluster is included in the study

34
Q

Two stage cluster random sample

A
  • simple random sample of one person from each cluster
  • probability of someone being in the study depends on the number in their cluster
35
Q

How to do two stage rCluster sampling

A
  • take a simple random sample of units within a group

E.g: a simple random sample of schools
- a single-stage cluster sample would include all students at the selected schools
- a two-stage cluster sample would take a simple random sample of schools, then a simple random sample of students at each school

36
Q

Cluster samples are useful..

A
  • when the clusters are easy to sample
37
Q

Cluster sampling pro and con compared to simple random sample or a stratified sample of the same size

A
  • usually cheaper
  • usually less precise

Can compensate by raking a larger sample

38
Q

Can combine methods

A
  • stratified sampling of clusters etc
39
Q

How we analyse the data depends on…

A

.. how we chose the data
The formulae for computing estimates from simple ransom sampling, stratified sampling, cluster sampling etc are all different

  • common mistake is to use top simple methods when the data are from a complicated design - this analysis will give misleading results

STATS115 (7 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions