LM 7: Estimation & Inference

Question 1

What is sampling?

Answer 1

generating statistics that are estimates of population parameters

Question 2

What is sampling error?

Answer 2

difference between the sample statistic and the population parameter. eg., sample mean & population mean

Question 3

What is the difference between probability sampling and non-probability sampling?

Answer 3

probability sampling: every member of population has the same chances of being selected

non-probability sampling: less representative due to methods considering factors such as access to data.

Question 4

What are the 4 types of probability sampling? SSSC

Answer 4

1. simple random sampling
2. systematic sampling
3. stratified random sampling
4. cluster sampling

Question 5

Describe the 4 types of probability sampling.

Answer 5

1. simple random: truly random sample, each data point equally likely to be selected
2. systematic sampling: choosing every kth member of population
3. stratified random: population divided into sub groups, then simple random drawn from subgroup
4. cluster sampling: several clusters created, each one meant to be a mini-representation of the population

Question 6

What are the 2 types of cluster sampling?

Answer 6

1. one stage cluster
2. two stage cluster

Question 7

Describe the 2 types of cluster sampling.

Answer 7

• one stage cluster: data from all members of clusters used
• two stage cluster: subsamples randomly selected from each sample cluster

Question 8

What are the 2 types of non-probability sampling methods?

Answer 8

1. convenience sampling
2. judgemental sampling

Question 9

Describe the 2 types of non-probability sampling. CJ

Answer 9

1. convenience sampling: data points selected based on availability
2. judgemental sampling: data points handpicked based on researchers expertise & judgement

Question 10

What is the standard error formula?

Answer 10

sx = s (or sqrt variance)/ sqrt n

s = standard deviation
sqrt n = number of samples

Question 11

What is standard error?

Answer 11

measures how much discrepancy is likely in a sample’s mean compared with the population mean

Question 12

What is the standard error of the sample formula using the bootstrap method?

Answer 12

sqrt (1/n-1)* variance

variance = (data value - mean ^2 + data value - mean ^2)…
n = sample size

Question 13

What is the difference between the jackknife and bootstrap method?

Answer 13

jackknife: leaves out one observation at a time without replacement.

bootstrapping: one number in a sample gets replaced.