WEEK 3

Question 1

Sampling distribution definition

Answer 1

A sampling distribution is the distribution of a statistic (like a mean or proportion) you get by taking many random samples from the same population.

Question 2

What is bias

Answer 2

a term used to describe statistics that don’t provide an accurate representation of the population

Question 3

What is precision

Answer 3

the consistency or reproducibility of measurements or estimates

Question 4

How to improve precision

Answer 4

Increasing the sample size

Question 5

How to reduce bias

Answer 5

Using random sampling

Question 6

What is sampling error

Answer 6

a statistical error that occurs when an analyst does not select a sample that represents the entire population of data

Question 7

What is a non-sampling error

Answer 7

an error that occurs during data collection, causing the data to differ from the true values

Question 8

Difference between sampling and non-sampling errors

Answer 8

Sampling error is an error that occurs from taking a sample from a larger population, whilst non-sampling error comes from other means such as errors in data collection or data entry

Question 9

What is an observational study

Answer 9

A type of study in which individuals are observed or certain outcomes are measured. No attempt is made to affect the outcome (for example, no treatment is given).

Used when an experiment is thought to be unethical

Question 10

What is an experiment

Answer 10

a scientific test in which you perform a series of actions and carefully observe their effects to learn about something.

Preferred over observational studies as we’re able to test different groups of subjects to the measured response variables

Question 11

Randomisation

Answer 11

A situation where individual outcomes are unpredictable, but there is a consistent overall pattern in the results that can be described using probability — for example, flipping a coin or rolling a die.

Question 12

Replication

Answer 12

Repeating the data collection on many subjects to reduce chance variation in
results.

Question 13

Blocking

Answer 13

splitting subjects into blocks (subsets) based on a variable. believed to have an impact on the results

Question 14

Probability distribution meaning

Answer 14

a mathematical function that describes the probability of different possible values of a variable

It can take any number between 0 and 1, but the sum of the probabilities of all outcomes must equal 1 (1 being 100% and it ranges from 0% - 100%)

Question 15

what does P(A) = 1 mean

Answer 15

the probability of an event happening is 100%

Question 16

What does P(A) = 0 mean

Answer 16

the probability of an event happening is 0%

Question 17

What does P(A) = 0.75 mean

Answer 17

the probability of an event happening is 75%

Question 18

Sample space

Answer 18

the set of all possible outcomes

Question 19

mutually exclusive

Answer 19

two or more events that cannot happen at the same time
e.g. rolling a 2 and a 3 in a single dice roll

Question 20

Collectively exhaustive

Answer 20

A set of events that encompasses all possible outcomes

Question 21

Relationship between collectively exhaustive events and sample space

Answer 21

The union of exhaustive events of an experiment forms the sample space

Question 22

Union

Answer 22

If event A, event B or both event A & B can occur, it is expressed as ‘A or B’ or A∪B

Question 23

Intersection

Answer 23

If event A & event B can occur at the same time, it is expressed as ‘A and B’ or A∩B

Question 24

Marginal probability

Answer 24

the probability of a single event occurring, independent of other events
(e.g. P(A))

Question 25

Joint probability

Answer 25

a statistical measure that calculates the likelihood of two events occurring together and at the same point in time (e.g. P(A∩B))

Question 26

Conditional probability

Answer 26

a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) is already known to have occurred (e.g. P(A|B))

Question 27

∩

Answer 27

and e.g. P(A∩B) where only the outcomes that are common for both A and B are accounted for

Question 28

∪

Answer 28

or e.g. P(A∪B) where all the outcomes of A happening and B happening or both are accounted for

Question 29

|

Answer 29

given e.g. P(A|B) where the probability of A happening given B has occurred

Question 30

What is the formula for conditional probability given that P(B) is the marginal probability

Answer 30

P(A∣B) = P(A∩B) ➗ P(B) or P(A∣B) = P(A∩B) / P(B) ​