Basic concepts

Question 1

Why are statistical tests important?

Answer 1

• Inherent in process of doing quantitative research

- Essential in designing research and interpreting results

Question 2

What is a statistical test?

Answer 2

• A procedure for addressing a problem with a specified sequence of steps
• Relies on assumptions
• Requires the formulation of a hypothesis

Question 3

What is a hypothesis?

Answer 3

An initial idea of expected patterns

Question 4

Null hypothesis

Answer 4

H0 - The default - always assumed to be correct

- There is no statistically significant relationship/pattern

Question 5

Alternative hypothesis

Answer 5

H1 - There is a statistically significant relationship/pattern

Question 6

What is a confidence level?

Answer 6

• The probability that H1 is correct

- e.g. 99% or 95%

Question 7

How does a table of critical values work?

Answer 7

If the output is greater than the critical value, you reject the null

Question 8

Why do we ‘fail to reject’ the null instead of ‘accepting’ the alternative?

Answer 8

Leaves room to re-test and improve

Question 9

The area under a distribution curve…

Answer 9

Represents the probability of an outcome in that range

Question 10

What is significance level?

Answer 10

How likely it is that the results are due to chance/The probability that the null hypothesis is correct

Question 11

When do we accept H1?

Answer 11

If the significance level is sufficiently low (usually 0.05 or 0.01)

Question 12

When is the critical value determined?

Answer 12

Before the test is carried out

Question 13

What is the population?

Answer 13

The whole body of individuals we’re interested in

Question 14

What is the sample?

Answer 14

A collection of individuals drawn from a population

- two samples from the same population are expected to have the same characteristics

Question 15

What is a sampling strategy?

Answer 15

A method applied to choose a sample from a population

Question 16

What are the main requirements in a sample?

Answer 16

• Large enough to ensure precision

- Careful consideration to avoid bias

Question 17

What is accuracy?

Answer 17

A measure of correctness - how close the results are to the true value. This requires the sample to be representative of the population and measurements to be correct.

Question 18

What is precision?

Answer 18

A measure of reproducibility - how well a result has been determined without reference to its closeness to the true value. This requires the sample to be large enough to compensate for variability within the population.

Question 19

What is bias?

Answer 19

Over or underrepresentation of a particular characteristic of a population.

Question 20

How might bias occur?

Answer 20

• Results from subtle aspects in our sampling strategy
• Depends on the target population
  (e. g. door knocking)

Question 21

What are the fundamentals of sampling?

Answer 21

• Every individual in the population has equal and independent probability of being included in the sample
• Inclusion of one individual does not affect the selection of another

Question 22

What is random sampling?

Answer 22

• Random selection
• Often by assigning labels to a population
• e.g. random number generator

Question 23

What is systematic sampling?

Answer 23

Selecting every nth individual from a population

Question 24

Why might interviewing people ‘at random’ be problematic and how could it be improved?

Answer 24

• Might be influenced by conscious/subconscious bias
• We can’t test for or correct this so it is not acceptable for practice in academic studies
• Sample the nth person passing by (systematic) - the order of individuals is assumed to be random (unlike choosing every nth house)

Question 25

What is assumed normal distribution?

Answer 25

• We assume samples and populations are approximately normally distributed
• This is where we would use parametric statistics

Question 26

Ardoyne Road, Belfast…

Answer 26

There are patterns to the houses in that area based on what religion you are – you will get very different results from different parts of that area so you could systematically sample all protestant, or all catholic houses.

Question 27

What is discrete data?

Answer 27

• Can only take particular values
• May potentially be an infinite number of those values, but each is distinct and there’s no grey area in between. - Can be numeric (like numbers of apples) but it can also be categorical (like red or blue, or male or female, or good or bad)

Question 28

What is continuous data?

Answer 28

• Not restricted to defined separate values, but can occupy any value over a continuous range
• Between any two continuous data values there may be an infinite number of others
• Continuous data are always essentially numeric