Data Distribution

Question 1

What does normally distributed data look like?

Answer 1

A Bel curve where more observations are dentally packed in the centre and both sides are roughly even

Question 2

What is a term for data that is not normally distributed?

Answer 2

Non-parametric

Question 3

Non-parametric data

Answer 3

Data that is positively or negatively skewed so the tail of the data may have a higher or lower value.

A positive skew means that the tale of the data is longer for higher values.
And negative skew means the tale of the data is longer for lower values.

Question 4

Mean

Answer 4

Is the average value i.e. all the hours added together and then divided by the number of people.

Question 5

Median

Answer 5

Is the middle value when a data set is ordered from the least the greatest.

Question 6

Mode

Answer 6

Is the number that occurs most often in a data set.

Question 7

In normally distributed data, what happens to the main the median and the mode?

Answer 7

They are roughly the same

Question 8

Ins skewed data what happens to the mean the median and the mode?

Answer 8

They are all different

Question 9

Standard deviation (SD)

Answer 9

Average distance from the mean

Question 10

Range

Answer 10

The difference between the largest or highest and the smallest or lowest.

Question 11

Interquartile range (IQR)

Answer 11

The range of the middle half of a distribution.

Question 12

What does high variability in a data set indicate?

Answer 12

Less consistency in our data

Question 13

What does low variability mean in a data set?

Answer 13

We have greater consistency and therefore more certainty in our data.

Question 14

What does Standard deviation tell us?

Answer 14

It helps us judge how common or rare the thing we observing is

Question 15

What are the terms main median and mode known as?

Answer 15

Measures of central tendency

Question 16

Causation

Answer 16

Something that either makes something else happen or prevent it from happening for example heat causes ice to melt

Question 17

Correlation

Answer 17

Is when two or more things seem to happen together but one probably doesn’t cause the other for example participating in sports and consuming alcohol to hazardous levels

Question 18

What is one of the most common ways to represent a correlation?

Answer 18

A scatterplot graph

Question 19

Strong negative correlation or R-value

Answer 19

Both terms that describe how closely related to 2 or more phenomena are

Our values are ratios, which means they’re always between one and negative one the closer the value is a whole number the closer or stronger the relationship between the two .

Question 20

Positive correlation

Answer 20

Two things rise and fall together e.g. householding come life expectancy

Question 21

Negative correlation

Answer 21

as one thing rises the other thing falls, as an adult agent increases their likelihood to commit a crime decreases

Question 22

What is another name for experimental studies?

Answer 22

Trials

Question 23

What is an observational study?

Answer 23

Researchers investigate the effective exposures that already exist in a population on that populations outcomes

Question 24

What are experimental studies?

Answer 24

Research is investigating the influence of an exposure or intervention on a particular outcome.

Question 25

Cohort studies

Answer 25

Longitudinal observational studies which investigate predictive risk factors and Health out comes overtime. No intervention treatment or exposure is administered to the participants. The factors of interest to the research is exist already in the study group under investigation.

Question 26

Aetiology

Answer 26

What factors contribute to the problem?

Question 27

Prognosis

Answer 27

How does the problem develop?

Question 28

Diagnosis

Answer 28

How good is the diagnostic test?

Question 29

Intervention

Answer 29

Does this program or treatment work?

Question 30

Mediator

Answer 30

Something that lies on the causal pathway between the exposure and the outcome. For instance if a person is working long hours they work hours limit their capacity to undertake exercise which in turn is associated with weight gain.

Question 31

Cofounders or confounding variables

Answer 31

Factors associated with both the exposure and the outcome and artificially explain the association you observed for instance the amount of food that a person consumes could be associated with working long hours (exposure) and with weight gain (outcome)

Question 32

Strength that are characteristic of quantitative research

Answer 32

Largest sample sizes objectivity and accuracy replicability

Question 33

Limitations of quantitative research

Answer 33

Experiments can be costly in time and labour intensive, cohort studies are highly intensive as populations must be followed up overtime testing a hypothesis may mean that other explanations for associations are ignored, results may not be generalisable to specific context or populations and being unable to help us understand social phenomena