Brainscape's Knowledge GenomeTM

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


See full index

Research Literacy > Data Distribution > Flashcards

Data Distribution Flashcards

1
Q

What does normally distributed data look like?

A

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

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

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

A

Non-parametric

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

Non-parametric data

A

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.

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

Mean

A

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

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

Median

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Mode

A

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

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

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

A

They are roughly the same

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

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

A

They are all different

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Standard deviation (SD)

A

Average distance from the mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Range

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Interquartile range (IQR)

A

The range of the middle half of a distribution.

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

What does high variability in a data set indicate?

A

Less consistency in our data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What does low variability mean in a data set?

A

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

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

What does Standard deviation tell us?

A

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

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

What are the terms main median and mode known as?

A

Measures of central tendency

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

Causation

A

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

17
Q

Correlation

A

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

18
Q

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

A

A scatterplot graph

19
Q

Strong negative correlation or R-value

A

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 .

20
Q

Positive correlation

A

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

21
Q

Negative correlation

A

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

22
Q

What is another name for experimental studies?

A

Trials

23
Q

What is an observational study?

A

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

24
Q

What are experimental studies?

A

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

25
Q

Cohort studies

A

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.

26
Q

Aetiology

A

What factors contribute to the problem?

27
Q

Prognosis

A

How does the problem develop?

28
Q

Diagnosis

A

How good is the diagnostic test?

29
Q

Intervention

A

Does this program or treatment work?

30
Q

Mediator

A

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.

31
Q

Cofounders or confounding variables

A

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)

32
Q

Strength that are characteristic of quantitative research

A

Largest sample sizes objectivity and accuracy replicability

33
Q

Limitations of quantitative research

A

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

Research Literacy (1 decks)

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