Introduction to quantitative data

Question 1

What kind of data is being studied here?

Answer 1

Numerical data

Question 2

Research questions of quantitative data

Answer 2

Descriptive and exploratory
With the goal of obtaining numerical objective data in order to show the relationships between variables

Question 3

4 types of design of quantitative studies

Answer 3

Descriptive
Correlational
Quasi- experimental
Experimental

Question 4

Descriptive designs

Answer 4

Aim is to gain as much info as possible on something
To generate new theories/ understand a phenomenon

Question 5

when is descriptive designs used?

Answer 5

In supplement/ conjunction with other methods

Question 6

Value neutrality

Answer 6

When descriptions are objective based on a singular reality
So any observer would reliably describe it the same way

Question 7

Episteic virtues

Answer 7

Scepticism
Uncertainty

Question 8

Correlational designs

Answer 8

Identifying patterns and associations between variables

Question 9

Correlations can be…

Answer 9

Descriptive of a relationship
Inferential to make predictions on what to assume in a wider context based on the data

Question 10

Induction inferences

Answer 10

If the sample is likely to exist in wider population

Question 11

Abduction

Answer 11

Explaining what relationship between variables could be caused by

Question 12

Why complete correlations?

Answer 12

Cannot run an experiment if it would be unethical or not feasible
But we can find a relationship betwee instinces that occurred in real life

Question 13

Why does correlation not imply causation?

Answer 13

Alternative explanations that mean 2 variables appear in relation to each other:
By chance
Unknown variables cause these

Question 14

Limitations of correlational research

Answer 14

Does not tell us about causality or directionality
Correlations can be confounded by other variables

Question 15

How can we ensure a correlation is valid?

Answer 15

Control for confounding variables

Question 16

Experimental designs aim

Answer 16

To establish a cause and effect relationship

Question 17

Steps of an experiment

Answer 17

Formulate a hypothesis
Test it - manipulate the IV at different levels
Measure any changes in the DV

Question 18

Confounding variable

Answer 18

A variable that varies with the changing IV at different levels that may impact the measured dependent variable

Question 19

What must true experiments require?

Answer 19

Manipulation of IV at different levels
Random assignment to groups
Comparison between grous
Control over external factors to keep things constant in all conditions

Question 20

Extraneous variables

Answer 20

Anything other than the independent variable that may affect the dependent variable

Question 21

Levels of the independent variable

Answer 21

At different values the IV is manipulated throughout at different conditions to measure how DV varies with changing IV

Question 22

Strengths of experimental design

Answer 22

Allows us to statistically work out likelihood of observing differences because everything is quantified
Identify causal relationships
Infer to wider population (make generalisation)
Allows for study replication

Question 23

Control group

Answer 23

A condition in which the IV is not manipulated to find a baseline measure we can compare experimental conditions too

Question 24

Limitations of experiments

Answer 24

Unethical to manipulate certain variables
Artificial lab environments means results lack ecologival validity
Uknown extraneous/ confounding variables we have not been able to control for may affect DV
Can never be certain the only difference between conditions is what we manipulated - human error or randomisation causes error?????
Reactivity effects - behaviour is impacted as result of knowing they are in a study

Question 25

Quasi experimental design

Answer 25

Lacks essential features: no control over variables, cannot randomly assign participants to groups Does not manipulate variables so is 'natural' e.g. studying the impact on the DV before and after something naturally occurred

Question 26

Do quasi experiments have self selecting samples?

Answer 26

Yes because if the IV is naturally occurring such as whether someone smokes or not, then no random assignment to conditions will occur- if a smoker, you will be in condition 1 for example

Question 27

Strengths of quasi experiment

Answer 27

Allows what could not feasibly be studied (cannot be manipulated) in an experiment A natural environment, has a more realistic impact on behaviour

Question 28

Limitations of quasi experiment

Answer 28

Lack of control over study Maybe not control confounding/ extraneous variables May not be able to replicate this