Topic 1: Design of Experiments

Question 1

Why is data important?

Answer 1

Use data for problem-solving

Question 2

How many types of data scientist?

Answer 2

2: Professional and popular

Question 3

What is different between professional and popular data scientist?

Answer 3

Professional data scientist is able to explore and work on different aspects of data life cycle

Popular data scientist works on dataset from a particular field, data detective

Question 4

What are challenges with collecting dataset?
How to minimize?

Answer 4

Ethics, privacy, errors, missing values
Transparent plan and non-identifible subjects

Question 5

What is the gold standard to gather data?

Answer 5

Randomised controlled trial (RCT)
random double-blinded allocation

Question 6

What is domain knowledge?

Answer 6

Domain knowledge is the context background information needed to analyse and understand the dataset

Question 7

During the process of gathering information or data, the evidence must be….

Answer 7

• Each piece of evidence needs to be weighed up equally
• Clear and well-cited
• Every stage of the study in research journal must be well-documented
• Journals needs to be reproducible research

Question 8

What is reproducible research?

Answer 8

The author of the study needs to present data set and software used in the study for further verifying and altenative analyses

Question 9

How many types of controlled experiments are there?

Answer 9

2: Contemporaneous (happens at the same time with the treatment grouop)
Historical (happens before the treatment group)

Question 10

What is placebo?

Answer 10

A pretend treatment, designed to be neutral and indistinguishable from the treatment

The participants in double-blinded trial don’t know whether they are receiving the real or placebo treatment

Question 11

What is placebo effect?

Answer 11

A phenomenon in which the subjects/receivers think they are having the treatment and responses to the idea

Question 12

What is confounding?

Answer 12

when the results/effects get mixed up/become misleading because of a 3rd extraneous variable
=> confusing intepretation

Question 13

What is bias?

Answer 13

A factor affecting the ablity of the data to precisely measure the effect of the treatment

Question 14

What are some confounders with RCT?
Explain each one

Answer 14

Selector bias: the 2 groups are not comparable

Observer bias: subjects/ investigators are aware of the identity of the 2 groups/the study ==> affects responses and evaluations + placebo effect

Consent bias: the subjects choose whether to join or not

Question 15

What is observational study?

Answer 15

The investigator does NOT decide or allocate the subjects into groups

Question 16

What results can be conveyed from observational study?

Answer 16

Observational study can only SUGGEST causation using suggestive verbs (link, increase the risks, risk factors,…), NOT PROVE causation

Question 17

What are lurking variables in observational studies?

Answer 17

Various misleading hidden confounders
- Selection bias

• Survivor bias: worst subjects dropout of the study => improvement of the effects
• Adherers/non-adherers: the pattern can be due to whether the subjects adhere to the treatment/program or not rather than the treatment itself

Question 18

What is a solution to minimize the confounders?

Answer 18

Slicing up the groups into subgroups based on the confounders in order to be able to compare the results

Question 19

What is Simpson’s paradox?

Answer 19

A phenomenon in which patterns/trends can be observed in individual data sets but will disappear or reverse when combining all groups together.
The percentages in subgroups are different when combining the subgroups.

Question 20

If a study involves a data set from the past, what is it called?

Answer 20

Historical control in which time will become a confounding variable

Question 21

What is a control group?

Answer 21

A group in a study that receives the placebo treatment

Question 22

What is a controlled experiment?

Answer 22

Investigators allocate subjects into 2 groups: control and treatment group
The effects of the variable/treatment is controlled

Question 23

What is controlling for confounders?

Answer 23

By dividing up the groups into subgroups based on confounders, the influence of those variables can be reduced

Question 24

What is the actual difference between RCT and observational studies?

Answer 24

In RCT, the investigator is the one allocating each participants into control/treatment group. This means that there is already intervention or manipulation to the variable being studied.

Meanwhile, in observational study, the investigator observes/studies the participants who are already exposed to the independent variable (eg: pp who already smoke since we cannot force pp into treatment group in which they have to start smoking) ==> No intervention