M3 - modelling

Question 1

predictive models

Answer 1

refers to using mathematical or computer-
based models to make predictions about future events or
unknown outcomes based on existing data.

• These models analyse trends, patterns or relationships in data
  to forecast what is likely to happen under certain conditions.

Question 2

advantages of predictive modelling

Answer 2

supports decision making, cost effectice, fast results, improves with data

Question 3

Limitations of
Predictive Modelling

Answer 3

relies on assumptions, data quality matters, cant predict unexpected events, may oversimplyfy

Question 4

Statistical Models

Answer 4

a mathematical framework that represents
relationships between two variables using probabilities and data.

• These models help describe patterns in data, test hypotheses,
  and make inferences about a population from a sample.

Question 5

Advantages of Statistical
Modelling

Answer 5

data drive, can quantify uncertainty, applicable across disciplines, helps identify relationship

Question 6

Limitations of Statistical
Modelling

Answer 6

requires assumptions, sample bias affects validity, correlation does not equal causation, can be missed or misinterpreted

Question 7

Descriptive Models

Answer 7

where we summarise, organise and
simplify data to allow researchers to identify key patterns and
trends.
* They tell us a story about the data; however they do not allow
conclusions about cause and effect or allow us to make
predictions beyond the data.
* Includes Measurements of Central Tendency.
* Recall these calculations describe the typical or central value of a
dataset.

Question 8

Advantages of Descriptive
Modelling

Answer 8

simplifies data, helps identify trends, useful for comparison, highlights differences or similarities

Question 9

Limitations of Descriptive
Modelling

Answer 9

affected by outliers, doesnt show variability - does not tell us how spread out the data is, mode may not be useful, median is less information with small datasets

Question 10

Graphical Modelling

Answer 10

involves representing data visually to
identify patterns, trends and relationships, and outliers.

• It helps students move from raw data to interpretation and
  communication of results.