,MIP2602 ASSIGNMENT 2 2026
DUE DATE: 25 MAY 2026
QUESTION 1:
1.1 Population and sample (Eastern Cape context)
In this study, the population refers to all possible individuals or observations within the
Eastern Cape region (or a similar defined Eastern Cape context such as all learners,
commuters, or participants being studied) from which the data could have been drawn.
In statistical terms, the population is the full group of interest about which conclusions
are intended. In this case, since no restriction is explicitly given, the population can be
understood as all individuals in the Eastern Cape whose travel distance, coin usage,
and favourite colour preferences could be measured under similar conditions.
The sample is the actual set of observations provided in the dataset. It consists of 19
recorded entries, each representing one individual or unit of analysis with values for
distance (km), number of coins, and favourite colour. This sample is a subset of the
broader Eastern Cape population and is used to make inferences about the larger group
(Eastern Cape residents or participants) (Field, 2018).
1.2 Three variables in the dataset
The dataset contains the following three variables:
, 1. Distance (km): This represents the distance travelled in kilometres by each
individual or unit in the study. It is a measurable quantity showing how far each
participant moved or travelled.
2. Coins: This represents the number of coins associated with each individual
observation. It is a count variable indicating frequency or quantity of coins per
person.
3. Favourite colour: This represents the preferred colour of each individual. It
reflects personal preference and is recorded as a descriptive category such as
black, blue, brown, grey, red, green, or white.
These variables collectively describe behavioural (distance), quantitative count (coins),
and preference-based (colour) characteristics of the dataset.
1.3 Classification of variables (qualitative/quantitative and categorical/numerical)
Distance (km):
Distance is a quantitative variable because it is expressed in numerical form and can
be measured meaningfully. It is also numerical (continuous) because it can
theoretically take any value within a range (e.g., 7 km, 7.5 km, etc.), even though only
whole numbers appear in the dataset. Its numerical nature allows for arithmetic
operations such as addition and averaging (Triola, 2019).
Coins:
Coins is a quantitative variable and specifically numerical (discrete) because it
represents a count of objects. It can only take whole number values (e.g., 0, 1, 2, 3), and
fractions of coins are not meaningful in this context. This makes it a discrete numerical
variable since it is countable rather than continuous.
DUE DATE: 25 MAY 2026
QUESTION 1:
1.1 Population and sample (Eastern Cape context)
In this study, the population refers to all possible individuals or observations within the
Eastern Cape region (or a similar defined Eastern Cape context such as all learners,
commuters, or participants being studied) from which the data could have been drawn.
In statistical terms, the population is the full group of interest about which conclusions
are intended. In this case, since no restriction is explicitly given, the population can be
understood as all individuals in the Eastern Cape whose travel distance, coin usage,
and favourite colour preferences could be measured under similar conditions.
The sample is the actual set of observations provided in the dataset. It consists of 19
recorded entries, each representing one individual or unit of analysis with values for
distance (km), number of coins, and favourite colour. This sample is a subset of the
broader Eastern Cape population and is used to make inferences about the larger group
(Eastern Cape residents or participants) (Field, 2018).
1.2 Three variables in the dataset
The dataset contains the following three variables:
, 1. Distance (km): This represents the distance travelled in kilometres by each
individual or unit in the study. It is a measurable quantity showing how far each
participant moved or travelled.
2. Coins: This represents the number of coins associated with each individual
observation. It is a count variable indicating frequency or quantity of coins per
person.
3. Favourite colour: This represents the preferred colour of each individual. It
reflects personal preference and is recorded as a descriptive category such as
black, blue, brown, grey, red, green, or white.
These variables collectively describe behavioural (distance), quantitative count (coins),
and preference-based (colour) characteristics of the dataset.
1.3 Classification of variables (qualitative/quantitative and categorical/numerical)
Distance (km):
Distance is a quantitative variable because it is expressed in numerical form and can
be measured meaningfully. It is also numerical (continuous) because it can
theoretically take any value within a range (e.g., 7 km, 7.5 km, etc.), even though only
whole numbers appear in the dataset. Its numerical nature allows for arithmetic
operations such as addition and averaging (Triola, 2019).
Coins:
Coins is a quantitative variable and specifically numerical (discrete) because it
represents a count of objects. It can only take whole number values (e.g., 0, 1, 2, 3), and
fractions of coins are not meaningful in this context. This makes it a discrete numerical
variable since it is countable rather than continuous.
