Computer 9th Chap 4 : Topic 2.13 - Maryam Publications

Computer Chapter 4 : Topic 2.13

Variable Relationships

1 / 9

In a dataset stored for analysis, what is the most accurate explanation of why a relationship between two variables may appear even when no real causal link exists in real-world context?

A) The variables always determine each other directly in every dataset

B) The relationship may appear due to coincidence, hidden variables, or sampling bias

C) The relationship must always be caused by measurement errors only

D) The relationship only exists when data is collected manually

2 / 9

When analyzing two variables in a dataset, which situation best indicates that no meaningful relationship exists between them?

A) Changes in one variable show no consistent pattern in relation to the other

B) Both variables are measured using the same unit

C) One variable directly controls the values of the other

D) Both variables increase together consistently in all observations

3 / 9

Why might two variables show a strong correlation in data analysis but still not have a causal relationship?

A) Because both variables may be influenced by a third hidden factor

B) Because graphs automatically create false relationships

C) Because statistical tools remove all real-world meaning

D) Because correlation always guarantees causation in datasets

4 / 9

In a classroom dataset, students notice that higher ice cream sales are linked with higher drowning cases. What is the most reasonable explanation?

A) Drowning causes people to eat ice cream

B) The dataset must be incorrect and unusable

C) A third factor like hot weather influences both variables

D) Ice cream causes drowning directly

5 / 9

Which statement best explains why relationships between variables must be interpreted carefully in data science?

A) Variables in datasets never interact in real life

B) Every correlation found in data is scientifically proven

C) Data always reflects perfect real-world causation

D) Relationships may be influenced by randomness or external factors

6 / 9

When a dataset shows no relationship between study time and exam scores, what is a logical explanation?

A) Study time always guarantees high scores

B) Students may use different study methods or have varying abilities

C) Data visualization always hides true relationships

D) Exam scores are unrelated to any human factor

7 / 9

What is the most likely reason for an observed relationship that disappears when more data is collected?

A) Initial dataset was too small and not representative

B) Graphing tools removed the relationship

C) Data collection always destroys patterns

D) The variables stopped interacting over time

8 / 9

Why is it dangerous to assume causation from correlation in data analysis?

A) Because it may lead to incorrect conclusions and decisions

B) Because correlation automatically proves a mathematical error

C) Because all correlations are random

D) Because datasets cannot contain relationships

9 / 9

In which situation is a “no relationship” conclusion most valid?

A) Both variables form a straight line pattern

B) One variable increases steadily while the other decreases

C) Both variables are measured in percentages

D) Data points are randomly scattered with no visible trend in a scatter plot

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