STATISTICAL RELATIONSHIPS INTERPRETATION
SCRIPT 2026 COMPLETE SOLUTION
◉ Causation vs. Correlation. Answer: Correlation:
- Is a measure of the strength of linear association between two
variables
- Is always between −1.0 and +1.0
- Can be positive or negative
Can be proven by observational study
Causation:
- Is a demonstrable cause and effect
- Can be measured by controlled studies or experiments
- Should not be assumed even when correlation is strong and
predictable
- Cannot be proven by observational study alone
◉ Causation or Correlation?
A student notices she gets better grades on tests when she goes to
bed at 9 p.m. instead of 10 p.m.. Answer: Correlation. Although it
, may be true that getting more sleep helps this student do better on
tests, without a controlled study we cannot be sure.
◉ Causation or Correlation?
A tennis player notices she wins more games in the evening than in
the afternoon.. Answer: Correlation. The player isn't attributing her
better scores to anything at this point, just making a correlation.
◉ Independent variable. Answer: The experimental factor that is
manipulated; the variable whose effect is being studied.
◉ Dependent variable. Answer: The outcome factor; the variable
that may change in response to manipulations of the independent
variable.
◉ Using Table and Graphs to Show Correlation
- Equation. Answer: Strengths:
- Easy to find the exact values of the independent and dependent
variables.
- Easy to update the equation if changes happen in the scenario.
- Easy to make a table of values.