Coaching Centre
Time series and bivariate data
Time-series graphs, trend and seasonal patterns, bivariate data, explanatory and response variables, scatter plots and describing correlation by direction, form and strength.
Time series
A time series is data recorded over time, graphed with time on the horizontal axis. Look for a trend (overall rise or fall) and seasonal patterns that repeat.
Bivariate data
Bivariate data has two variables per item. The explanatory (independent) variable goes on the $x$-axis; the response (dependent) variable on the $y$-axis.
Hours of study and test score have points rising tightly from left to right. Describe the relationship.
Hours of study vs test score (points rise tightly). Describe it.
Rising and close to a line.
Car age vs resale value usually shows:
Older cars are worth less.
Shoe size vs maths score shows:
No connection.
In "temperature vs ice-cream sales", the explanatory variable is:
Temperature drives sales.
Electricity use is high every winter and low every summer. This is:
It repeats each year.
Ice-cream sales and sunburn cases are strongly correlated. This means:
Correlation is not causation.
Points scattered widely but trending slightly upward show:
Upward but loose.
On a time-series graph, time goes on the:
Time is the explanatory variable.
New numbers every time. Keep going until you get five in a row.