Want this question answered?

Be notified when an answer is posted

Add your answer:

Earn +20 pts
Q: What does tails stand for in a graph?
Write your answer...
Still have questions?
magnify glass
Related questions

What does tails for a graph stand for?

It stands for Title, Axis, Intervals, Labels, and Scale. Hope this helped!

What are the TAILS of a graph?

title,axis,interval,label and scale

What does geo and graph stand for in Latin?

Graph is to write in Latin

What POS Equipment will keep track of sales in a graph for me?

Tails euipment is known to handle all your tracking needs including into graph.

How do outliers influence the shape and spread of the data?

Outliers will make give the graph a long tail (or tails). Overall, the graph will be flatter and wider.

What does the 'a' stand for in dogs tails?

The 'A' stands for 'Author' (who made the map).

What do the numbers on the bottom of the graph stand for?

The numbers on the bottom of a graph usually represent which vertical line you're on. (there are some exceptions)

What is a bar chart used for?

A bar chart is a term for bar graph. A bar graph is a graph that has rectangular bars with different lengths representing what they stand for. They are used to compare categorical data.

In a formula for a parabola what do h and k stand for?

In the formula for calculating a parabola the letters h and k stand for the location of the vertex of the parabola. The h is the horizontal place of the vertex on a graph and the k is the vertical place on a graph.

What does TAILS stand for in the metric system?

T itleA xisI ntervalsL abelS cale

How do American saddlebreds tails stand so tall?

It is natural for them to lift up there tails. But saddlebreds trainers but tail sets on them. At shows they use what is call a tail brace

What does SALT stand for on a graph?

SALT on a graph stands for "Sensitivity Analysis Limited By Technology." It is a measure of how uncertain a model's predictions are influenced by changes in input parameters. A higher SALT value indicates the model's output is more sensitive to changes in input parameters.