# DATA TABLES AND GRAPHS

## 28 terms

### DATA TABLE

* visual representation of data
* arranged in columns & rows
I.V. listed 1st, D.V. follows I.V.

### GRAPH

* visual representation of data
* represented as series of plotted points, bars, or pieces of a circle
* types = line, bar, pie
* I.V. goes on x-axis
* D.V. goes on y-axis
* shows relationship btwn I.V. & D.V.

### TITLE

* contains I.V. & D.V.
* Format = The Effect of I.V. on D.V.

### LABELS

* identify the I.V. or D.V.

### UNITS

* indicate what has been measured
* abbreviated
* come after the label
* ex = cm, mm, mg, L, etc.

### INTERVALS

* on a graph =
- the difference between the numbered lines on the x or y axis on a graph
- usually indicate how often & to what degree I.V. is changed
- typically changed in consistent amounts (ex. = by 2's, 5's, 10's, etc.)
* on a data table = how the independent variable has been changed

### TRIALS

* number of times 1 value of the I.V. is has been tested
* should be numbered in the table
* use minimum of 3

### SCALE

* numerical value of each grid-line on x and/or y axis
* formula: range / # of grid-lines

### ATTRIBUTE

* characteristic represented by I.V. or D.V.
* qualitative or quantitative

### CORRELATION

* when one variable influences/or is associated w/ another
*shows possible cause-effect relationship
* it is positive, negative or there is none
* strong = plotted points line up closely
* weak = plotted points are highly scattered
* stronger the correlation = more confidence in predictions using line of best fit

### LINE OF BEST FIT

* Used to:
- show relationship btwn I.V. & D.V.
- show general trend of data
- make predictions
- make sense of data
* straight line or smooth curve
* passes as close to as many data pts as possible/doesn't have to touch all pts. (splits the data set)

### POSITIVE CORRELATION

* as one variable goes up - the other goes up
* ex. - +correlation btwn height & arm length --> as height increase, arm length increases

### NEGATIVE CORRELATION

* as one variable goes up - the other goes down
* ex. - neg. correlation btwn north latitude & temperature--> as N. latitude increases, average temps decrease

### NO CORRELATION

* no relationship btwn I.V. & D.V.
* ex - no corrrelation btwn height and I.Q. - knowing how tall people are doesn't tell us anything about how intelligent they are

### RANGE

* high # in data set - low # in data set for one variable
* needed to help determine scale

### PIE GRAPH

* displays data given as %
* shows how whole is divided into parts
* sum of wedges = 100%
* I.V. = what each wedge represents
* D.V. = the size of wedge

### BAR GRAPH

* uses bars to represent data
* shows how # of objects of one thing compares to a single characteristic
* determines trends in data
* one variable is qualitative

### LINE GRAPH

* shows relationships btwn variables
* both sets of data are quantitative
* I.V. = x-axis
* D.V. = y-axis,

### X-AXIS

* horizontal axis
* I.V.

### ROW

* horizontal in table
* runs side to side / left to right

### COLUMN

* vertical in table
* runs up & down
* 1st column in table = I.V.

* vertical axis
* D.V.

### EXTRAPOLATION

* making estimates using a line of best fit
* estimate is for data falling outside the data set

### INTERPOLATION

* making estimates using line of best fit
* estimate is for data falling inside the data set

### D.R.Y.

* acronym to remember what goes on the y-axis
D = Dependent Variable
R = Responding Variable
Y = y - axis

### M.I.X.

* acronym to remember what goes on the x-axis
M = Manipulated Variable
I = Independent Variable
X = x-axis

### KEY

* used to identify what a line, bar or slice of pie chart means on a graph that has more than one

### BROKEN LINE GRAPH

* graph created by "connecting the dots" after plotting them, thus often creating a line with "breaks" or bends in it