| ANOVA |
Short
for "Analysis of Variance," this is used
to tell you if at least two subgroups on a categorical
variable performed significantly different on a dependent
variable. This is one of EZAnalyze's Advanced functions.
|
| Area Chart |
A
graph that has a categorical variable on the X axis
and a summary number (mean, total number of people)
on the Y axis
|
| Axis - X axis |
The
bottom of a bar or area chart; shows you the levels
of the categorical variable you selected for the graph
|
| Axis - Y axis |
The
vertical side (left side) of a bar or area chart; displays
summary information (mean, total number of people)
|
| Bar Chart |
A
graph that has a categorical variable on the X axis
and a summary number (mean, total number of people)
on the Y axis
|
| Case |
A
row in EZAnalyze. Each case should contribute uniquely
to the EZAnalyze data set. For example, if you are
analyzing student data, each case would represent one
student. If you are analyzing school test scores statewide,
each case would be one school.
|
| Categorical variable |
A
variable that divides your data into groups. For example,
if you are looking at data for a High school, a good
categorical variable would be "grade level." Other
examples are gender, group (experimental vs. control)
and race
|
| Correlation |
A
number between negative 1 and positive 1 that indicates
the degree of relationship between two variables. The
direction of the relationship is indicated by the number
being negative or positive, while the strength of the
relationship is indicated by the number itself. For
example, -.88 would be a strong, negative correlation
|
| Dependent variable |
A
numeric variable that contains information you are
interested in. Test scores, number of days absent,
and number of behavioral referrals are good examples
of dependent variables
|
| Descriptive statistics |
Descriptive
statistics are a broad class of statistics used to
simply describe your results.
|
| Difference score |
A
difference score is a new variable that is the difference
between two other variables. Allows you to show changes
over time with one variable.
|
| Disaggregate |
Disaggregate means to sort something into categories. In EZAnalyze,
disaggregate means to sort your dependent variable
by your categorical variable
|
| Distribution of scores |
The
distribution of scores is the range of scores people
obtained on a variable, and how many people scored
in each category of the variable. For example, the
distribution of scores for a variable called gender
could be "65 males and 45 females"
|
| EZAnalyze |
A
fun software program that makes data analysis a snap!
|
| Frequency |
The
frequency is a simple count of how many times something
occurred. For example, if 55 people said "yes" to
a question, the frequency would be 55
|
| Maximum value |
The
highest number observed in your data for the given
variable
|
| Mean |
The
average score of all of the scores in a given range
of values
|
| Median |
The
middle occurring number if you laid all of your scores
out on a line. For example, the median of 0, 0, 1,
2, 3 is 1, and the median of 5, 5, 5, 5, 100, 111,
112, 113, 114 is 100.
|
| Minimum value |
The
lowest number observed in your data for the given variable
|
| Missing value |
A
number that is not present in your data, and is not
included in analyses
|
| Mode |
The
most frequently occurring number. For example, 3 is
the mode of 0, 1, 2, 3, 3 because there are more 3's
than any other number
|
| NTV |
A "Numeric
Test Value." Used to specify a known mean in the
one sample t-test.
|
| Numeric variable |
A
variable that contains "meaningful numbers".
For example, if you use the numbers 1 and 2 to represent
males and females in your data, "gender" would
not be a numeric variable (even though it contains
numbers). If you can get a mean score for the variable
that makes sense, then it is probably numeric. For
example, saying that "the average race in our
data was caucasian" does not make sense. Saying "the
average test score was 98" does make sense
|
| Percent |
Mathematically,
the number in a category divided by the total number
in all categories. Simply put, it is the proportion
of scores on a variable relative to the total number
of scores
|
| Percentages |
See Percent
|
| Pie Chart |
A
chart that displays the percent of people in each category.
Each slice of the pie represents a category, and the
percent of the total that each slice represents is
its size
|
| Results report |
A
chart or table that displays the results of an EZAnalyze
function
|
| Standard deviation |
How
far, on average, each score in your data deviates from
the mean. The larger the standard deviation, the farther
each person's score on average was different than the
mean
|
| String variable |
A
variable that contains letters. Can not be used as
a dependent variable
|
| T-Test, independent |
A
statistical hypothesis test used to indicate the degree
of difference between two group means. An EZAnalyze
Advanced function
|
| T-Test, one sample |
A
statistical hypothesis test used to indicate the degree
of difference between an observed sample mean and the
value of a known population mean. An EZAnalyze Advanced
function
|
| T-Test, paired |
A
statistical hypothesis test used to indicate the degree
of difference between two non-independent (paired)
means. An EZAnalyze advanced function
|
| Total score |
The
total of all selected data pieces added up
|
| Valid N |
The
number of people who had usable data for the selected
analysis
|
| Variable |
A column in EZAnalyze. More specifically, a variable
is something that can assume different values. The
variable "gender" can assume two values,
while the variable "gross income" could assume
a potentially infinite number of values
|
| X axis |
The
bottom of a bar or area chart; shows you the levels
of the categorical variable you selected for the graph
|
| Y axis |
The
vertical side (left side) of a bar or area chart; displays
summary information (mean, total number of people)
|
