Gloassary
Analysis of covariance:
See ANCOVA.
Analysis of covariance:
See ANCOVA.
Analysis of variance:
See ANOVA.
ANCOVA:
Analysis of covariance. ANOVA with the addition of a second or third covariate.
ANOVA:
Analysis of variance. Using an F-ratio to test the fit of a linear model.
ascending:
A sorting order. The values range in order from small to large. See also descending.
autoscript:
A script that executes automatically in response to the output of certain data. See also script.
average:
The result of adding several values and then dividing by the number of values. See also mean and mode.
base:
The main system of SPSS. Modules can be added to expand SPSS, but the base system is always present.
BASIC:
See script.
binning:
The process of dividing the values of a variable into groups. Each group is a range of values and can be thought of as being sorted into its own bin. This is also called clustering.
bivariate:
Two variables.
break variable:
When organizing data into tabular form, the break variable is used to group the information. At the point in the report where the break variable changes value, a subtotal line is generated, or a new page is started, or some other break appears in the report.
case:
Any single group (or row) of constant values. All the values in a single row. It is also called a single record.
case summary:
A simple table that directly summarizes values from the cases.
categorical variable:
A type of variable that can take on only one of a specific set of values, such as year of birth, make of car, or favorite color. See also scale, ordinal, nominal, dichotomy, and binning.
category:
A possible value of a categorical variable.
chart:
See graph.
clustering:
See binning.
coefficient of determination:
A statistic used to determine the correctness of the fit of regression coefficients.
command language:
See Syntax.
confidence interval:
A range around an average into which a specified percentage of the values appears. For example, if gravel trucks for a company deliver an average of 190 loads per month, but 95% of the trucks deliver between 183 and 194 loads, the 95% confidence interval ranges from a low of 7 below to a high of 4 above.
constant:
A number. See also variable.
correlation:
The degree of similarity or difference between two variables.
covariance:
A comparison of the variance of one set of values with that of another.
covariate:
A variable that takes part in the prediction of an outcome. An independent variable in regression. It is secondary to the relationship of the main independent variable.
cutpoint:
A number used as a divider to split values into groups, as in binning.
data set:
The data displayed in the Data Editor window, whether you loaded it from a file, entered it from the keyboard, or both. Multiple data sets can be loaded and will appear in separate windows. They will be labeled DataSet1, DataSet2, and so on.
degrees of freedom:
The minimum number of values that must be specified to determine all the data points. This number is usually one less than the number of values used in the calculation.
delimiter:
A character used to indicate the beginning of, ending of, or separation between individual values in a series of strings of characters. For example, the string of characters 59,21,34 is a series of comma-delimited numbers.
dependent variable:
A variable that is compared against one or more other variables. Also called a predicted variable. See also independent variable.
descending:
A sorting order. The values range in order from large to small.
deviation:
The amount by which a measurement differs from some fixed value.
dichotomy:
A variable with only two possible values, such as yes/no, true/false, or like/dislike. It is a specific type of categorical variable. See also categorical variable.
dodging:
Plotting points on a graph so they appear next to one another instead of one of top of the other.
error:
Two kinds of errors exist in the world of statistics. The conventional kind comes about when you do something wrong and get a bogus result. The other kind is calculated — that is, you figure the amount of error present in the results you get from the data you have. With modern survey techniques, you will often hear the term “margin of error” for this second type.
faceting:
See paneling.
F-ratio:
A comparison of the variance of unexpected values with the variance of expected values.
frequency distribution:
The collection of values that a variable takes in a sample.
geoset:
A file containing map information in a format that can be used for display and annotation by SPSS.
GLM:
General Linear Model. A general procedure for analyzing variance, covariance, and regression.
graph:
A non-numeric display of values. The terms graph and chart are used in SPSS internal documentation almost interchangeably.
GUI:
Graphical user interface. Control of an application with windows and a mouse.
histogram:
A graphical display of a distribution in which the extent of each rectangle represents the magnitude (as in a bar chart) and the width of each rectangle represents the magnitude of the bin. The area of each rectangle thus represents the frequency.
hoc:
See post hoc.
independent variable:
A variable whose values are used as the basis of a comparison. See also dependent variable.
kurtosis:
A measure of the peakedness of the bell curve. A positive number indicates more of a peak than standard; a negative number indicates flatness of the line.
Levene test:
A test to determine whether the variance of two groups is significantly different or significantly the same.
linear:
A straight line. No curves.
mean:
- Another word for average.
- A calculated value equally distant from the two extreme values.
- The temperament of the person making you learn this stuff. See also average and mode.
missing data:
If you declare a value for a variable as representing the fact that no value is present, the missing value will not be included in calculations.
mode:
The value that occurs most frequently in a given set of data. See also average and mean.
module:
A utility that can be added to SPSS.
multiple response set:
A special variable that has its content generated from the content of two or more other variables. In SPSS, it doesn’t appear in the Data View (in the Data Editor window), but does appears when you select variable names for other activities.
multivariate:
Multiple variables.
nominal:
Numbers that specify categories are nominal. For example, yes, no, and undecided could be represented by 2, 1, and 0. See also scale, ordinal, and categorical.
nonlinear:
Not in a straight line. Curved.
OLAP cubes:
Online Analytical Processing cubes. A multilevel table containing totals, means, or some other statistic in which each level of the table contains the values relating to one value of a categorical variable.
Online analytical processing:
See OLAP.
ordinal:
Types of numbers that specify the order of occurrences. In English, the ordinal forms of 1, 2, and 3 are first, second, and third. See also scale, nominal, and categorical.
outliers:
The extreme values of a variable. Generally, they are the five largest and five smallest values.
paneling:
Adding another dimension of data to a graphic display causing the layout to be replicated a number of times to accommodate the values of the data along the new dimension. This process is also known as faceting.
Pearson’s Product Moment Correlation:
Commonly call Pearson’s correlation. It represents the degree of linear relationship between two variables.
periodicity:
The interval of repetition at which data recordings are made.
pivot table:
A table with names identifying the rows and columns. Swapping the rows and columns to make the table appear in a different form, but containing the same data, is known as pivoting the table. The tables in SPSS Viewer are pivot tables.
post hoc:
Cause and effect — some condition arises as the result of a previous condition.
p-p plot:
A proportion-proportion plot. The observed cumulative proportion is plotted against the expected cumulative proportion.
predicted variable:
See dependent variable.
probit:
A nonlinear function of probability.
pyramid:
A special form of a histogram where the bars representing the value extend to the sides from a center line. It often assumes the shape of a pyramid.
Python:
A general-purpose programming language that can also be used to program SPSS internal operations.
q-q plot:
A quantile-quantile plot. The quantiles of the observed values are plotted against the quantiles of a specified distribution.
quantiles:
A set of values chosen to divide a sampling of data into groups, each containing (as far as possible) an equal number of values.
quartile:
Specific values that divide all the values into four groups, with an equal number of values in each group. The groups are generally called the first, second, third, and fourth quartiles.
R:
See coefficient of determination.
recoding:
The conversion of a set of values to a new set of values. For example, if you have yes/no coded as 0/1, you can recode the values to 1/2.
record:
Any single collection of values for the variables defined in SPSS. A record is all the values of a single row. It is a single case or row.
regression:
Determining the “best fit” equation for the relationship between two variables. See also dependent variable and independent variable.
row:
Any single collection of values for the variables defined in SPSS. It appears as a single row in the Data View window. It is a single case.
scale:
A type of number that uses a standard by which something is measured, such as inches, pounds, dollars, or hours. See also ordinal, nominal, and categorical.
script:
A program written in the BASIC language. It is different than Syntax and Python.
skewness:
A measure of the unevenness of the distribution of data. Positive skewness indicates more high values, while negative skewness indicates more low values.
SPSS:
Statistical Package for the Social Sciences.
standard deviation:
A calculated indicator of the extent of deviation for a specific collection of data. The value is derived from the variations when the points are compared to a standard bell-shaped curve. It is the square root of the variance.
standard error:
A measurement of the magnitude of the change from one sample to the next.
statistic:
A single number calculated in a specific way. Some examples of types of a statistics are sum, mean, deviation, and average.
statistics:
A collection of statistical values.
string:
A series of characters making up a name or even a complete sentence. Quite often the beginning and ending of a string is delimited by quotes.
Syntax:
The name of the programming language fundamental to SPSS. All actions performed by SPSS are in response to the internal interpretation of Syntax commands. In the SPSS documentation, Syntax is sometimes referred to as the command language.
t:
The number of degrees of freedom. A continuous distribution with density symmetrical around the null value and a bell-shaped curve.
thematic map:
A geographical map as displayed by SPSS listing statistical data for each named area.
univariate:
A statistic derived from the values of one variable. Examples are mean, standard deviation, and sum.
variable:
A place to store constants. A variable can store a number of constants (one for each case). Each case (or row) in SPSS consists of a collection of constant values assigned to variables.
variance:
The average of the differences between a set of measured values and a set of expected values on a standard bell-shaped curve. It is the square of the standard deviation.
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