Frhd 3070 Ch.11

Front 1

Codebook

Back 1

A document that describes the procedure for coding variables and their location in a format for computers

Front 2

Code sheet

Back 2

Paper with a printed grid on which a researcher records info that can easily be entered into a computer. It is an alternative to the direct-entry method and using optical scan sheets

Front 3

Direct entry method

Back 3

A method of entering data into a computer by typing data without code or optical scan sheets

Front 4

Possible code cleaning

Back 4

Cleaning data using a computer in which the researcher looks for responses or answer categories that cannot have cases

Front 5

Contingency cleaning

Back 5

Cleaning data using a computer in which the researcher looks at the combination of categories for two variables for logically impossible cases

Front 6

Descriptive Statistics

Back 6

A General type of simple Statistics used by researchers to describe basic patterns in the data

Front 7

Univariate Statistics

Back 7

Statistical measures that deal with one variable only

Front 8

Frequency distribution

Back 8

A table that shows the distribution of cases into the categories of one variable (ex. The number or percent of cases in each category)

Front 9

Histogram

Back 9

A type of bar chart used to visually display the distribution of continuous variable

Front 10

Bar Chart

Back 10

A display of quantitative data for one variable in the form of rectangles. Usually used with discrete data

Front 11

Pie Chart

Back 11

A display of numerical info on one variable that divides a circle into fractions by lines representing proportions

Front 12

Mode

Back 12

A measure of central tendency for one variable that indicates the most frequent or common score

Front 13

Bimodal

Back 13

A distribution with two modes

Front 14

Multi model

Back 14

A distribution with more than one mode

Front 15

Median

Back 15

Measure of central tendency indicating the point which half the cases are higher and half are lower

Front 16

Possible code cleaning

Back 16

Cleaning data using a computer in which the researcher looks for responses or answer categories that cannot have cases

Front 17

Mean

Back 17

A measure of central tendency that indicates the arithmetic average (the sum of all scores divided by the total number of scores)

Front 18

Normal distribution

Back 18

A "bell shaped" frequency polygon for a distribution of cases with a peak in the centre and identical curving slopes on either side of the centre. It is the distribution of many naturally occurring phenomena.

Front 19

Skewed distribution

Back 19

Distribution of cases among the categories of a variable that is not normal (ex. Not a "bell shape"). Instead of an equal number of cases on both ends, more are at one of the extremes

Front 20

Range

Back 20

A measure of dispersion for one variable indicating the highest and lowest scores

Front 21

Percentile

Back 21

A measure of dispersion of one variable that indicates the percentage of cases at or below a score or point

Front 22

Standard deviation

Back 22

A measure of dispersion for one variable that indicates an average distance between the scores and the mean

Front 23

Z-Scores

Back 23

A way to locate a score in a distribution of scores by determining the number of standard deviations it is above or below the mean or arithmetic average

Front 24

Bivariate Statistics

Back 24

Statistically measures that involve two variables only

Front 25

Correlation

Back 25

The idea that two variables vary together, such that knowing the values in one variable provides information about values found in another variable

Front 26

Independence

Back 26

The absence I have a statistical relationship between two variables for example when knowing the values on one variable provides no information about the values that will be found on another variable. There's no association between them

Front 27

Scattergram

Back 27

A diagram to display the statistical relationship between two variables based on plotting each case values for both the variables

Front 28

Linear relationship

Back 28

An association between two variables that is positive or negative across the attributes and levels of the variables. When plotted the basic pattern of the associations form a straight line not a curve or pattern

Front 29

Curvilinear relationship

Back 29

A relationship between two variables such as the values of one variable increases the values of the second show a change in pattern it is not a linear relationship

Front 30

Precision

Back 30

The amount of spread in the point on the graph. A high level of precision occurs when the point hug the line that summarizes the relationship. A little level occurs when the points are widely spread around the line

Front 31

Cross Tabulation

Back 31

Placing data for two variables into a contingency table to show the number of percentage of cases at the intersection of categories of the two variables

Front 32

Contingency Table

Back 32

A table that shows the cross tabulation of two or more variables. But usually shows bivariate quantitative data for the variables in the form of percentages across rows or down columns of the categories of one variable

Front 33

Marginals

Back 33

The totals in a contingency table outside the body of a table

Front 34

Measure of Association

Back 34

A single number that expresses the strength and often in the direction of a relationship. It condenses information about a bivariate relationship into a single number

Front 35

Control variable

Back 35

A third variable that shows whether the bivariate relationship holds up to an alternative explanation. It can occur before or between other variables

Front 36

Partials

Back 36

In contingency tables for three variables table show the association between the independent and dependent variables for each category of a control variable

Front 37

Statistical significance

Back 37

A way to discuss the likelihood that a finding or statistically relationship in a sample is due to random factors rather than due to the existence of an actual relationship in the entire population

Front 38

Level of statistical significance

Back 38

A set of numbers researchers use as a simple way to measure the degree to which a statistical relationship results from random factors rather than existence of a true relationship among variables

Front 39

Type I error

Back 39

The logical error of falsely rejecting the null hypothesis

Front 40

Type II error

Back 40

The logical error of falsely accepting the null hypothesis