Marketing Research Spring Test 5 Set 2

Front 1

a consistent and systematic linkage between the levels or lavels for two variables.

Back 1

relationship

Front 2

two variables are shown simultaneously in the same bar graph. each bar stands for 100%

Back 2

stacked bar chart

Front 3

the analytical technique that assesses the statistical significance of Boolean or categorical varible relationships is

Back 3

cross tabulation analysis

Front 4

contains the raw counts of the various boolean relationships found in the complete data set.

Back 4

frequencies table

Front 5

an index number, constrained to fall between the range of -1.0 and +1.0, that communicates both the strength and the direction of the linear relationship between two metric variables

Back 5

correlation coefficient

Front 6

correlation coefficient's deal with what type of variables?

Back 6

metric

Front 7

correlation coefficient indicates the degree of -------- between two variables

Back 7

covariation

Front 8

defined as the amount of change in one variable systematically associated with a chang in another variable.

Back 8

covaration

Front 9

the greater the absolute size of the correlation coefficient, the greater is the -------------------------, or the stronger is their relationship regardless of sign

Back 9

covariation between two variables

Front 10

used to illustrate covariation. plots data pairs in an x and y axis graph

Back 10

scatter diagram

Front 11

the variable that is predicted and is customarily termed y in the regression straight-line equation.

Back 11

dependent variable

Front 12

the one that is used to predict the dependent variable, that is the x in the regression formula.

Back 12

independent variable

Front 13

What methods of doing business are associated with level of customer satisfaction?
What demographic variables are associated with repeat buying of Brand A?
Is type of sales training associated with sales performance of sales representatives?
Are purchase intention scores of a new product associated with actual sales of the product?

Back 13

examples of relationships

Front 14

describe each unit of the property being measured.

Back 14

descriptors

Front 15

When the scale is metric, descriptors measure ----- of the property – levels of temperature, levels of satisfaction, etc.

Back 15

levels

Front 16

When the scale is categorical, the descriptors measure ------ of the properties – buyer versus non-buyer; yes, no; etc.

Back 16

labels

Front 17

is a consistent and systematic linkage between the levels (for metric scales variables) or labels (for categorical scaled variables) for two variables.

Back 17

a relationship

Front 18

Knowledge of relationships between variables can give marketers -------- ------- into phenomena in the marketplace.

Back 18

advantageous insights

Front 19

is the analytical technique that assesses the statistical significance of Boolean or categorical variable relationships.

Back 19

A cross-tabulation analysis

Front 20

the two variables are arranged in a cross-tabulation table in a row-and-column format.

Back 20

cross tabulation

Front 21

is the intersection of a row and a column.

Back 21

a cross tabulation cell