Please choose the most appropriate answer for each sentence.

1

Dr. Hossein Arsham of the University of Baltimore explains that in this diverse world of ours, no two things are exactly the same, and a statistician is interested in both the differences and the similarities; i.e., both ..... and patterns.

departures

detractions

disorders

distractions

Dr. Hossein Arsham of the University of Baltimore explains that in this diverse world of ours, no two things are exactly the same, and a statistician is interested in both the differences and the similarities; i.e., both ..... and patterns.
(*) departures(*) detractions(*) disorders(*) distractions

2

The ..... tables published by insurance companies reflect their statistical analysis of the average life expectancy of men and women at any given age.

actuarial

calculation

demogogic

graduated

The ..... tables published by insurance companies reflect their statistical analysis of the average life expectancy of men and women at any given age.
(*) actuarial(*) calculation(*) demogogic(*) graduated

3

From these numbers, the insurance companies then calculate the appropriate ..... for a particular individual to purchase a given amount of insurance.

charges

fees

gratuities

premiums

From these numbers, the insurance companies then calculate the appropriate ..... for a particular individual to purchase a given amount of insurance.
(*) charges(*) fees(*) gratuities(*) premiums

4

The more widely used descriptive statistical techniques are: Frequency Distribution, ....., Boxplot, Scattergrams and Error Bar plots, and diagnostic plots.

Histograms

Holograms

Picograms

Pictograms

The more widely used descriptive statistical techniques are: Frequency Distribution, ....., Boxplot, Scattergrams and Error Bar plots, and diagnostic plots.
(*) Histograms(*) Holograms(*) Picograms(*) Pictograms

5

In examining distribution of data, you should be able to detect important characteristics, such as shape, location, variability, and unusual values, and from careful observations of patterns in data, you can generate ..... about relationships among variables.

conjectures

conjunctions

junctures

juxtapositions

In examining distribution of data, you should be able to detect important characteristics, such as shape, location, variability, and unusual values, and from careful observations of patterns in data, you can generate ..... about relationships among variables.
(*) conjectures(*) conjunctions(*) junctures(*) juxtapositions

6

The notion of how one variable may be associated with another ..... almost all of statistics, from simple comparisons of proportions through linear regression.

penetrates

peregrinates

permeates

permutates

The notion of how one variable may be associated with another ..... almost all of statistics, from simple comparisons of proportions through linear regression.
(*) penetrates(*) peregrinates(*) permeates(*) permutates

7

From the data collection plan, a statistical model can be formulated from which inferences can be ......

drawn

implied

penned

sketched

From the data collection plan, a statistical model can be formulated from which inferences can be ......
(*) drawn(*) implied(*) penned(*) sketched

8

As an example of statistical modeling with managerial implications, such as 'what-if' analysis, ..... regression analysis.

acknowledge

consider

ponder

regard

As an example of statistical modeling with managerial implications, such as 'what-if' analysis, ..... regression analysis.
(*) acknowledge(*) consider(*) ponder(*) regard

9

Frequently, for example, the marketing managers are faced with the question, 'What sample size do I need?' - this is an important and common statistical decision, which should be given ..... attention, since an inadequate sample size invariably leads to wasted resources.

all

apt

due

long

Frequently, for example, the marketing managers are faced with the question, 'What sample size do I need?' - this is an important and common statistical decision, which should be given ..... attention, since an inadequate sample size invariably leads to wasted resources.
(*) all(*) apt(*) due(*) long

10

Your organization database contains a wealth of information, yet the decision technology group members can usually ..... only a fraction of it.

tap

taste

tell

try

Your organization database contains a wealth of information, yet the decision technology group members can usually ..... only a fraction of it.
(*) tap(*) taste(*) tell(*) try

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