Introduction to Inferential Statistics and Data Types

Question 1

Inferential Methods:

Accepted Answer

Techniques used to make inferences orconclusions about a large group of objectsBASED on the observation of only a small partof the groupWhen the interpretation of the data includesconclusions & predictions

Question 2

Population

Accepted Answer

Group of objects about which conclusions are to be drawn

Question 3

Sample

Accepted Answer

Portion (subset) of objects drawn from the population

Question 4

Random variable

Accepted Answer

Variable whose value is determined by the outcome of some chance experiment

Question 5

Continuous random variable

Accepted Answer

A random variable that PRIOR TO THE EXPERIMENT can conceivably assume any value in some interval or continuous span of real numbers (not just integers)

Question 6

Discrete random variable

Accepted Answer

A random variable that assumes its values ONLY AT ISOLATED POINTS

Question 7

A Statistic

Accepted Answer

Descriptive measure associated with a random variable when the variable is considered only over the sample (value that describes some aspect of the sample)

Question 8

Population parameters

Accepted Answer

Descriptive measure associated with a random
variable when the variable is considered over
the entire population (value that describes
some aspect of the entire population)

Since they don't usually study the entire
population, the actual numerical values of
population parameters are seldom known.

Question 9

Qualitative Data

Accepted Answer

Categorical or attributeCategories are based on someNONNUMERICAL characteristics

Question 10

Quantitative Data

Accepted Answer

Numbers representing counts or measurements (may be paired data)

Question 11

Discrete data

Accepted Answer

result from a FINITE number of possible values or aCOUNTABLE # of possible values(when data representcounts)

Question 12

Continuous numerical data

Accepted Answer

result from INFINITELY many possible values associated withpoints on a CONTINUOUS SCALE in which there are NO GAPSor INTERUPTIONS

Question 13

NOMINAL

Accepted Answer

consists of names, labels or categories ONLY
The data CAN'T be arranged in an ORDERING scheme
and CAN'T be used for calculations
Examples:
Poll Responses: 45 Democrats, 80 Republicans, 90 Independents
Movie Genres: comedy, adventure, romance
Note: Even if you assign a number per category, those numbers lack
any real computational significance

Question 14

ORDINAL

Accepted Answer

data may be arranged in some orderbut DIFFERENCES between data values eitherCAN'T BE DETERMINED or are MEANINGLESSExample:Rating: 12 "good", 16 "better", 8 "best" stereo speakersMovie Ratings: 4 stars vs. 1 starEmployee Promotions: Michelle 3rd, Ed 7th, Matt 10thThe DATA CAN'T be used for calculations

Introduction to Inferential Statistics and Data Types

Inferential Methods:

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Term	Definition
Inferential Methods:	Techniques used to make inferences or conclusions about a large group of objects BASED on the observation of only a small part of the group When the interpretation of the data includes conclusions & predictions
Population	Group of objects about which conclusions are to be drawn
Sample	Portion (subset) of objects drawn from the population
Random variable	Variable whose value is determined by the outcome of some chance experiment
Continuous random variable	A random variable that PRIOR TO THE EXPERIMENT can conceivably assume any value in some interval or continuous span of real numbers (not just integers)
Discrete random variable	A random variable that assumes its values ONLY AT ISOLATED POINTS
A Statistic	Descriptive measure associated with a random variable when the variable is considered only over the sample (value that describes some aspect of the sample)
Population parameters	Descriptive measure associated with a random variable when the variable is considered over the entire population (value that describes some aspect of the entire population) Since they don't usually study the entire population, the actual numerical values of population parameters are seldom known.
Qualitative Data	Categorical or attribute Categories are based on some NONNUMERICAL characteristics
Quantitative Data	Numbers representing counts or measurements (may be paired data)
Discrete data	result from a FINITE number of possible values or a COUNTABLE # of possible values(when data represent counts)
Continuous numerical data	result from INFINITELY many possible values associated with points on a CONTINUOUS SCALE in which there are NO GAPS or INTERUPTIONS
NOMINAL	consists of names, labels or categories ONLY The data CAN'T be arranged in an ORDERING scheme and CAN'T be used for calculations Examples: Poll Responses: 45 Democrats, 80 Republicans, 90 Independents Movie Genres: comedy, adventure, romance Note: Even if you assign a number per category, those numbers lack any real computational significance
ORDINAL	data may be arranged in some order but DIFFERENCES between data values either CAN'T BE DETERMINED or are MEANINGLESS Example: Rating: 12 "good", 16 "better", 8 "best" stereo speakers Movie Ratings: 4 stars vs. 1 star Employee Promotions: Michelle 3rd, Ed 7th, Matt 10th The DATA CAN'T be used for calculations