Chapter 1: Nature of Probability vocab

Question 1

statistics

Answer 1

is the science of conducting studies to collect, organize,summarize, analyze, and draw conclusions from data.

Question 2

A variable

Answer 2

Is a characteristic or attribute that can assume different values (measurements or observations).
- Examples: customer names, amount of daily sales, favorite tv programs.

Question 3

Random variable

Answer 3

determined by chance. Ex: roll a dice, toss a coin

Question 4

data

Answer 4

values, measurements or observations that variables can assume.
Measurement: height of customer, circumference of a tree
Observation: hair color, # of shirts on a rack

Question 5

Descriptive Statistics

Answer 5

Collection, OrganizatIon, Summarization, and Presentation of data. NO CONCLUSIONS DRAWN.

Question 6

Inferential Statistics

Answer 6

Using probability to make predictions and DRAW CONCLUSIONS. Generalizing from samples to populations.

Question 7

Sample

Answer 7

A group of SOME subjects selected from population.

Question 8

Population

Answer 8

ALL subjects of interest being studied. humans, animals, business ethics, products. difficult due to expense or time.

Question 9

Quantitative variables

Answer 9

Numerical that can be ranked or ordered.

Ex: temperature, age, weights. classified in 2 groups: discrete and continuous.

Question 10

Discrete

Answer 10

Assume values that can be counted.

Ex: # of people in household, # of eggs needed for a recipe, # of chairs on a table.

Question 11

Continuous

Answer 11

Assume an infinite number of values in an interval between any specific values. 4 feet maybe recorded as (3.5 - 4.5). Ex: temperature, weight of a book.

Question 12

Qualitative variables

Answer 12

Categorical, described.

Ex: eye color, gender, location and satisfaction rankings.

Question 13

Qualitative and Quantitative can also be classified in 4 common types which are:

Answer 13

Nominal, Ordinal, Interval and Ratio

Question 14

Nominal

Answer 14

Lowest level of measurement. Qualitative. No meaningful order or rank.
Ex: Zip codes, address, social security

Question 15

Ordinal

Answer 15

Second level of measruremnet. Qualitative. CAN be ordered and ranked.
Ex: Stisfaction ratings, football team rankings, clothing sizes.

Question 16

Interval

Answer 16

Third level of measurement. Quantitavtive. CAN be ranked and ordered, have precise differences between unit measurement, NO meaningful zero.
Ex: Fahrenheit, calendar years, time of day.

Question 17

Ratio

Answer 17

Highest level of measurement. Quantitative. MEANINGFUL zero.
Ex: GPA, weight, years of work experience

Question 18

Data

Answer 18

Most common form of collection is surveys.

Question 19

Random Sampling

Answer 19

Using chace method or random numbers.

Ex: flip a coin, lotteries.

Question 20

Systematic Sampling

Answer 20

Numbering each subject of population and choosing every 4th subject. first subject is random then every 4th.

Question 21

Stratified Sampling

Answer 21

Dividing population into groups and random sample is taken from each group. SOME OF ALL

Question 22

Cluster Sampling

Answer 22

Population is divided into groups, once groups are deteremined a few groups are randomly selected and everyone in that chosen group become subjects. ALL OF SOME.

Question 23

Convenience Sampling

Answer 23

Consists of subjects that are available and easy to find. results are biased, or flawed. NOT the best for pilot studies.

Question 24

Sampling Error

Answer 24

The difference between the results obtained from a sample and the results obtained from the population from which the sample is collected.

Question 25

Nonsampling Error

Answer 25

Occurs when the data are obtained incorrectly or sample is biased or nonrespresentative.

Question 26

Observational Studies

Answer 26

Researchers observe what is happening or what has happened in the past and draw conclusions based on the observation.

Question 27

Experimental Studies

Answer 27

The researcher manipulates one of the variables of interest.

Question 28

Independent/ Explanatory Variables

Answer 28

being manipulated.

Question 29

Dependent Variables

Answer 29

being measured.