Chapter 1: Nature of Probability vocab Flashcards
statistics
is the science of conducting studies to collect, organize,summarize, analyze, and draw conclusions from data.
A variable
Is a characteristic or attribute that can assume different values (measurements or observations).
- Examples: customer names, amount of daily sales, favorite tv programs.
Random variable
determined by chance. Ex: roll a dice, toss a coin
data
values, measurements or observations that variables can assume.
Measurement: height of customer, circumference of a tree
Observation: hair color, # of shirts on a rack
Descriptive Statistics
Collection, OrganizatIon, Summarization, and Presentation of data. NO CONCLUSIONS DRAWN.
Inferential Statistics
Using probability to make predictions and DRAW CONCLUSIONS. Generalizing from samples to populations.
Sample
A group of SOME subjects selected from population.
Population
ALL subjects of interest being studied. humans, animals, business ethics, products. difficult due to expense or time.
Quantitative variables
Numerical that can be ranked or ordered.
Ex: temperature, age, weights. classified in 2 groups: discrete and continuous.
Discrete
Assume values that can be counted.
Ex: # of people in household, # of eggs needed for a recipe, # of chairs on a table.
Continuous
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.
Qualitative variables
Categorical, described.
Ex: eye color, gender, location and satisfaction rankings.
Qualitative and Quantitative can also be classified in 4 common types which are:
Nominal, Ordinal, Interval and Ratio
Nominal
Lowest level of measurement. Qualitative. No meaningful order or rank.
Ex: Zip codes, address, social security
Ordinal
Second level of measruremnet. Qualitative. CAN be ordered and ranked.
Ex: Stisfaction ratings, football team rankings, clothing sizes.
Interval
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.
Ratio
Highest level of measurement. Quantitative. MEANINGFUL zero.
Ex: GPA, weight, years of work experience
Data
Most common form of collection is surveys.
Random Sampling
Using chace method or random numbers.
Ex: flip a coin, lotteries.
Systematic Sampling
Numbering each subject of population and choosing every 4th subject. first subject is random then every 4th.
Stratified Sampling
Dividing population into groups and random sample is taken from each group. SOME OF ALL
Cluster Sampling
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.
Convenience Sampling
Consists of subjects that are available and easy to find. results are biased, or flawed. NOT the best for pilot studies.
Sampling Error
The difference between the results obtained from a sample and the results obtained from the population from which the sample is collected.
