Chapter 1 - Defining and Collecting Flashcards
What are the two major categories to classify variables, and how do they differ?
Qualitative / Categorical - variables take categories as their values
Quantitative / Numerical - variables have values represented by a countable or measurable quantity
What is another term for a qualitative variable and provide an example
Categorical
Eye color - blue, brown, or green
What is a quantitative variable, what is another term used to describe a quantitative variable, and what are the two types of quantitative variables?
A quantitative variable has values represented by a countable or measurable quantity
Another term used for quantitative is numerical
When a quantitative/numerical variable is countable to a finite number it is considered DISCRETE
When a quantitative/numerical variable is measurable it is considered CONTINUOUS
What is a discrete variable and provide a sample
A discrete variable is a quantitative / numerical variable that is obtained by COUNTING finite rational numbers
How many texts you send in a day is a finite number
How many steps you took yesterday is a finite number
How many hours you studied last week is a finite number
What is a continuous variable and provide an example
A continuous variable is a quantitative / numerical variable that is obtained by MEASURING
It can be an infinite number within a range
The weight of students in a class (not counted but measured on a scale)
What is a data population?
Consists of all the items or individuals you want to draw a conclusion about
What is a data sample?
The portion of a population selected for analysis
What is a primary source of data?
The data collector is the one using the data. They are in charge of gathering and explaining the data collected
What is a secondary source of data?
A person analyzing data previously gathered. This is where Econ analysis lives.
What are they two categories of sampling, and what are their differences?
Non-Probability - items are chosen without regard to probability of occurrence
Probability - Items are chosen based on the known probabilities
What are they two types of non-probability sampling, and how do they differ?
Judgment - getting the opinions of pre-selected experts within the subject matter
Convenience - items are selected only on the fact that they are easy, inexpensive, or convenient to sample
What are the four types of probability sampling, and how do they differ?
Simple Random - every individual or item has an equal opportunity to be selected
Systematic - population is divided by the sample size to select the individuals or items
Stratified - population is divided into strata based on like characteristics
Cluster - population is divided into clusters representative of the population
What is the underlying issue when using a Random or Systematic sample, and how can you ensure it is as accurate as possible?
It may not be a good representation of the population’s underlying characteristics.
Gathering a large Random or Systematic sample ensures the sampling is representative of the overall population (or as close as possible)
What is the major benefit of a Stratified sample when comparing it to other sampling options?
It ensures the representation of individuals across the entire population
When considering Simple Random Sampling with replacement, what happens to your observations, what happens to your probability of being selected, and are your variables dependent or independent of each other, explain?
There is a possibility to repeat observations
The probability of being chosen remains the same each time a new variable is selected
The variables are independent of each other. because the previous selection, when replaced, has no effect on the next selections probability.