Introduction to Statistics Flashcards
What are Statistics?
Statistics are numbers used to communicate a piece of information
What is Statistics?
The science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions.
List the types of statistics
Descriptive and Inferential
Define Descriptive Statistics.
The method of organizing, summarizing and presenting data in an informative way
What is Inferential Statistics?
The method used to estimate the property of a population in a sample
What are the 2 types of variables
Qualitative and Quantitative
What are the types of Quantitative variables
Discrete and Continuous
What is Discrete Variable?
These are values and variables that are in whole numbers e.g. age, number of houses etc.
What is Continuous variable?
These are values and variables that are unlimited and can be in between two definite values e.g. GPA, temperature,
List the 4 levels of measurement
Nominal, Ordinal, Interval and Ratio level data
What is Nominal level-data?
(Name-Only) The nominal scale simply categorizes variables according to qualitative labels (or names). These labels and groupings don’t have any order or hierarchy to them, nor do they convey any numerical value. For example, the variable “hair color” could be measured on a nominal scale according to the following categories: blonde hair, brown hair, gray hair, and so on
What is Ordinal level-data?
(Hierarchical) categorizes variables into labeled groups, and these categories have an order or hierarchy to them. For example, you could measure the variable “income” on an ordinal scale as follows: low income, medium income, high income. Another example could be level of education, classified as follows: high school, master’s degree, doctorate. These are still qualitative labels (as with the nominal scale), but you can see that they follow a hierarchical order.
What is Interval level-data?
(Evenly spaced intervals) numerical scale which labels and orders variables, with a known, evenly spaced interval between each of the values. An oft-cited example of interval data is temperature in Fahrenheit, where the difference between 10 and 20 degrees Fahrenheit is exactly the same as the difference between, say, 50 and 60 degrees Fahrenheit.
What is Ratio level-data?
(true zero) is exactly the same as the interval scale, with one key difference: The ratio scale has what’s known as a “true zero.” A good example of ratio data is weight in kilograms. If something weighs zero kilograms, it truly weighs nothing—compared to temperature (interval data), where a value of zero degrees doesn’t mean there is “no temperature,”
