Chapter 1: Intro to Stats Flashcards
What are Statistics?
Statistics are used to predict important outcomes and make decisions about many things in your everyday life
Population
The entire group of individuals
Sample
The smaller group selected from the population
Variable
Characteristic or condition that can change or take on different values
Data
The measurements obtained in a research study
Relationship between the population and sample
The sample is selected from the population and the results are generalized to the population (populations are often too large to sample– it’s rare to even know their size)
Descriptive statistics
- Methods for organizing, summarizing, and simplifying data
- Familiar examples: tables, graphs, averages
Parameter
descriptive value for a population
Statistic
a descriptive value for a sample
Inferential Statistics
- Methods for using sample data to make general conclusions (inferences) about the population
- Interprets experimental data
Sampling Error
The discrepancy between a sample statistic and its population parameter
Discrete Variables
indivisible categories, each unit is the smallest it can be
Ex. Fruit types
Continuous Variables
infinitely divisible into whatever units a researcher may choose. They can be broken into small units
Ex. weight
Real limits of continuous variables
Boundaries of each interval representing scores measured on a continuous number line
Upper real limit
Marks the top of the interval
Lower real limit
Marks the bottom of the interval
Nominal scale
an unordered set of categories identified only by name. Nominal measurements only permit you to determine whether two individuals are the same or different
Ex. gender identity
Ordinal scale
a set of ordered categories. Ordinal measurements tell you the direction of difference between two individuals
Ex. high school vs bachelor’s degree vs. PhD
Interval scale
an ordered series of equal-sized categories. Interval measurements identify the direction and magnitude of a difference. The zero point is located arbitrarily on an interval scale
Zero doesn’t mean NONE
ex. Temperature
Ratio scale
an interval scale where a value of zero indicates none of the variables. Ratio measurements identify the direction and magnitude of differences and allow ratio comparisons of measurements.
Ex. time
Order of Operations
Brackets
Squaring/exponents
Multiplying/dividing
Summation with the ∑ notation
Adding/subtracting
Summing a set of values
∑
Experiment
one variable is manipulated to create treatment conditions, while a second variable is observed and measured to obtain scores for a group of individuals in each of the treatment conditions
The measurements are then compared to see if there are differences between treatment conditions
Independent Variable
the manipulated variable
Dependent Variable
the observed variable
Non-experimental/quasi-experimental
Do not use a manipulated variable to differentiate the groups. Instead, differentiate variables using pre-existing variables
x and y
The individual measurements obtained for a research participant
N
The number of scores in a population
n
the number of scores in a sample
