Stats 330 Exam 1 Feb 20 Flashcards
Statistics
a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.
Population
the complete collection of all elements to be measured
Sample
a sub collection of elements drawn from a population
Statistic
a numerical measurement describing some characteristic of a sample
Quantitative Data
consists of numbers representing counts or measurements
Qualitative Data
aka categorical. can be separated into diff categories that are distinguished by some nonnumeric characteristic
variable
a characteristic or attribute that can assume different values
random variables
variables whose values are determined by chance
discrete data
result from either a finite number of possible values or a countable number of possible values
continuous data
result from infinitely many possible values that can be associated w/points on a continuous scale in such a way that there are no gaps or interruptions
Sampling Error
the difference between a sample result and the true population result
Frequency Table
lists categories or classes of scores, along with counts (or frequencies) of the number of scores that fall into each category
Class Width
Range/ # of classes
Cumulative Frequency
the sum of the frequencies for that class and all previous classes
Relative Frequency
Class Frequency/ sum of all frequencies
Stem and Leaf Plot
Data is sorted according to a pattern that reveals the distribution (shape), also can see original data set.
Mean
The sum of all the data values divided by the total number of data values
Median
The middle value when data are arranged in numerical order.
Mode
The value in a data set that occurs most frequently
Skewed Data
Data that is not symmetric and extends more to one side than the other.
Skewed Left
Mean to left of median (Mean < Median)
Skewed Right
Mean to right of median (Mean > Median)
Symmetrical Distribution
Mean and Median are equal
Variation
the amount that scores vary among themselves
Variance
average of squares of the distance each value is from the mean
Standard Deviation
square root of the variance