Exam 1 Flashcards
Controlled experiment
An experiment that is conducted under controlled conditions in which one or two factors are changed at a time to determine if a relationship exists between variables
Treatment Group
Group that receives the treatment in the experiment
Control Group
The group that goes not receive the treatment.
Population
The set of all subjects and elements about which we are interested in making inferences
Frame
A list containing all members of the population is referred to as the frame
Census
A survey that includes all the elements or units in the frame
Population Parameters
Facts about the population. Since parameters are descriptions of the population, a population can have many parameters
Sample
A subset of the population which is used to gain insight about the population. Samples are used to represent a larger group of the population
Process
A series of actions that changes inputs to outputs
Descriptive statistics
-frequency distribution
-mean, median, mode
-range, variance, standard deviation
Inferential statistics
To make reasonable estimates about population characteristics using sample data
Confounding variable
A variable that was not controlled or accounted for by the researcher and thus damaged the integrity of the experiment
Double blind study
A study in which the subjects are not told whether they are members of the experiment group or the control group and the evaluators are also not told whether their subject are members of the experiment or control group is called a double blind study
Casual factors
Factors or variables that influence the response variable
Big data
Any data that can be characterized by any or all of the following characteristics: volume, velocity, variety, and veracity
Structured data
Highly organized, has labels, and fits in spreadsheet cells, such as each cell in the sheet is of an identifiable format called structured data
Unstructured data
Data that does not have a predictable organization
Semi-structured data
Data that is a combination of both structured and unstructured data
Analytics
The science of examining raw data to draw conclusions about information contained in the data is called analytics
Predictive analytics
Uses past data to develop models that can help determine what future events are most likely to happen
Prescriptive Analytics
The development of models that help us answer the question “What should we do moving forward”
Qualitative data
Measurements that can change in kind, but not in degree, qualitative measurements often consist of labels or descriptions and do not have naturally occurring numerical values
Quantitative Data
Measurements that change in magnitude from trial to trial such that some order or ranking can be applied. Quantitative variables can be measured using naturally occurring numerical scale
Discrete Data
Data in which the observations are restricted to a set of variables (such as 1,2,3,4) that possesses gaps are discrete
Continuous data
Data that can take on any value within some interval are continuous
Nominal data
Data that represents whether a variable possesses some characteristics
Ordinal data
Represents categories that have some associated order
Very bad
Bad
Fair
Good
Very good
Interval data
If that data can be ordered and the arithmetic differences are meaningful
48 degrees-45 degrees =3
72 degrees-69 degrees=3
Ratio Data
Similar to interval data, except they have a meaningful zero point and the ratio of two data points in meaningful
Time series data
Measurements taken from a process over equally spaced intervals of time
Stationary process
The time series varies around some central value and has approximately the same variation over the series
Nonstationary process
The time series processes a trend-the series either increases over time or decreases over time
Cross sectional data
Measurements created approximately the same period of time
Frequency distribution
Summarizes data into classes and provides in tabular form a list of the classes along with the number of observations in each class
Relative Frequency Distribution
Summarizes data into classes and provides in tabular form a list of the classes along with the proportion or percentage of observations in each class
Cumulative Frequency
The sum of the frequency of a particular class and all preceding classes
Cumulative relative frequency
Is the proportion of observation in a particular class and all preceding classes
Relative frequency equation
Number in class
——————————————
Total number of observations
Histogram
Bar graph of a frequency in which the height of each bar corresponds to the frequency or relative frequency of each class
Symmetric distribution
A distribution in which if a vertical line were drawn down the middle of the distribution, the two sides would mirror each other
Skewed distribution
If a vertical line were drawn down the middle of the distribution, it would have a long tail to the right or left
Stem and leaf display
A hybrid graphical method in which the raw data is used both order and detect patterns in the data. Each data value is broken into two parts a “stem” and a “leaf”
Ordered array
A listing of a data set in either increasing or decreasing order of magnitude
Rank order
Data listed in increasing order are said to be listed in rank order
Reverse rank order
Data listed in decreasing order are said to be listed in
