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Data151- Midterm #1

Study Guide for the first midterm of the Willamette Data 151 class

TermDefinition
Data observations collected in one way or another
Datum a single entry/element/instance of a very large data, the smallest possible part of the largest data you can think of
Observations an object/unit described by data
Variables any data item in an experiment
Numeric (Quantitative) a variable that can take a wide range of numerical values, and it is sensible to add, subtract, or take averages with those values
Categorical (Qualitive) types of data which may be divided into groups
Continuous data that can take any value
Discrete data that can only take whole non-negative numbers
Ordinal a categorical variable, but the levels have a natural ordering
Nominal a regular categorical variable without any type of special ordering
Level the possible values a variable can be
Binary data whose unit can take on only two possible states
Data Matrix (Data Frame) a convenient and common way to organize data
Tidy Data A data frame where each row is a unique case (observational unit), each column is a variable, and each cell is a single value
Big Data data that contains greater variety, arriving in increasing volumes and with more velocity
Volume the amount of data that exists
Variety the diversity of data types
Velocity the speed with which data is generated
Veracity the quality and accuracy of data
Population a distinct group of individuals with shared citizenship
Parameter a number that describes something about an entire population
Sample an analytic subset of a larger population
Statistic a fact or piece of data from a study of a large data size
Census the complete enumeration of a population or group at a point in time
Sampling Unit the building block of a data set; an individual member of the population, a cluster of members, or some other predefined unit
Sampling Frame a list of the items or people forming a population
Target Population the group of individuals that the intervention intends to conduct research in and draw conclusions from
Bias any sort of influence that may skew the outcome of the data
Biased Sampling occurs when some members of a population are systematically more likely to be selected in a sample than others
Undercoverage Bias when some groups in the population are left out of the process of choosing the sample
Nonresponse Bias when an individual chosen for the sample can't be contacted or refuses to participate
Response Bias when an individual does not answer honestly
Simple Random Sample most basic random sample; is equivalent to drawing names out of a hat to select cases
Stratified Random Sample a divide-and-conquer sampling strategy; the population is divided into groups called strata; the strata are chosen so that similar cases are grouped together, then a second sampling method, usually simple random sampling, is employed within each stratum
Cluster Sample break up the population into many groups, called clusters; then we sample a fixed number of clusters and include all observations from each of those clusters in the sample
Multistage Sample like a cluster sample, but rather than keeping all observations in each cluster, we would collect a random sample within each selected cluster
Convenience Sample whoever wants to answer can; individuals who are easily accessible are more likely to be included in the sample
Voluntary Sample researcher puts out a request for members of a population to join the sample, and people decide whether or not to be in the sample
Anecdotal Evidence Data collected with a haphazard fashion
Response Variable the variable one suspects is affected by the explanatory variable
Explanatory Variable the variable whose effect one wants to study
Observational Study observes individuals and measures variables of interest but does not attempt to influence
Experiment deliberately imposes some treatment on individuals to measure their response
Confounding Variable occurs when two variables associate in such a way that there effects on a response variable can't be distinguish from each other
Experimental Unit the smallest collection of individuals to which treatments are applied
Treatment a specific condition applied to the individuals in an experiment
Control may also be referred to as the "no treatment"
Randomization researchers randomize participants into treatment groups to account for variables that cannot be controlled
Replication being able to repeat an experiment or a part of it under the same or similar conditions
Blocking Researchers sometimes know or suspect that variables, other than the treatment, influence the response, they may first group individuals based on this variable into blocks and then randomize cases within each block to the treatment groups.
Placebo Effect to give a fake treatment to patients in the control group
Blinding only the researcher is aware of which group each participant belongs to
Double Blinding where doctors or researchers who interact with patients are, just like the patients, unaware of who is or is not receiving the treatment
Completely Randomized Design where the treatments are assigned completely at random so that each experimental unit has the same chance of receiving any one treatment
Randomized Complete Block Design each block size is the same and is equal to the number of treatments
Matched Pairs Design an experimental design where participants are matched in pairs based on shared characteristics before they are assigned to groups
Console a computer terminal where a user may input commands and view output such as the results
Script a series of Analytics commands that are executed sequentially and used to automate work within Analytics
Global Environment consists of multifaceted factors that affect a business's operation, and the business has no control over them
Variable Environment a user-definable value that can affect the way running processes will behave on a computer
Vectors a tuple of one or more values called scalars
Permutation the number of ways to arrange items/objects given in a list taken, some or all at a time, in a specific order
Created by: DoubleDeckard
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