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40 Cards in this Set

  • Front
  • Back
statistics
the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions.
Process of Statistics
1) Identify the research objective
2) Collect the information needed to answer the questions posed in (1)
3) Organize and summarize the information
4) Draw conclusions from the information
descriptive statistics
consists of organizing and summarizing the information collected
inferential statistics
uses methods that take results obtained from a sample, extends them to the population, and measures the reliability of the result.
qualitative variables
allow for the classification of individuals based on some attribute or characteristic
quantitative variables
provide numerical measures of individuals. Arithmetic operations such as addition and subtraction can be performed on the values of a quantitative variable ad will provide meaningful results.
discrete variable
is a quantitative variable that has either a finite number of possible values or a countable number of possible values. The term countable means that the values result from counting numbers.
continuos variable
is a quantitative variable that has an infinite number of possible values that are not countable.
experimental group
the group that gets the treatment
control group
the group that gets the placebo
census
a list of all individuals in a population along with certain characteristics of each individual
observational study
measures of characteristics of a population by studying individuals in a smaple, but does not attempt to manipulate or influence the variable(s) of interest. Can only claim there is association, never causation.
designed experiment
applies a treatment to individuals and attempts to isolate the effects of the treatment on a response variable.
lurking variables
A lurking variable is a variable that has an important effect on the relationship among the variables in a study but is not included among the variables studied.
simple random sampling
a sample of size n from a population of size N is obtained through simple random sampling if every possible sample of size n has an equally likely chance of occurring. Like taking names out of a hat.
frame
a list of all the individuals within the population
stratified sample
obtained by separating the population into nonoverlapping groups called strata and then obtaining a simple random sample from each stratum. The individuals within each stratum should be homogeneous (or similar) in some way. (ex: dividing a constituency in Democrat, Republican, or Independent strata)
systematic sample
obtained by selecting every kth individual from the population. The first individual selected corresponds to a random number between 1 and k. Doesn't require a frame, so it is useful when you can't obtain a list of the individuals in the population that you wish to study. (ex: selecting every 5th person out of a line at Wendy's) (k may equal N/desired n)
cluster sample
obtained by selecting all individuals within randomly selected collection or group of individuals. If the clusters have homogenous individuals, it is better to have more clusters with fewer individuals in each cluster. When the clusters are more heterogenous, fewer clusters with more individuals in each cluster are appropriate. (ex: city blocks can be clusters)
convenience sample
a sample in which the individuals are easily obtained. the participants are self-selected. (ex: questionnaire online or phoning in an opinion)
non-sampling errors
errors that result from the survey process. They are due to the nonresponse of individuals selected to be in the survey, to inaccurate responses, to poorly worded questions, to bias in the selection of individuals to be given the survey, and so on.
sampling errors
errors that result from using sampling to estimate information regarding a population. This type of error occurs because a sample gives incomplete information about the population.
underrepresentation
(non-sampling error) in which the frame for the sample is not complete, and some sections of the population end up being underrepresented in the study
nonresponse
an individual selected for the sample does not respond to the survey.
interviewer error
when information is not given to the interviewer accurately because of something about the interviewer - how they ask the question, what gender or race they are, and so on.
misrepresented answers
when those answering the surveys lie
questionnaire design
when the design of the survey itself illicits a certain response from the participants.
designed experiment
controlled study conducted to determine the effect that varying one or more explanatory variables has on a response variable. Control, manipulation, randomization, and replication are the key ingredients designed experiment
explanatory variable
independent variable, the control variable. (ex: amount of sleep participants are allowed to have)
response variable
dependent variable (ex: the participant's reaction time to a stimulus after a certain number of hours of sleep)
process of conducting an experiment
1) identify the problem to be solved
2) determine the factors that affect the response variable
3) determine the number of experimental units
4) determine the level of each factor: control, manipulate, and randomize
5) conduct the experiment
6) test the claim - inferential statistics
completely randomized design
one in which each experimental unit is randomly assigned to a treatment
matched-pairs design
an experimental design in which the experimental units are paired up. the pairs are matched up so that they are somehow related (that is, same person before and after the treatment, twins, husband and wife, same geographical location, and so on). One individual receives one treatment, and the other receives a different one.
experimental unit
is a person, object, or some other well-defined item to which a treatment is applied
double-blind experiment
neither the experimental unit nor the experimenter knows what treatment is being administered to the experimental unit.. Important so that patients and researchers don't behave in a way that affects the results.
bar graph
frequency or relative frequency, rectangles are of equal width, separate bars. Each bar has its own category.
histogram
bars done per class of data, rectangles touch each other.
skewed left/right
skewed left - tail to the left
skewed right - tail to the right
Steps in Designing an Experiment (6)
1) Identify the problem to be solved
2) Determine the factors that affect the response variable
3) Determine the number of experimental units
4) Determine the level of each factor (control, manipulate, randomize)
5) Conduct the experiment
6) Test the claim - make generalizations about a population on the basis of the results
residual
= observed y - predicted y