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Fundamentals of Statistics III Sullivan Chapter 1

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Answer
statistics   The science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. In addition, statistics is about providing a measure of confidence in any conclusions.  
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data   Facts or propositions used to draw a conclusion or make a decision. The list of observed values for a variable.  
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anecdotal   the information being conveyed is based on casual observation, not scientific research  
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population   the entire group of individuals to be studied  
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individual   a person or object that is a member of the population being studied  
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sample   a subset of the population that is being studied  
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statistic   a numerical summary of a sample  
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descriptive statistics   Consist of organizing and summarizing data. Describe data through numerical summaries, tables, and graphs.  
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inferential statistics   Uses methods that take a result from a sample, extend it to the population, and measure the reliability of the result. One goal is to estimate parameters.  
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parameter   a numerical summary of a population  
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the process of statistics   1. Identify the research objective 2. Collect the data needed to answer the question(s) posed in step 1 3. Describe the data 4. Perform inference  
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convenience samples   Samples obtained through convenience rather than systematically, i.e. Internet or phone-in polls. Not based on randomness. Not considered reliable.  
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variables   the characteristics of the individuals within the population  
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qualitative variables   allow for classification of individuals based on some attribute or characteristic - sometimes called categorical variables  
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quantitative variables   Provide numerical measures of individuals. Math operations such as addition and subtraction can be performed on the values of a quantitative variable and will provide meaningful results.  
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approach   a way to look at and organize a problem so that it can be solved.  
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discrete variable   A quantitative variable that has either a finite number of possible values or a countable number of possible values. The values result from counting.  
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continuous variable   A quantitative variable that has an infinite number of possible values that are not countable, but are instead measured.  
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Qualitative data   Observations corresponding to a qualitative variable.  
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Quantitative data   Observations corresponding to a quantitative variable.  
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Discrete data   Observations corresponding to a discrete variable  
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Continuous data   Observations corresponding to a continuous variable.  
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nominal level of measurement   The values of a variable name, label, or categorize. The naming scheme does not allow for the values of the variable to be arranged in a ranked or specific order.  
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ordinal level of measurement   The variable has the properties of the nominal level of measurement and the naming scheme allows for the values of the variable to be arranged in a ranked or specific order.  
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interval level of measurement   The variable has the properties of the ordinal level of measurement and the differences in the values of the variable have meaning. Zero does not mean the absence of the quantity. Addition and subtraction can be performed on values of the variable.  
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ratio level of measurement   the variable has the properties of the interval level of measurement and the ratios of the values of the variable have meaning. Zero means the absence of quantity. Multiplication and division can be performed on values of the variable.  
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Four levels of measurement of a variable   1. nominal 2. ordinal 3. interval 4. ratio  
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observational study   Measure the value of response variable w/out trying to influence the value of the response or explanatory variables. Researcher observes behavior of individuals in the study w/out trying to influence outcome. Association may be claimed but not causation.  
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designed experiment   An experiment where the researcher assigns the individuals in a study to a certain group, intentionally changes the value of an explanatory variable, then records the value of the response variable for each group.  
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explanatory variable   a variable that explains or causes changes in the response variable - sometimes called the predictor variable  
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response variable   a variable that measures an outcome or result of a study (variable whose changes are to be studied)  
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confounding   Occurs when the effects of two or more explanatory variables are not separated, so any change in the response variable may be due to a variable that was not accounted for in the study.  
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lurking variable   An explanatory variable that was not considered in a study, but that affects the value of the response variable in the study. Lurking variables are typically related to explanatory variables considered in the study.  
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three categories of observational studies   1. cross-sectional studies 2. case-control studies 3. cohort studies  
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cross-sectional studies   Observational studies that collect information about individuals at a specific point in time or over a very short period of time.  
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case-control studies   Retrospective studies that require individuals to look back in time or require the researcher to examine existing records. Individuals that have a certain characteristic are matched with those that do not.  
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cohort studies   Group of individuals participates in study (the cohort). Cohort observed over time. Characteristics @ individuals are recorded. Some individuals exposed to certain factors; others are not. At study end, value of response value is recorded for individuals.  
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census   a list of all individuals in a population along with certain characteristics of each individual  
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random sampling   the process of using chance to select individuals from a population to be included in the sample  
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simple random sampling   every possible sample of size n from a population of size N has an equally likely chance of occurring  
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frame   lists all the individuals in a population  
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stratified sample   Obtained by separating the population into non-overlapping groups called strata and then obtaining a simple random sample from each stratum. The individuals within each stratum should be homogeneous in some way.  
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systematic sample   Obtained by selecting every kth individual from the population. The first individual selected corresponds to a random number between 1 and k.  
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cluster sample   Obtained by selecting all individuals within a randomly selected collection or group of individuals  
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bias   the results of the sample are not representative of the population  
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nonsampling errors   Errors that result from undercoverage, nonresponse bias, response bias, or data entry error. May be present in a complete census of the population.  
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sampling error   Error that results from using a sample to estimate information about a population. Occurs because a sample gives incomplete information about a population.  
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