Karteikarten
Introduction to statistics
Karten in diesem Stapel (32)
- 1Statisticsinvolves studying facts that have been collected so we can learn about a group, object, or interest
- collected facts are called data - 2Descriptive Statisticsinvolves the collection, presentation, and description of the data
- may have calculations or graphical displays to communicate information about the data
- describes immediate data used in calculations - 3Inferential Statisticsprocess used to take information from descriptive statistics and interpret it so it allows us to draw conclusions or make decisions
- uses descriptive statistics from a sample to make inferences about the population - 4Populationcomplete collection of objects or individuals that are being studied
- 5Samplea subset of the population (section)
- good sample is a "representative" of the population - 6Variablesthings of interest that we wish to learn from our sample or the population
- ex. gender, age, height, and race - 7Datafacts we collect
- data may be numbers, a word, or a symbol - 8Parameterscalculations using data values that reflect the entire population
- 9Statisticperform a calculation using data from the sample
- can be frequencies, percentages, averages - 10Simple random sample (srs)sample selected by method where each combination of experimental units have an equal chance of being selected
ex. population is an order and number- then use a random number generator to select subjects for sample - 11Convenience samplesample is selected by taking members or objects of the population that are easiest to reach
- can lead to many errors
- only acceptable when there is reason to believe there isn't no systematic difference between sample and population - 12Stratified random samplingpopulation is divided into distinct subgroups or strata based on specific characteristics or attributes and a random sample is selected from each stratum
- each strata should differ from the other strata - 13Cluster samplingpopulation is divided into naturally occurring groups or clusters and a section of clusters is selected for inclusion in the sample
- commonly used in research and education - 14Systematic sampleimportant to start at a random point in the population
ex. choosing every 25th student - 15Voluntary response sampleindividual volunteer to participate or opinion
- never reliable - 16Data setcollection of data that we gather from our sample
- 17Variablescharacteristics or information that we collect
- 18Qualitative variables or categorical variablesinvolve what the name implies, qualities or categories
- usually response that allow us to sort the data into groups or categories - 19Ordinal variablesdata can be sorted into distinct groups or categories
- have an order or ranking - 20Nominal variablesdata can be sorted into specific groups or categories
- no specific order or hierarchy
ex. male, female, non-binary - 21Identifier variablecategorical variable with one observation in each category (ssn)
- 22Quantitative variablesprovide information about the amount or quantity of a particular attribute or characteristic being measured
- should be some units associated with type of data
ex. height, age, weight
- can be divided into two categories: discrete and continuous - 23Discrete variablequantitative variable consisting of countable values (usually whole numbers)
- values can be easily listed or enumerated - 24Continuous variablequantitative variable with an uncountable number of possible values
- can take on any value within a given interval - 25Sampling error or sampling variabilitysample-to-sample differences will occur in each sample
- different means, median, variances - 26Sampling biasdesign of statistical study is biased if it favors certain outcomes (if it shows fair representation, then it's unbiased)
- 27Voluntary response biasleave it to the individual to choose to respond (website, text)
- 28Self interest biasconducted by someone with a vested interest in the outcome
- 29Social acceptability biaspeople may not respond honestly if they fear of being judged
- 30leading question biasconfusing or leading questions can influence answers given
- 31Nonresponse biaslot of your sample doesn't respond, missing group who share the same opinion
- 32Sampling biaswhen some members of the population are more likely to be included that others ( can lead to undercovering- some subpopulation is either not sampled at all or not adequately represented)
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- Mathematics Karteikarten am Introduction to statistics , erstellt von Chloe Hallengren am 25/09/2023.
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- Chloe Hallengren
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