Zusammenfassung der Ressource
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What is a population?
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A subset of a large group of people
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A large group of observations (people, objects etc.) about which a researcher wants to draw conclusions
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The number of people in a country
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The number of people that comprise a demographic
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What does descriptive statistics do?
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Make leaps and conclusions about a population from sample data
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Describe the data in a meaningful way
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Explain formulae, the theory behind the statistics
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Compress and condense raw data in the world into a workable size
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What are inferential statistics
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A tool to predict the sample based on population data
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A tool to draw inferences about a population from sample data
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A way to compress and consolidate sample data
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A way to estimate and make decisions about sample statistics
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What are the two inferential procedures
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Hypothesis testing and extrapolating
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Estimation and interpolating
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Estimation and hypothesis testing
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Hypothesis testing and determining limitations
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What is a confidence interval?
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How likely a particular value or set of values is in the given data
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An estimation of the confidence results are significant
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An estimation of the area that encompasses a particular value
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A tool to define a prediction, i.e. is it true or not
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What is hypothesis testing?
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How likely a particular value or set of values is in the given data
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A way to test if the hypothesis can be applied to the entire population
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A way to test if the hypothesis is valid
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A tool to define a prediction regarding a statement about the population parameter, i.e. is it true or not
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What is the sampling distribution?
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A hypothetical distribution of values of a particular population parameter made by repeatedly sampling "n" times from a sample and calculating the value of the statistic for each sample
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A hypothetical distribution of values of a particular sample statistic made by repeatedly sampling "n" times from a population and calculating the value of the population parameter for each sample
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A hypothetical distribution of values of a particular sample statistic made by repeatedly sampling "n" times from a population and calculating the value of the statistic for each sample
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The standard error of the mean only refers to the [blank_start]experiment[blank_end] [blank_start]that you are doing now[blank_end], i.e. the behaviour of the averages collected [blank_start]in the experiment[blank_end], while the variance is the noise in the [blank_start]population[blank_end].
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experiment
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population
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sample
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that you are doing now
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parameter
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statistic
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that you did previously
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in the experiment
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for the population
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in a previous experiment
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populations
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experiments
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samples
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sampling distributions
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M is the unbiased estimate of μ
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[blank_start]Variability[blank_end] tells you how much you can trust your [blank_start]experiment[blank_end]
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As 'n' gets larger, you get a better estimate of the [blank_start]true population mean[blank_end].
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Decreasing standard deviation makes the σ²M more spread out, and pulls data away from the population mean.