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Lesson 4-5

Eva Bonning 14 Fragen

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  1. 1A population is a [blank_start]set[blank_end] of [blank_start]all[blank_end] [blank_start]possible[blank_end] [blank_start]values[blank_end]. The absolute, [blank_start]true[blank_end] value of population parameters is always [blank_start]unknown[blank_end]. Statistical inference is using [blank_start]sample[blank_end] [blank_start]statistics[blank_end] to [blank_start]estimate[blank_end] and generalise to the larger population.
    1. Aset
    2. Ball
    3. Cpossible
    4. Dvalues
    5. Etrue
    6. Funknown
    7. Gestimate
    8. Hsample
    9. Istatistics
  2. 2You can get a completely accurate estimator with a large enough sample of the population.
    1. ARichtig
    2. BFalsch
  3. 3[blank_start]Estimation[blank_end] - produces point estimates for population parameters
    [blank_start]Hypothesis Testing[blank_end] - tests if sample data supports a certain hypothesis about the population.
    1. AEstimation
    2. BHypothesis Testing
    3. CMean
    4. DMedian
    5. EPopulation parameters
  4. 4Estimation - produces [blank_start]point[blank_end] [blank_start]estimates[blank_end] for [blank_start]population[blank_end] [blank_start]parameters[blank_end]
    Hypothesis tests - tests if [blank_start]sample[blank_end] [blank_start]data[blank_end] supports a certain [blank_start]hypothesis[blank_end] about the population
    1. Apoint
    2. Bestimates
    3. Cparameters
    4. Dpopulation
    5. Esample
    6. Fdata
    7. Ghypothesis
  5. 5Sample statistics are like random variables because you can never guess their exact value with 100% accuracy
    1. ARichtig
    2. BFalsch
  6. 6Which of the following is the correct definition of a sampling distribution of an estimator
    1. AIt looks at how an estimator performs across multiple samples
    2. BIt looks at how a population parameter performs across multiple samples
    3. CIt looks at how certain parameters perform in the population
    4. DIt looks at how an estimator performs in the population
  7. 7An unbiased estimator is one where
    1. Athe average of sample estimates are equal to or close to the actual population parameter
    2. Bthe standard deviation of sample estimates are large
    3. Cthe standard deviation of sample estimates are small
    4. Dthe average of the sample estimate does not equal the actual population parameter
  8. 8Which of the following are true
    1. AMean is always an unbiased estimator of population mean
    2. BMedian is always an unbiased estimator of population Median
    3. CMedian is NOT an unbiased estimator of population median
    4. DMean is NOT an unbiased estimator of population mean
  9. 9Standard error is the [blank_start]standard[blank_end] deviation of an [blank_start]estimator[blank_end], and measures the [blank_start]spread[blank_end] around the [blank_start]mean[blank_end] and therefore the [blank_start]precision[blank_end] of the estimator
    1. Astandard
    2. Bestimator
    3. Cspread
    4. Dmean
    5. Eprecision
  10. 10Which of the following is correct in regards to the central limit theorem
    1. AWhen n>30, the distribution of the sample mean will follow a normal distribution regardless of what the population distribution looks like
    2. BWhen n>30, the sample will follow a normal distribution regardless of what the population distribution looks like
    3. CWhen n<30, the distribution of the sample mean will follow a normal distribution but only if the population is normally distributed
    4. DWhen n>30, the distribution of the sample mean will follow a normal distribution but only if the population is normally distributed

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Beschreibung
Learning Technology Specialist Honours Psychology (MATHS581) Quiz am Lesson 4-5, erstellt von Eva Bonning am 07/04/2021.
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