Test
Lesson 4-5
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Preguntas del test (14)
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.
- Aset
- Ball
- Cpossible
- Dvalues
- Etrue
- Funknown
- Gestimate
- Hsample
- Istatistics
2You can get a completely accurate estimator with a large enough sample of the population.
- AVerdadero
- BFalso
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.- AEstimation
- BHypothesis Testing
- CMean
- DMedian
- EPopulation parameters
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- Apoint
- Bestimates
- Cparameters
- Dpopulation
- Esample
- Fdata
- Ghypothesis
5Sample statistics are like random variables because you can never guess their exact value with 100% accuracy
- AVerdadero
- BFalso
6Which of the following is the correct definition of a sampling distribution of an estimator
- AIt looks at how an estimator performs across multiple samples
- BIt looks at how a population parameter performs across multiple samples
- CIt looks at how certain parameters perform in the population
- DIt looks at how an estimator performs in the population
7An unbiased estimator is one where
- Athe average of sample estimates are equal to or close to the actual population parameter
- Bthe standard deviation of sample estimates are large
- Cthe standard deviation of sample estimates are small
- Dthe average of the sample estimate does not equal the actual population parameter
8Which of the following are true
- AMean is always an unbiased estimator of population mean
- BMedian is always an unbiased estimator of population Median
- CMedian is NOT an unbiased estimator of population median
- DMean is NOT an unbiased estimator of population mean
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
- Astandard
- Bestimator
- Cspread
- Dmean
- Eprecision
10Which of the following is correct in regards to the central limit theorem
- AWhen n>30, the distribution of the sample mean will follow a normal distribution regardless of what the population distribution looks like
- BWhen n>30, the sample will follow a normal distribution regardless of what the population distribution looks like
- CWhen n<30, the distribution of the sample mean will follow a normal distribution but only if the population is normally distributed
- DWhen n>30, the distribution of the sample mean will follow a normal distribution but only if the population is normally distributed
11Which of the following is a correct implication of the Central Limit Theorem
- ASample mean is an unbiased estimator of the population mean
- BSample median is an unbiased estimator of population median
- CAs sample size increases, spread increases meaning that the distribution is tighter around the mean
- DAs sample size increases, spread decreases meaning that the distribution becomes more spread out around the mean
12Implications of the Central Limit Theorem are as follows
The sample mean will be [blank_start]normally[blank_end] [blank_start]distributed[blank_end] when n[blank_start]>[blank_end]30
Sample mean is an [blank_start]unbiased[blank_end] [blank_start]estimator[blank_end] of the population mean
As sample size [blank_start]increases[blank_end], the [blank_start]standard[blank_end] [blank_start]deviation[blank_end] decreases and the [blank_start]distribution[blank_end] is [blank_start]tighter[blank_end] around the mean- A>
- Bnormally
- Cdistributed
- Dunbiased
- Eestimator
- Fstandard
- Gdeviation
- Hincreases
- Itighter
- Jdistribution
13Sample variance depends on the [blank_start]population[blank_end] [blank_start]variance[blank_end] and the [blank_start]sample[blank_end] [blank_start]size[blank_end], if the population variance is [blank_start]large[blank_end] and the sample size is [blank_start]small[blank_end], then the sample [blank_start]standard[blank_end] [blank_start]deviation[blank_end] will be [blank_start]large[blank_end] and there will be a greater [blank_start]spread[blank_end] in the sample.
- Apopulation
- Bvariance
- Csample
- Dsize
- Elarge
- Fsmall
- Gstandard
- Hdeviation
- Ilarge
- Jspread
14Which of the following is correct
- AConfidence intervals and unbiasedness are about the process of finding those estimates, rather than the actual value you've obtained.
- BConfidence intervals and unbiasedness are about the actual value you've obtained, rather than process of finding those estimates
- CConfidence intervals and unbiasedness tell you information about the true value of a parameter in the population with 100% accuracy
- DConfidence intervals and unbiasedness tell you information about the true value of the mean in the population
Información
- Descripción
- Learning Technology Specialist (MATHS581) Honours Psychology Test sobre Lesson 4-5, creado por Eva Bonning el 07/04/2021.
- Autor
- Eva Bonning
- Idioma
- English
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