Chapter Nine Review

TaylorPaul

Heather

1. A statistic is a number that describes a sample. You use a statistic in order to estimate an unknown

A. VariabilityB. ParameterC. Proportion

2. A parameter is a number that describes theA. PopulationB. SampleC. Distribution

3. P represents the population proportions as p-hat representsA. Sample MeanB. True MeanC. Sample Proportion

4. X-Bar represents the mean of the sample as Mu represents theA. Mean of PopulationB. Proportion of PopulationC. Proportion of Sample

5. You can only use normal approximation for p-hat when…A. Population is at least ten times sample sizeB. np>10 and nq>10C. You can always assume normal distributionD. All of the aboveE. A and B only

6. The central limit theorem or CLT tells thatA. Regardless the shape of the population distribution, the

shape of the sampling distribution of x-bar will be approximately normal if n is large enough

B. The shape of the population will always directly affect the shape of the sample

C. If the population is skewed then the sample distribution is always skewed regardless the size of the sample

7. A statistical inference uses data to draw conclusions about theA. SampleB. PopulationC. Distribution

8. __________ describes the values of a statistic would take in many repetitions of a sample or experiment under like conditionsA. SpreadB. Sampling VariabilityC. Sampling Distribution

9. The variability of a statistic is the range of a sampling distribution. If the sample size is larger the spread becomesA. LargerB. SmallerC. Sample size doesn’t affect spread

10.If the sample X bar is very far from the mu you may question if the sample population was

A. BiasB. UnbiasedC. This is normal, so don’t suspect anything