Chapter Nine Review

1. Chapter Nine Review Taylor Paul Heather

2. A statistic is a number that describes a sample. You use a statistic in order to estimate an unknown • Variability • Parameter • Proportion

3. 2. A parameter is a number that describes the • Population • Sample • Distribution

4. 3. P represents the population proportions as p-hat represents • Sample Mean • True Mean • Sample Proportion

5. 4. X-Bar represents the mean of the sample as Mu represents the • Mean of Population • Proportion of Population • Proportion of Sample

6. 5. You can only use normal approximation for p-hat when… • Population is at least ten times sample size • np>10 and nq>10 • You can always assume normal distribution • All of the above • A and B only

7. 6. The central limit theorem or CLT tells that • 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 • The shape of the population will always directly affect the shape of the sample • If the population is skewed then the sample distribution is always skewed regardless the size of the sample

8. 7. A statistical inference uses data to draw conclusions about the • Sample • Population • Distribution

9. 8. __________ describes the values of a statistic would take in many repetitions of a sample or experiment under like conditions • Spread • Sampling Variability • Sampling Distribution

10. 9. The variability of a statistic is the range of a sampling distribution. If the sample size is larger the spread becomes • Larger • Smaller • Sample size doesn’t affect spread

11. If the sample X bar is very far from the mu you may question if the sample population was • Bias • Unbiased • This is normal, so don’t suspect anything