Basic Statistics for Business and Economics ch 9
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| Point Estimate | The statistic, computed from sample information, which is used to estimate the population parameter.
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| Confidence Interval | A range of values constructed sample data so that the population parameter is likely to occur within that range at a specified probability. The specified probability is called the level of confidence.
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| Level of Confidence | Specified Probability
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| Standard Error | The standard deviation of the sampling distribution of the sample mean.
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| 95 Percent Confidence Interval | z = 1.96
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| 99 Percent Confidence Interval | z = 2.58
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| The factors that determine width of a confidence interval are: | The sample size, n. The variability in the population sigma, usually estimated by s. The desired level of confidence.
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| What are the characteristics of the t distribution? | It is a continuous distribution. It is bell-shaped and symmetrical. There is a family of t distributions where the mean is 0 and the standard deviations differ according to the sample size. It is more spread out and flatter than the z distribution.
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| Use a Z distribution if: | The population standard deviation is known or the sample size is at least 30.
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| Use a t distribution if: | The population standard deviation is unknown or the sample size is less than 30.
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| Proportion | The fraction, ratio, or percent indicating the part of the sample of the population having a particular trait of interest.
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| Sample Proportion (p) = | X / n
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| Finite-Population Correction Factor (FPC) | For a finite population, where the total number of objects is N and the size of the sample is n, the adjustment is made to the standard errors of the sample means and the proportion. If n/N is less than .05, then the FPC can be ignored.
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| Finite | A population that has a fixed upper bound.
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| Selecting a sample size (n)depends on these factors: | The level of confidence desired. The margin of error the researcher will tolerate. The variability in the population being studied.
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| The Maximum Allowable Error, (E) | The amount that is added and subtracted to the sample mean (or sample proportion) to determine the endpoints of the confidence interval.
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