KEY (not always used, but used the same way) = Main Points Key Words (get you points on tests) Remember: these will save your life Descriptive Statistics: Sum or Description of a population Sample means (M) or proportions (P) allow us to infer a plausible value of a characteristic Confidence Intervals: A sample gives us a statistic (sample M or P). We are unable to say exactly what the population mean or proportion is. To get around this we say we have a confidence that our parameter lies with in an interval. This interval is centered around a sample proportion (a mean). Basically its a point estimate with a margin of error we tack on, a Confidence Interval. See book Definition for more info Confidence Level (C): For every Confidence Interval there is a C C is how much confidence" we have in our method. often choices for confidence levels are 90%, 95%, 99%. Remember: A Confidence Level is not a probability How to read a C: a C of 90% means "in the long run, 90% of the results from this method will capture the true value of the population parameter being estimated within the confidence interval." See book definition for more info Applied: Confidence Interval for a pop. mean (we are currently using z-intervals) To mix up a good C we work with three things
In order to use z-intervals we MUST have #'s 1 and 3.
2/1 - Chapter 10 Steps for full credit on interval problems: 1. Name the Interval Z-Interval for population mean 2. State and Check the conditions
A) Given population distribution is approximately normal Remember: Do not use "it" when writing any of this!!! 3. Show the work 4. Write your final answer with the mean in between (_________<M<_________) Pat Phrase (plug in your own data in the underline sections): "I am 99% confident that the true mean number of years general managers spend with the company is between 11.01 and 12.59" |