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CHAPTER SIX

CHAPTER SIX. Confidence Intervals. Section 6.1. Confidence Intervals for the MEAN (Large Samples). Estimating Vocab. Point Estimate: a single value estimate for a population parameter. Interval Estimate: a range of values used to estimate a population parameter.

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CHAPTER SIX

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  1. CHAPTER SIX Confidence Intervals

  2. Section 6.1 Confidence Intervals for the MEAN (Large Samples)

  3. Estimating Vocab • Point Estimate: a single value estimate for a population parameter. • Interval Estimate: a range of values used to estimate a population parameter. • Level of Confidence (c): the probability that the interval estimate contains the population parameter • The level of confidence, c, is the area under the curve between 2 z-scores called Critical Values

  4. Find the critical value zc necessary to construct a confidence interval at the given level of confidence. • C = 0.85 • C = 0.75

  5. More Vocab! • Sampling Error: the difference between the point estimate and the actual population parameter. • Margin of Error (E): the greatest possible distance between the point estimate and the population parameter. E = zc ·σ √n • When n > 30, s may be used for σ

  6. Find the sampling error

  7. Find the margin of error for the given values.

  8. Confidence Intervals for the Population Mean • A c-confidence interval for the population mean µ is: mean – E < µ < mean + E

  9. Construct a C.I. for the Mean • 1. Find the sample mean and sample size. • 2. Specify σ if known. Otherwise, if n > 30 , find the sample standard deviation s. • 3. Find the critical value zc that corresponds with the given level of confidence. • 4. Find the margin of error, E. • 5. Find the left and right endpoints and form the confidence interval.

  10. Construct the indicated confidence interval for the population mean.

  11. 44. A random sample of 55 standard hotel rooms in the Philadelphia, PA area has a mean nightly cost of $154.17 and a standard deviation of $38.60. Construct a 99% confidence interval for the population mean. Interpret the results. • 46. Repeat Exercise 44, using a standard deviation of s = $42.50. Which confidence interval is wider? Explain.

  12. Sample Size: given c and E…

  13. 56. A beverage company uses a machine to fill one-liter bottles with water. Assume that the population of volumes is normally distributed. • A) The company wants to estimate the mean volume of water the machine is putting in the bottles within 1 milliliter. Determine the minimum sample size required to construct a 95% confidence interval for the population mean. Assume the population standard deviation is 3 milliliters. • B) Repeat part A using an error tolerance of 2 milliliters. Which error tolerance requires a larger sample size? Explain.

  14. Section 6.2 Confidence Intervals for the MEAN (Small Samples)

  15. The t – Distribution (table #5) • Used when the sample size n < 30 , the population is normally distributed, and δ is unknown. • t – Distribution is a family of curves. • Bell shaped, symmetric about the mean. • Total area under the t - curve is 1 • Mean, median, mode are equal to 0

  16. Uses Degrees of Freedom (d.f. =n–1) • d. f. are the # of free choices after a the sample mean is calculated. • To find the critical value, tc , use the t table. • Find the critical value, tc for c = 0.98, n = 20 • Find the critical value, tc for c = 0.95, n = 12

  17. Confidence Intervals and t - Distributions • 1. Find the sample mean, standard deviation, and sample size. • 2. ID the degrees of freedom, level of confidence and the critical value. • 3. Find the margin of error, E. • 4. Find the left and right endpoints and for the confidence interval.

  18. Construct the indicated C.I.

  19. Use a Normal or a t – Distribution to construct a 95% C.I. for the population mean. • 28. In a random sample of 15 mortgage institutions, the mean interest rate was 4.99% and the standard deviation was 0.36%. Assume the interest rates are normally distributed.

  20. 30. In a recent season, the standard deviation of the yards per carry for all running backs was 1.34. The yards per carry of 20 randomly selected running backs are listed below. Assume the yards per carry are normally distributed. 5.6 4.4 3.8 4.5 3.3 5.0 3.6 3.7 4.8 3.5 5.6 3.0 6.8 4.7 2.2 3.3 5.7 3.0 5.0 4.5

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