Important: Test 3 is on Monday, 2 November 2009 and will cover Chapters 6 and 7 and Section 8.1. You will need to know when and how to use the following calculations:
- binompdf(n, p, k)
- binomcdf(n, p, k)
- 1–binomcdf(n, p, k)
- normalcdf(xlower, xupper, μ, σ)
- normalpdf [hint: NEVER for this course!]
- invnorm(area to left, μ, σ)
- NRMHST
- when the normal approximation to binomial probability is permitted [np(1–p) ≥ 10]
- normal approximation to binomial probability [using μ = np and σ = sqrt(np(1–p)) and using appropriate values for x
- mean and standard deviation of sampling distribution
- 68-95-99.7 Rule for any normally-distributed set of data – including a sampling distribution
- finding z-score (i.e., z = (x-μ)/σ).
The test items will not be in any order with respect to the textbook. Question #1 on the test is: “State the Central Limit Theorem. Explain, in your own words, what this theorem states.” You will need to know the other material from these sections, not just the calculations.
Today, we discussed applications of the sampling distribution and the Central Limit Theorem (CLT). According to CLT, if given x~N(μ,σ), then the sample mean (x-bar) is also normally distributed with mean μ and standard deviation σ/sqrt(n). In fact, no matter what the shape of distribution of the population, the sampling distribution will always be approximately normal with mean μ and standard deviation σ/sqrt(n).
The next homework assignment is due on Monday, 2 November 2009 and consists of the following:
Section 7.3*: # 1-11 odd, 17-25 odd;
Section 7.5: # 1-29 odd;
Section 8.1: # 1, 2, 3-15 odd, 17bc, 19-29 odd.
* Ignore any questions involving percentiles.
