Important: Test 3 is on Monday, 2 November 2009 and will cover Chapters 6, 7, and 8. You will need to know when to use
- 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
The test items will not be in any order with respect to the textbook.
Today, we briefly discussed, again, that the area under the normal curve refers to percentage and probability. Thus, you can use normalcdf to calculate area, percentage or probability. Recall, if z is used, then assume N(0,1). If given N(μ,σ), then the distribution is normal with mean μ and standard deviation σ.
We also discussed one example from Section 7.5 and how add or subtract 0.5 or both add and subtract 0.5 from x to make the correction for continuity (see Figure 47 on p. 363 of your text).
Lastly, we discussed Sampling Distributions from Section 8.1 – we will discuss them in more detail on Wednesday. At the very end of class I mentioned The Central Limit Theorem (CLT). This is so important to statistics that I require that you know the exact definition for the test (see p. 385 for a decent definition). We will finish discussing Chapter 8 on Wednesday. The sampling distribution applet that was used in class is located at http://onlinestatbook.com/stat_sim/sampling_dist/index.html.
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, 3-29 odd;
Section 8.2: # 1-21 odd.
