Chapter_07e

Chapter_07e - Overview Overview...

Info iconThis preview shows pages 1–10. Sign up to view the full content.

View Full Document Right Arrow Icon
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Overview Overview 7.1 Introduction to Sampling Distributions 7.2 Central Limit Theorem for Means 7.3 Central Limit Theorem for Proportions
Background image of page 2
Point Estimates Point Estimates Use known statistics to estimate unknown     parameters and report a single number     as the estimate The value of the statistic is called the  point  estimate Table 7.1 Point estimation: Use statistics to estimate unknown  population parameters
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Sampling error Sampling error The distance between the point estimate and its  target parameter Table 7.3 Sampling error for common  characteristics 
Background image of page 4
Sampling distribution of the sample mean Sampling distribution of the sample mean Collection of the sample means of all possible samples of size  n The mean of the sampling distribution of the sample mean x  is the value of the population mean   μ . Denoted as x μ = The standard deviation of the sampling distribution of the  sample mean x is      s is the population standard deviation is the sample size / x n σ =
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Example Example According to CanEquity Mortgage company, the mean age  of mortgage applicants in the City of Toronto is 37 years  old. Assume that the standard deviation is 6 years. Find  the mean and standard deviation for the sampling  distribution of x for the following sample sizes:  (a) 4,  (b) 9,  (c) 25,  (d) 49,  (e) 100,  (f) 225.
Background image of page 6
Example continued Example continued Solution We have          = μ = 37. Value for      does not depend on the sample size, so the  value is true for any sample size. Now, we have  σ  = 6 which is the standard deviation of the  population.  What will be the standard deviations of the  sample means?  It will be different for each case as it  depends on the sample size.   x μ x
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Example 7.4 continued Example 7.4 continued Solution We have      = μ = 37. Value for      does not depend on the sample size,  so the value is true for any sample size. σ  = 6 x μ x
Background image of page 8
Example 7.4 continued Example 7.4 continued Solution 6 a. n = 4. Then 3. 4 x n σ σ= = = 6 b. n = 9. Then 2. 9 x n = = 6 c. n = 25. Then 1.2. 25 x n = = 6 d. n = 49. Then 0.86. 49 x n = 6 e. n = 100. Then 0.6. 100 x n = = 6 f. n = 225. Then 0.4.
Background image of page 9

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 10
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 32

Chapter_07e - Overview Overview...

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online