* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Confidence Interval Estimation for a Population Mean
		                    
		                    
								Survey							
                            
		                
		                
                            
                            
								Document related concepts							
                        
                        
                    
						
						
							Transcript						
					
					Confidence Interval Estimation for a Population Mean Lecture 33 Section 10.3 Tue, Nov 14, 2006 Confidence Intervals   To estimate , we will use confidence intervals, as we did when estimating p. The basic form, as well as the theory, is the same: (pt. est.)  (approp. no. of st. devs.) Confidence Intervals    What is the point estimate for ? What is the standard deviation for this estimator? How do we determine the appropriate number of standard deviations? Confidence Intervals  Ifx has a normal distribution, then the confidence interval is or x  z  / n     x  z  s / n  If (x – )/(s/n) has a t distribution, then the confidence interval is  x t s/ n  When to Use Z  If The population is normal (or nearly normal) and  is known, or  The population is not normal, but the sample size is at least 30,   Then use Z. When to Use t  If The population is normal (or nearly normal), and   is not known, and  The sample size is less than 30,   Then use t. Example   Example 10.4, p. 641: The Kellogg Corporation controls approximately a 43% share of the ready-to-eat cereal market worldwide. A popular cereal is Corn Flakes. Suppose the weights of full boxes of a certain kind of cereal are normally distributed with a population standard deviation of 0.29 ounces. A random sample of 25 boxes produced a mean weight of 9.82 ounces. Construct a 95% confidence interval for the true mean weight of such boxes. Example      Use Z. Why? n = 25. x = 9.82. Assume that  = 0.29. Level of confidence = 95%, so z = 1.96. Example  The confidence interval is 9.82  (1.96)(0.29/25) = 9.82  0.114 = (9.706, 9.934). TI-83 – Confidence Intervals      When the standard normal distribution applies, do the following. Press STAT. Select TESTS. Select ZInterval. A window appears requesting information. TI-83 – Confidence Intervals        Select Data or Stats. Assume we selected Stats. Enter . Enterx. Enter n. Enter the level of confidence. Select Calculate and press ENTER. TI-83 – Confidence Intervals      A window appears containing The title “ZInterval”. The confidence interval in interval notation. The sample mean. The sample size. Example   Example 10.5, p. 643: Unoccupied seats on flights cause airlines to lose revenue. Suppose that a large airline wants to estimate its average number of unoccupied seats per flight from Detroit to Minneapolis over the past month. To accomplish this, the records of 61 such flights were randomly selected, and the number of unoccupied seats was recorded for each of the sampled flights. The sample mean is 12.6 and sample standard deviation is 4.4 seats. Construct a 99% confidence interval for the mean number of unoccupied seats. Example      Should we use Z or t? Why? n = 61. x = 12.6. s = 4.4. Level of confidence = 99%. Find t. Example    Consider again the t table (Table IV). The degrees of freedom include every value up to 30, then jump to 40, 60, 120. If the actual degrees of freedom are Between 30 and 40, use 30.  Between 40 and 60, use 40.  Between 60 and 120, use 60.   If they are beyond 120, use z. Example  The confidence interval is 12.6  (2.660)(4.4/61) = 12.6  1.499 = (11.101, 14.099). TI-83 – Confidence Intervals      To use t, do the following. Press STAT. Select TESTS. Select TInterval. A window appears requesting information. TI-83 – Confidence Intervals        Select Data or Stats. Assume we selected Stats. Enterx. Enter s. Enter n. Enter the level of confidence. Select Calculate and press ENTER. TI-83 – Confidence Intervals       A window appears containing The title “TInterval”. The confidence interval in interval notation. The sample mean. The sample standard deviation. The sample size.
 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
									 
                                             
                                             
                                             
                                             
                                             
                                             
                                             
                                             
                                             
                                             
                                            