SlideShare a Scribd company logo
1 of 43
Inductive Statistics Dr. Ning DING [email_address] I.007 IBS, Hanze You’d better use the full-screen mode to view this PPT file.
Table of Contents Review: Chapter 5 Probability Distribution Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Chapter 5: Probability Distribution Bionomial Distribution Poisson  Distribution Discrete within a range Normal  Distribution continuous Discrete with mean λ : mean p: probability of success q: probability of failure q = 1- p Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
60  80 The student is doing better in Chemistry than in biology.  Is it correct? The student is actually doing better in biology.  Chapter 5: Probability Distribution Chemistry standardized scale Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion Test Score Class mean SD z score Biology 60 50 5 +2 Chemistry 80 90 10 -1
Chapter 6: Sampling Distribution Sample size  Dispersion of sample means Standard Error Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Chapter 6: Sampling Distribution Infinite population  Finite population Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Chapter 7: Estimation confidence level confidence interval Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion Upper tail Lower tail
Interval Estimates &  Confidence Intervals = the probability that we associate with an interval estimate It is the range of the estimate we are making.  -1.64 σ +1.64 σ 90% 90% confident that our population mean will lie within this interval.  Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Chapter 7 Estimation Interval Estimates of the  Mean Interval Estimates of the  Proportion σ  is known: σ  is unknown: n <30 &  σ  is unknown ,[object Object],[object Object]
Interval Estimates of the  mean  from Large Samples Estimate  the mean life of windshield wiper . The standard deviation of the population life is 6 months. We randomly select 100 wiper blades and know the mean is 21 months. Example: Step 1: List the known variables Step 2: Calculate the standard error of the mean n=100  σ =6 months  Ch 7 Example P.361 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  mean  from Large Samples Estimate  the mean life of windshield wiper . The standard deviation of the population life is 6 months. We randomly select 100 wiper blades and know the mean is 21 months. Example: Step 3: If we choose 95% confidence level,  find the z score -1.96 σ 95% +1.96 σ Appendix Table 1 47.5% 47.5% Ch 7 Example P.361 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  mean  from Large Samples Estimate  the mean life of windshield wiper . The standard deviation of the population life is 6 months. We randomly select 100 wiper blades and know the mean is 21 months. Example: Step 4: Calculate the upper and lower limits 19.82 22.18 95% Ch 7 Example P.361 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  mean  from Large Samples Suppose we don’t know the population standard deviation Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. Step 1: Estimate the population standard deviation. Step 2: Find the standard error of the mean Estimate the mean.  Ch 7 Example P.363 n/N = 50/700 = 0.0714  >.05  Use F.P.M. Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  mean  from Large Samples Suppose we don’t know the population standard deviation Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. Step 2: Find the standard error of the mean Estimate the mean.  Ch 7 Example P.363 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  mean  from Large Samples Step 3: Find the z score -1.64 σ +1.64 σ Appendix Table 1 Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. 90% 45% 45% Ch 7 Example P.363 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the mean from Large Samples 11,587.50 12,012.50 Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. Step 4: Calculate the upper and lower limits 90% 45% 45% Ch 7 Example P.363 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates Using  t  Distribution ,[object Object],[object Object],1. Degree of Freedom b=6 b=13 ... ... degree of freedom n-1 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates Using  t  Distribution 2. Using the  t  Distribution Table Appendix Table 2 Confidence Interval degree of f reedom 7 0.05 2.365 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates Using  t  Distribution Example: The plant manager wants to estimate the coal needed for this year. He took a sample by measuring coal usage for 10 weeks.  Step 1: Calculate the standard error of the mean  9 Step 2: Look in Appendix Table 2 to get the t value t  = 2.262 95%  Step 3: Calculate the upper and lower limits The manager is 95% confident that the mean weekly usage of coal lies between 10,899 and 11,901 tons.  Ch 7 Example P.373 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  proportion  from Large Samples Mean of the Sampling Distribution of the Proportion Standard Error of the Proportion Esitmated Standard Error of the Proportion unemployment rate is a  proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the  proportion  from Large Samples Example: What proportion of employees prefer to provide their own retirement benefits in lieu of a company-sponsored plan? n = 75 Step 1: Conduct simple random sampling Step 2: Questionnaire Agree  or  Disagree 30  vs.  45 Step 3: Calculate the estimated error of the proportion Ch 7 Example P.368 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Interval Estimates of the proportion from Large Samples Example: What proportion of employees prefer to provide their own retirement benefits in lieu of a company-sponsored plan? Step 4: Use the confidence level to find z score 99% -2.58 σ 99% 49.5% 49.5% +2.58 σ Step 5: Estabilish of the upper and lower limits 0.253 0.547 99% sure that 25.3% to 54.7% of the employees agreed with this plan Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknown AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: Basics Vocabulary ,[object Object],[object Object],[object Object],[object Object],hypothese  Hypothese  hipótesis  гипотеза   假设  l'hypothèse la probabilité  可能性  вероятность   Wahrscheinlichkeit  waarschijnlijkheid   probabilidad significativo  signifikant  significant  significative  значительный   显著 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: Basics H 0 H 1 There is  no  difference between the sample mean and the hypothesized population mean.  There is  a  difference between the sample mean and the hypothesized population mean.  H 0  : µ = 10 H 1  : µ > 15 H 1  : µ < 2 H 1  : µ ≠ 10 For example: Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion Two-tailed test One-tailed test
Chapter 8 Testing Hypotheses: Practice Ch 8 No. 8-24 P.415 The STA department installed energy-efficient lights, heaters and air conditioners last year. Now they want to determine whether the average monthly energy usage has decreased. Should they perform a one- or two-tailed test?  If their previous average monthly energy usage was 3,124 kw hours, what are the null and alternative hypotheses? Answer: One-tailed test    lower-tailed test 8-24 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: two-tailed test Ch 8 Example P.417 Assume that a manufacturer supplies axles which must withstand 80,000 pounds per square inch. Experiences show the standard deviation is 4,000 pounds.  Being either lower or greater is not allowed. He sampled 100 axles from the production and found the mean is 79,600 pounds.  Example: Step 1: List the known variables Step 2: Formulate the hypotheses Step 3: Calculate the standard error Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: two-tailed test Ch 8 Example P.417 Assume that a manufacturer supplies axles which must withstand 80,000 pounds per square inch. Experiences show the standard deviation is 4,000 pounds.  Being either lower or greater is not allowed. He sampled 100 axles from the production and found the mean is 79,600 pounds.  Example: Step 4: Visualize the confidence level -1.96  +1.96 Step 5: Establish the limits 79,216  80,784 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: one-tailed test Ch 8 Example P.419 Hospital uses large quantities of packaged doses of a drug. The individual dose is 100 cc. The body can pass off the excessive but insufficient doses will be problematic. The hospital knows the standard deviation of the supplier is 2 cc. They sampled 50 doses randomly and found the mean is 99.75 cc.  Example: Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: one-tailed test Ch 8 Example P.419 Hospital uses large quantities of packaged doses of a drug. The individual dose is 100 cc. The body can pass off the excessive but insufficient doses will be problematic. The hospital knows the standard deviation of the supplier is 2 cc. They sampled 50 doses randomly and found the mean is 99.75 cc.  Example: Step 4: Visualize the confidence level Step 5: Calcuate the z value -1.28 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: Practice Ch 8 No. 8-26  P.422 8-26 Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Step 4: Visualize the confidence level Step 5: Calcuate the z value P=0.48    z=-2.05 -2.05 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: Practice Ch 8 No. 8-26  P.422 8-27 Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Step 4: Visualize the confidence level Step 5: Calcuate the z value P=0.475     z=  1.96 -1.96  +1.96 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Ch 8 No. Example P.433 Example: Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error The HR director thinks that the average aptitude test is 90. The manager sampled 20 tests and found the mean score is 80 with standard deviation 11.  If he wants to test the hypothesis at the 0.10 level of significance, what is the procedure? Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Ch 8 No. Example P.433 Example: Step 4: Visualize the confidence level Step 5: Calcuate the  t  value The HR director thinks that the average aptitude test is 90. The manager sampled 20 tests and found the mean score is 80 with standard deviation 11.  If he wants to test the hypothesis at the 0.10 level of significance, what is the procedure? Appendix Table 2 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Ch 8 No. Example P.433 Step 4: Visualize the confidence level Appendix Table 2 Confidence Interval degree of f reedom 12 0.05  0.10 1.782 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses-Summary Ch 8 Example P.417 H 0 H 1 There is  no  difference between the sample mean and the hypothesized population mean.  There is  a  difference between the sample mean and the hypothesized population mean.  H 0  : µ = 10 H 1  : µ > 15 H 1  : µ < 2 H 1  : µ > 15  AND µ < 2 For example: Mean Proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion Two-tailed test One-tailed test
Chapter 8 Testing Hypotheses: Proportion Ch 8 Example P.427 HR director tell the CEO that the promotability of the employees is 80%. The president sampled 150 employees and found that 70% are promotable.  The CEO wants to test at the 0.05 significance level the hypothesis that 0.8 of the employees are promotable.  Example: Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: Proportion Ch 8 Example P.427 HR director tell the CEO that the promotability of the employees is 80%. The president sampled 150 employees and found that 70% are promotable.  The CEO wants to test at the 0.05 significance level the hypothesis that 0.8 of the employees are promotable.  Example: Step 4: Visualize the confidence level Step 5: Calculate the z score Proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses: Practice Ch 8 SC 8-9 P.431 .  Step 4: Visualize the confidence level Step 5: Calculate the z score Proportion Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error SC 8-9 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Chapter 8 Testing Hypotheses:  Measuring Power of a Hypothesis Test True Not True Accept Reject H 0 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion Type I Error Type II Error
Summary Review: Chapter 5 Probability Distribution Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when  σ  is known * when  σ  is unknown * when  σ  is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when  σ  is known * when  σ  is unknwn AND n=<30 ~Test for Proportion
Connection with BRM (Business Research Methods)
Connection with BRM (Business Research Methods) P.354
The Normal Distribution SPSS 1st Assessment The data can be downloaded from: Blackboard – Inductive Statsitics STA2—SPSS-- Week 3 Creating Graphs.sav

More Related Content

What's hot

Test of significance (t-test, proportion test, chi-square test)
Test of significance (t-test, proportion test, chi-square test)Test of significance (t-test, proportion test, chi-square test)
Test of significance (t-test, proportion test, chi-square test)Ramnath Takiar
 
Statistical tests /certified fixed orthodontic courses by Indian dental academy
Statistical tests /certified fixed orthodontic courses by Indian dental academy Statistical tests /certified fixed orthodontic courses by Indian dental academy
Statistical tests /certified fixed orthodontic courses by Indian dental academy Indian dental academy
 
STATISTICS: Hypothesis Testing
STATISTICS: Hypothesis TestingSTATISTICS: Hypothesis Testing
STATISTICS: Hypothesis Testingjundumaug1
 
Test of hypothesis test of significance
Test of hypothesis test of significanceTest of hypothesis test of significance
Test of hypothesis test of significanceDr. Jayesh Vyas
 
Hypothesis testing , T test , chi square test, z test
Hypothesis testing , T test , chi square test, z test Hypothesis testing , T test , chi square test, z test
Hypothesis testing , T test , chi square test, z test Irfan Ullah
 
Stat 130 chi-square goodnes-of-fit test
Stat 130   chi-square goodnes-of-fit testStat 130   chi-square goodnes-of-fit test
Stat 130 chi-square goodnes-of-fit testAldrin Lozano
 
Testing of hypothesis - large sample test
Testing of hypothesis - large sample testTesting of hypothesis - large sample test
Testing of hypothesis - large sample testParag Shah
 
Chi Square Worked Example
Chi Square Worked ExampleChi Square Worked Example
Chi Square Worked ExampleJohn Barlow
 
Lect w7 t_test_amp_chi_test
Lect w7 t_test_amp_chi_testLect w7 t_test_amp_chi_test
Lect w7 t_test_amp_chi_testRione Drevale
 
T test, independant sample, paired sample and anova
T test, independant sample, paired sample and anovaT test, independant sample, paired sample and anova
T test, independant sample, paired sample and anovaQasim Raza
 
Student's T-test, Paired T-Test, ANOVA & Proportionate Test
Student's T-test, Paired T-Test, ANOVA & Proportionate TestStudent's T-test, Paired T-Test, ANOVA & Proportionate Test
Student's T-test, Paired T-Test, ANOVA & Proportionate TestAzmi Mohd Tamil
 

What's hot (19)

Basics of Hypothesis Testing
Basics of Hypothesis TestingBasics of Hypothesis Testing
Basics of Hypothesis Testing
 
Unit 3
Unit 3Unit 3
Unit 3
 
Freq distribution
Freq distributionFreq distribution
Freq distribution
 
Test of significance (t-test, proportion test, chi-square test)
Test of significance (t-test, proportion test, chi-square test)Test of significance (t-test, proportion test, chi-square test)
Test of significance (t-test, proportion test, chi-square test)
 
Statistical tests /certified fixed orthodontic courses by Indian dental academy
Statistical tests /certified fixed orthodontic courses by Indian dental academy Statistical tests /certified fixed orthodontic courses by Indian dental academy
Statistical tests /certified fixed orthodontic courses by Indian dental academy
 
STATISTICS: Hypothesis Testing
STATISTICS: Hypothesis TestingSTATISTICS: Hypothesis Testing
STATISTICS: Hypothesis Testing
 
Small sample
Small sampleSmall sample
Small sample
 
f and t test
f and t testf and t test
f and t test
 
Test of hypothesis test of significance
Test of hypothesis test of significanceTest of hypothesis test of significance
Test of hypothesis test of significance
 
Hypothesis testing , T test , chi square test, z test
Hypothesis testing , T test , chi square test, z test Hypothesis testing , T test , chi square test, z test
Hypothesis testing , T test , chi square test, z test
 
Goodness Of Fit Test
Goodness Of Fit TestGoodness Of Fit Test
Goodness Of Fit Test
 
T-Test
T-TestT-Test
T-Test
 
Stat 130 chi-square goodnes-of-fit test
Stat 130   chi-square goodnes-of-fit testStat 130   chi-square goodnes-of-fit test
Stat 130 chi-square goodnes-of-fit test
 
Testing of hypothesis - large sample test
Testing of hypothesis - large sample testTesting of hypothesis - large sample test
Testing of hypothesis - large sample test
 
Z-Test with Examples
Z-Test with ExamplesZ-Test with Examples
Z-Test with Examples
 
Chi Square Worked Example
Chi Square Worked ExampleChi Square Worked Example
Chi Square Worked Example
 
Lect w7 t_test_amp_chi_test
Lect w7 t_test_amp_chi_testLect w7 t_test_amp_chi_test
Lect w7 t_test_amp_chi_test
 
T test, independant sample, paired sample and anova
T test, independant sample, paired sample and anovaT test, independant sample, paired sample and anova
T test, independant sample, paired sample and anova
 
Student's T-test, Paired T-Test, ANOVA & Proportionate Test
Student's T-test, Paired T-Test, ANOVA & Proportionate TestStudent's T-test, Paired T-Test, ANOVA & Proportionate Test
Student's T-test, Paired T-Test, ANOVA & Proportionate Test
 

Viewers also liked

Estimation and confidence interval
Estimation and confidence intervalEstimation and confidence interval
Estimation and confidence intervalHomework Guru
 
Elasticity &amp; forecasting
Elasticity &amp; forecastingElasticity &amp; forecasting
Elasticity &amp; forecastingHomework Guru
 
Sampling distribution
Sampling distributionSampling distribution
Sampling distributionDanu Saputra
 
Introduction To Statistics
Introduction To StatisticsIntroduction To Statistics
Introduction To Statisticsalbertlaporte
 

Viewers also liked (9)

Business statistics
Business statisticsBusiness statistics
Business statistics
 
Test hypothesis
Test hypothesisTest hypothesis
Test hypothesis
 
Estimation and confidence interval
Estimation and confidence intervalEstimation and confidence interval
Estimation and confidence interval
 
Elasticity &amp; forecasting
Elasticity &amp; forecastingElasticity &amp; forecasting
Elasticity &amp; forecasting
 
Sampling distribution
Sampling distributionSampling distribution
Sampling distribution
 
Sampling distribution
Sampling distributionSampling distribution
Sampling distribution
 
Confidence interval
Confidence intervalConfidence interval
Confidence interval
 
Sampling Distributions
Sampling DistributionsSampling Distributions
Sampling Distributions
 
Introduction To Statistics
Introduction To StatisticsIntroduction To Statistics
Introduction To Statistics
 

Similar to Lesson 04 chapter 7 estimation

Similar to Lesson 04 chapter 7 estimation (20)

Estimating a Population Mean
Estimating a Population Mean  Estimating a Population Mean
Estimating a Population Mean
 
3. Statistical inference_anesthesia.pptx
3.  Statistical inference_anesthesia.pptx3.  Statistical inference_anesthesia.pptx
3. Statistical inference_anesthesia.pptx
 
Estimating a Population Mean
Estimating a Population MeanEstimating a Population Mean
Estimating a Population Mean
 
Sqqs1013 ch6-a122
Sqqs1013 ch6-a122Sqqs1013 ch6-a122
Sqqs1013 ch6-a122
 
Two dependent samples (matched pairs)
Two dependent samples (matched pairs) Two dependent samples (matched pairs)
Two dependent samples (matched pairs)
 
6. point and interval estimation
6. point and interval estimation6. point and interval estimation
6. point and interval estimation
 
Estimation in statistics
Estimation in statisticsEstimation in statistics
Estimation in statistics
 
Statistik Chapter 6
Statistik Chapter 6Statistik Chapter 6
Statistik Chapter 6
 
Estimating a Population Mean
Estimating a Population MeanEstimating a Population Mean
Estimating a Population Mean
 
Chapter10 Revised
Chapter10 RevisedChapter10 Revised
Chapter10 Revised
 
Chapter10 Revised
Chapter10 RevisedChapter10 Revised
Chapter10 Revised
 
Chapter10 Revised
Chapter10 RevisedChapter10 Revised
Chapter10 Revised
 
Chapter09
Chapter09Chapter09
Chapter09
 
week 5.pptx
week 5.pptxweek 5.pptx
week 5.pptx
 
Sampling
SamplingSampling
Sampling
 
Estimating a Population Proportion
Estimating a Population Proportion  Estimating a Population Proportion
Estimating a Population Proportion
 
Ch3_Statistical Analysis and Random Error Estimation.pdf
Ch3_Statistical Analysis and Random Error Estimation.pdfCh3_Statistical Analysis and Random Error Estimation.pdf
Ch3_Statistical Analysis and Random Error Estimation.pdf
 
Statistical inference: Estimation
Statistical inference: EstimationStatistical inference: Estimation
Statistical inference: Estimation
 
Probability Distributions
Probability DistributionsProbability Distributions
Probability Distributions
 
statistical inference.pptx
statistical inference.pptxstatistical inference.pptx
statistical inference.pptx
 

More from Ning Ding

Victor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in ChinaVictor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in ChinaNing Ding
 
Oct11 college 5
Oct11 college 5Oct11 college 5
Oct11 college 5Ning Ding
 
Sept27 college 3
Sept27 college 3Sept27 college 3
Sept27 college 3Ning Ding
 
Sept19 college 2
Sept19 college 2Sept19 college 2
Sept19 college 2Ning Ding
 
Lesson 02 class practices
Lesson 02 class practicesLesson 02 class practices
Lesson 02 class practicesNing Ding
 
Sept13 2011 college 1
Sept13 2011 college 1Sept13 2011 college 1
Sept13 2011 college 1Ning Ding
 
Lesson 1 Chapter 5 probability
Lesson 1 Chapter 5 probabilityLesson 1 Chapter 5 probability
Lesson 1 Chapter 5 probabilityNing Ding
 

More from Ning Ding (20)

Victor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in ChinaVictor Yuan: interpretation of the economic data in China
Victor Yuan: interpretation of the economic data in China
 
Lesson 6
Lesson 6Lesson 6
Lesson 6
 
Lesson 5
Lesson 5Lesson 5
Lesson 5
 
Lesson 4
Lesson 4Lesson 4
Lesson 4
 
Lesson 3
Lesson 3Lesson 3
Lesson 3
 
Lesson 2
Lesson 2Lesson 2
Lesson 2
 
Lesson 1
Lesson 1Lesson 1
Lesson 1
 
Oct11 college 5
Oct11 college 5Oct11 college 5
Oct11 college 5
 
Sept27 college 3
Sept27 college 3Sept27 college 3
Sept27 college 3
 
Sept19 college 2
Sept19 college 2Sept19 college 2
Sept19 college 2
 
Lesson 02 class practices
Lesson 02 class practicesLesson 02 class practices
Lesson 02 class practices
 
Sept13 2011 college 1
Sept13 2011 college 1Sept13 2011 college 1
Sept13 2011 college 1
 
Lesson01
Lesson01Lesson01
Lesson01
 
Lesson06
Lesson06Lesson06
Lesson06
 
Lesson05
Lesson05Lesson05
Lesson05
 
Lesson04
Lesson04Lesson04
Lesson04
 
Lesson03
Lesson03Lesson03
Lesson03
 
Lesson02
Lesson02Lesson02
Lesson02
 
Lesson07
Lesson07Lesson07
Lesson07
 
Lesson 1 Chapter 5 probability
Lesson 1 Chapter 5 probabilityLesson 1 Chapter 5 probability
Lesson 1 Chapter 5 probability
 

Recently uploaded

Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application ) Sakshi Ghasle
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
Science 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsScience 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsKarinaGenton
 
Class 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfClass 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfakmcokerachita
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesFatimaKhan178732
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon AUnboundStockton
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfUmakantAnnand
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppCeline George
 

Recently uploaded (20)

Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application )
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
 
Science 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsScience 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its Characteristics
 
Class 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfClass 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdf
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and Actinides
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.Compdf
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website App
 

Lesson 04 chapter 7 estimation

  • 1. Inductive Statistics Dr. Ning DING [email_address] I.007 IBS, Hanze You’d better use the full-screen mode to view this PPT file.
  • 2. Table of Contents Review: Chapter 5 Probability Distribution Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 3. Chapter 5: Probability Distribution Bionomial Distribution Poisson Distribution Discrete within a range Normal Distribution continuous Discrete with mean λ : mean p: probability of success q: probability of failure q = 1- p Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 4. 60 80 The student is doing better in Chemistry than in biology. Is it correct? The student is actually doing better in biology. Chapter 5: Probability Distribution Chemistry standardized scale Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion Test Score Class mean SD z score Biology 60 50 5 +2 Chemistry 80 90 10 -1
  • 5. Chapter 6: Sampling Distribution Sample size Dispersion of sample means Standard Error Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 6. Chapter 6: Sampling Distribution Infinite population Finite population Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 7. Chapter 7: Estimation confidence level confidence interval Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion Upper tail Lower tail
  • 8. Interval Estimates & Confidence Intervals = the probability that we associate with an interval estimate It is the range of the estimate we are making. -1.64 σ +1.64 σ 90% 90% confident that our population mean will lie within this interval. Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 9.
  • 10. Interval Estimates of the mean from Large Samples Estimate the mean life of windshield wiper . The standard deviation of the population life is 6 months. We randomly select 100 wiper blades and know the mean is 21 months. Example: Step 1: List the known variables Step 2: Calculate the standard error of the mean n=100 σ =6 months Ch 7 Example P.361 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 11. Interval Estimates of the mean from Large Samples Estimate the mean life of windshield wiper . The standard deviation of the population life is 6 months. We randomly select 100 wiper blades and know the mean is 21 months. Example: Step 3: If we choose 95% confidence level, find the z score -1.96 σ 95% +1.96 σ Appendix Table 1 47.5% 47.5% Ch 7 Example P.361 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 12. Interval Estimates of the mean from Large Samples Estimate the mean life of windshield wiper . The standard deviation of the population life is 6 months. We randomly select 100 wiper blades and know the mean is 21 months. Example: Step 4: Calculate the upper and lower limits 19.82 22.18 95% Ch 7 Example P.361 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 13. Interval Estimates of the mean from Large Samples Suppose we don’t know the population standard deviation Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. Step 1: Estimate the population standard deviation. Step 2: Find the standard error of the mean Estimate the mean. Ch 7 Example P.363 n/N = 50/700 = 0.0714 >.05 Use F.P.M. Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 14. Interval Estimates of the mean from Large Samples Suppose we don’t know the population standard deviation Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. Step 2: Find the standard error of the mean Estimate the mean. Ch 7 Example P.363 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 15. Interval Estimates of the mean from Large Samples Step 3: Find the z score -1.64 σ +1.64 σ Appendix Table 1 Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. 90% 45% 45% Ch 7 Example P.363 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 16. Interval Estimates of the mean from Large Samples 11,587.50 12,012.50 Example: Find the interval estimate of the mean annual income of 700 families at 90% confidence level. Step 4: Calculate the upper and lower limits 90% 45% 45% Ch 7 Example P.363 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 17.
  • 18. Interval Estimates Using t Distribution 2. Using the t Distribution Table Appendix Table 2 Confidence Interval degree of f reedom 7 0.05 2.365 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 19. Interval Estimates Using t Distribution Example: The plant manager wants to estimate the coal needed for this year. He took a sample by measuring coal usage for 10 weeks. Step 1: Calculate the standard error of the mean 9 Step 2: Look in Appendix Table 2 to get the t value t = 2.262 95% Step 3: Calculate the upper and lower limits The manager is 95% confident that the mean weekly usage of coal lies between 10,899 and 11,901 tons. Ch 7 Example P.373 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 20. Interval Estimates of the proportion from Large Samples Mean of the Sampling Distribution of the Proportion Standard Error of the Proportion Esitmated Standard Error of the Proportion unemployment rate is a proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 21. Interval Estimates of the proportion from Large Samples Example: What proportion of employees prefer to provide their own retirement benefits in lieu of a company-sponsored plan? n = 75 Step 1: Conduct simple random sampling Step 2: Questionnaire Agree or Disagree 30 vs. 45 Step 3: Calculate the estimated error of the proportion Ch 7 Example P.368 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 22. Interval Estimates of the proportion from Large Samples Example: What proportion of employees prefer to provide their own retirement benefits in lieu of a company-sponsored plan? Step 4: Use the confidence level to find z score 99% -2.58 σ 99% 49.5% 49.5% +2.58 σ Step 5: Estabilish of the upper and lower limits 0.253 0.547 99% sure that 25.3% to 54.7% of the employees agreed with this plan Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknown AND n=<30 ~Test for Proportion
  • 23.
  • 24. Chapter 8 Testing Hypotheses: Basics H 0 H 1 There is no difference between the sample mean and the hypothesized population mean. There is a difference between the sample mean and the hypothesized population mean. H 0 : µ = 10 H 1 : µ > 15 H 1 : µ < 2 H 1 : µ ≠ 10 For example: Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion Two-tailed test One-tailed test
  • 25. Chapter 8 Testing Hypotheses: Practice Ch 8 No. 8-24 P.415 The STA department installed energy-efficient lights, heaters and air conditioners last year. Now they want to determine whether the average monthly energy usage has decreased. Should they perform a one- or two-tailed test? If their previous average monthly energy usage was 3,124 kw hours, what are the null and alternative hypotheses? Answer: One-tailed test  lower-tailed test 8-24 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 26. Chapter 8 Testing Hypotheses: two-tailed test Ch 8 Example P.417 Assume that a manufacturer supplies axles which must withstand 80,000 pounds per square inch. Experiences show the standard deviation is 4,000 pounds. Being either lower or greater is not allowed. He sampled 100 axles from the production and found the mean is 79,600 pounds. Example: Step 1: List the known variables Step 2: Formulate the hypotheses Step 3: Calculate the standard error Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 27. Chapter 8 Testing Hypotheses: two-tailed test Ch 8 Example P.417 Assume that a manufacturer supplies axles which must withstand 80,000 pounds per square inch. Experiences show the standard deviation is 4,000 pounds. Being either lower or greater is not allowed. He sampled 100 axles from the production and found the mean is 79,600 pounds. Example: Step 4: Visualize the confidence level -1.96 +1.96 Step 5: Establish the limits 79,216 80,784 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 28. Chapter 8 Testing Hypotheses: one-tailed test Ch 8 Example P.419 Hospital uses large quantities of packaged doses of a drug. The individual dose is 100 cc. The body can pass off the excessive but insufficient doses will be problematic. The hospital knows the standard deviation of the supplier is 2 cc. They sampled 50 doses randomly and found the mean is 99.75 cc. Example: Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 29. Chapter 8 Testing Hypotheses: one-tailed test Ch 8 Example P.419 Hospital uses large quantities of packaged doses of a drug. The individual dose is 100 cc. The body can pass off the excessive but insufficient doses will be problematic. The hospital knows the standard deviation of the supplier is 2 cc. They sampled 50 doses randomly and found the mean is 99.75 cc. Example: Step 4: Visualize the confidence level Step 5: Calcuate the z value -1.28 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 30. Chapter 8 Testing Hypotheses: Practice Ch 8 No. 8-26 P.422 8-26 Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Step 4: Visualize the confidence level Step 5: Calcuate the z value P=0.48  z=-2.05 -2.05 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 31. Chapter 8 Testing Hypotheses: Practice Ch 8 No. 8-26 P.422 8-27 Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Step 4: Visualize the confidence level Step 5: Calcuate the z value P=0.475  z= 1.96 -1.96 +1.96 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 32. Ch 8 No. Example P.433 Example: Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error The HR director thinks that the average aptitude test is 90. The manager sampled 20 tests and found the mean score is 80 with standard deviation 11. If he wants to test the hypothesis at the 0.10 level of significance, what is the procedure? Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 33. Ch 8 No. Example P.433 Example: Step 4: Visualize the confidence level Step 5: Calcuate the t value The HR director thinks that the average aptitude test is 90. The manager sampled 20 tests and found the mean score is 80 with standard deviation 11. If he wants to test the hypothesis at the 0.10 level of significance, what is the procedure? Appendix Table 2 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 34. Ch 8 No. Example P.433 Step 4: Visualize the confidence level Appendix Table 2 Confidence Interval degree of f reedom 12 0.05 0.10 1.782 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 35. Chapter 8 Testing Hypotheses-Summary Ch 8 Example P.417 H 0 H 1 There is no difference between the sample mean and the hypothesized population mean. There is a difference between the sample mean and the hypothesized population mean. H 0 : µ = 10 H 1 : µ > 15 H 1 : µ < 2 H 1 : µ > 15 AND µ < 2 For example: Mean Proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion Two-tailed test One-tailed test
  • 36. Chapter 8 Testing Hypotheses: Proportion Ch 8 Example P.427 HR director tell the CEO that the promotability of the employees is 80%. The president sampled 150 employees and found that 70% are promotable. The CEO wants to test at the 0.05 significance level the hypothesis that 0.8 of the employees are promotable. Example: Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error Proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 37. Chapter 8 Testing Hypotheses: Proportion Ch 8 Example P.427 HR director tell the CEO that the promotability of the employees is 80%. The president sampled 150 employees and found that 70% are promotable. The CEO wants to test at the 0.05 significance level the hypothesis that 0.8 of the employees are promotable. Example: Step 4: Visualize the confidence level Step 5: Calculate the z score Proportion Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 38. Chapter 8 Testing Hypotheses: Practice Ch 8 SC 8-9 P.431 . Step 4: Visualize the confidence level Step 5: Calculate the z score Proportion Step 1: List the known variables Step 2: Formulate Hypotheses Step 3: Calculate the standard error SC 8-9 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 39. Chapter 8 Testing Hypotheses: Measuring Power of a Hypothesis Test True Not True Accept Reject H 0 Review: -Chapter 5 Probability Distribution -Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion Type I Error Type II Error
  • 40. Summary Review: Chapter 5 Probability Distribution Chapter 6 Sampling Distribution Chapter 7 Estimation ~Interval Estimation for Mean * when σ is known * when σ is unknown * when σ is unknown AND n=<30 ~Interval Estimation for Proportion Chapter 8 Testing Hypothesis ~Basics ~Two- and One-tailed Test ~Test for Mean * when σ is known * when σ is unknwn AND n=<30 ~Test for Proportion
  • 41. Connection with BRM (Business Research Methods)
  • 42. Connection with BRM (Business Research Methods) P.354
  • 43. The Normal Distribution SPSS 1st Assessment The data can be downloaded from: Blackboard – Inductive Statsitics STA2—SPSS-- Week 3 Creating Graphs.sav

Editor's Notes

  1. Solution. If we let X denote the number of subscribers who qualify for favorable rates, then X is a binomial random variable with n = 10 and p = 0.70. And, if we let Y denote the number of subscribers who don&apos;t qualify for favorable rates, then Y , which equals 10 −  X , is a binomial random variable with n = 10 and q = 1 − p = 0.30. We are interested in finding P ( X ≥ 4). We can&apos;t use the cumulative binomial tables, because they only go up to p = 0.50. The good news is that we can rewrite  P ( X  ≥ 4) as a probability statement in terms of Y : P ( X ≥ 4) = P (− X ≤ −4) = P (10 − X ≤ 10 − 4) = P ( Y ≤ 6) Now it&apos;s just a matter of looking up the probability in the right place on our cumulative binomial table. To find  P ( Y  ≤ 6), we:  Find  n  = 10  in the first column on the left. Find the column containing  p  = 0.30 . Find the  6  in the second column on the left, since we want to find  F (6) =  P ( Y  ≤ 6). Now, all we need to do is read the probability value where the  p  = 0.30 column and the ( n  = 10, y  = 6) row intersect. What do you get? Do you need a hint? The cumulative binomial probability table tells us that  P ( Y  ≤ 6) =  P ( X  ≥ 4) = 0.9894. That is, the probability that at least four people in a random sample of ten would qualify for favorable rates is 0.9894.