英文统计学1.pptx
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1、,Chapter 9,Part A Hypothesis Testing,Developing Null and Alternative Hypotheses,Type I and Type II Errors,Population Mean:s Known,Population Mean:s Unknown,Population Proportion,Hypothesis Testing,Hypothesis testing can be used to determine whether a statement about the value of a population paramet
2、er should or should not be rejected.,The null hypothesis,denoted by H0,is a tentative assumption about a population parameter.,The alternative hypothesis,denoted by Ha,is the opposite of what is stated in the null hypothesis.,The hypothesis testing procedure uses data from a sample to test the two c
3、ompeting statements indicated by H0 and Ha.,Developing Null and Alternative Hypotheses,It is not always obvious how the null and alternative hypotheses should be formulated.,Care must be taken to structure the hypotheses appropriately so that the test conclusion provides the information the research
4、er wants.,The context of the situation is very important in determining how the hypotheses should be stated.,In some cases it is easier to identify the alternative hypothesis first.In other cases the null is easier.,Correct hypothesis formulation will take practice.,Alternative Hypothesis as a Resea
5、rch Hypothesis,Developing Null and Alternative Hypotheses,Many applications of hypothesis testing involve an attempt to gather evidence in support of a research hypothesis.,In such cases,it is often best to begin with the alternative hypothesis and make it the conclusion that the researcher hopes to
6、 support.,The conclusion that the research hypothesis is true is made if the sample data provide sufficient evidence to show that the null hypothesis can be rejected.,Alternative Hypothesis as a Research Hypothesis,Developing Null and Alternative Hypotheses,Example:A new teaching method is developed
7、 that is believed to be better than the current method.,Alternative Hypothesis:The new teaching method is better.,Null Hypothesis:The new method is no better than the old method.,Alternative Hypothesis as a Research Hypothesis,Developing Null and Alternative Hypotheses,Example:A new sales force bonu
8、s plan is developed in an attempt to increase sales.,Alternative Hypothesis:The new bonus plan increase sales.,Null Hypothesis:The new bonus plan does not increase sales.,Alternative Hypothesis as a Research Hypothesis,Developing Null and Alternative Hypotheses,Example:A new drug is developed with t
9、he goal of lowering blood pressure more than the existing drug.,Alternative Hypothesis:The new drug lowers blood pressure more than the existing drug.,Null Hypothesis:The new drug does not lower blood pressure more than the existing drug.,Developing Null and Alternative Hypotheses,Null Hypothesis as
10、 an Assumption to be Challenged,We might begin with a belief or assumption that a statement about the value of a population parameter is true.,We then using a hypothesis test to challenge the assumption and determine if there is statistical evidence to conclude that the assumption is incorrect.,In t
11、hese situations,it is helpful to develop the null hypothesis first.,Developing Null and Alternative Hypotheses,Example:The label on a soft drink bottle states that it contains 67.6 fluid ounces.,Null Hypothesis:The label is correct.m 67.6 ounces.,Alternative Hypothesis:The label is incorrect.m 67.6
12、ounces.,Null Hypothesis as an Assumption to be Challenged,One-tailed(lower-tail),One-tailed(upper-tail),Two-tailed,Summary of Forms for Null and Alternative Hypotheses about a Population Mean,The equality part of the hypotheses always appears in the null hypothesis.,In general,a hypothesis test abou
13、t the value of a population mean must take one of the following three forms(where 0 is the hypothesized value of the population mean).,Example:Metro EMS,Null and Alternative Hypotheses,A major west coast city provides one of the mostcomprehensive emergency medical services in theworld.Operating in a
14、 multiple hospital systemwith approximately 20 mobile medical units,theservice goal is to respond to medical emergencieswith a mean time of 12 minutes or less.,The director of medical services wants toformulate a hypothesis test that could use a sampleof emergency response times to determine whether
15、or not the service goal of 12 minutes or less is beingachieved.,Null and Alternative Hypotheses,The emergency service is meetingthe response goal;no follow-upaction is necessary.,The emergency service is notmeeting the response goal;appropriate follow-up action isnecessary.,H0:,Ha:,where:=mean respo
16、nse time for the population of medical emergency requests,Type I Error,Because hypothesis tests are based on sample data,we must allow for the possibility of errors.,A Type I error is rejecting H0 when it is true.,The probability of making a Type I error when the null hypothesis is true as an equali
17、ty is called the level of significance.,Applications of hypothesis testing that only control the Type I error are often called significance tests.,Type II Error,A Type II error is accepting H0 when it is false.,It is difficult to control for the probability of making a Type II error.,Statisticians a
18、void the risk of making a Type II error by using“do not reject H0”and not“accept H0”.,Type I and Type II Errors,CorrectDecision,Type II Error,CorrectDecision,Type I Error,Reject H0(Conclude m 12),Accept H0(Conclude m 12),H0 True(m 12),H0 False(m 12),Conclusion,Population Condition,Example:Metro EMS,
19、The EMS director wants to perform a hypothesistest,with a.05 level of significance,to determinewhether the service goal of 12 minutes or less is being achieved.,The response times for a random sample of 40medical emergencies were tabulated.The samplemean is 13.25 minutes.The population standarddevia
20、tion is believed to be 3.2 minutes.,One-Tailed Tests About a Population Mean:s Known,Critical Value Approach to One-Tailed Hypothesis Testing,The test statistic z has a standard normal probability distribution.,We can use the standard normal probability distribution table to find the z-value with an
21、 area of a in the lower(or upper)tail of the distribution.,The value of the test statistic that established the boundary of the rejection region is called the critical value for the test.,The rejection rule is:Lower tail:Reject H0 if z z,a 1,0,-za=-1.28,Reject H0,Do Not Reject H0,z,Samplingdistribut
22、ion of,Lower-Tailed Test About a Population Mean:s Known,Critical Value Approach,0,za=1.645,Reject H0,Do Not Reject H0,z,Samplingdistribution of,Upper-Tailed Test About a Population Mean:s Known,Critical Value Approach,p-Value Approach toOne-Tailed Hypothesis Testing,Reject H0 if the p-value.,The p-
23、value is the probability,computed using the test statistic,that measures the support(or lack of support)provided by the sample for the null hypothesis.,If the p-value is less than or equal to the level of significance,the value of the test statistic is in the rejection region.,p-Value Approach,p-val
24、ue 72,0,-za=-1.28,a=.10,z,z=-1.46,Lower-Tailed Test About a Population Mean:s Known,Samplingdistribution of,p-Value a,so reject H0.,p-Value Approach,p-Value 11,0,za=1.75,a=.04,z,z=2.29,Upper-Tailed Test About a Population Mean:s Known,Samplingdistribution of,p-Value a,so reject H0.,Steps of Hypothes
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