Quantitative Business Res Meth
Quantitative Business Res Meth MKT 317
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This 41 page Class Notes was uploaded by Jeanette Orn on Saturday September 19, 2015. The Class Notes belongs to MKT 317 at Michigan State University taught by Thomas Page in Fall. Since its upload, it has received 3 views. For similar materials see /class/207250/mkt-317-michigan-state-university in Marketing at Michigan State University.
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Date Created: 09/19/15
MKT 317 QUANTITATIVE BUSINESS RESEARCH METHODS Spring 2012 PROFESSOR Dr Page OFFICE HOURS 200 7 400 Tuesday and Thursday and by appointment OFFICE LOCATION N332 North Business Complex PHONE 4326419 E MAIL tpagemsuedu TEXT Statistics for Business and Economics 11 edition by McClave et al COURSE WEBPAGE httpswwwmsueducoursemsc317 TEACHING ASSISTANTS See the course webpage for teaching assistant office hours and contact information READ THE SYLLABUS COMPLETELY YOU CAN EXPECT AT LEAST ONE QUESTION ON ITS CONTENT SOMETIME DURING THE TERM COURSE DESCRIPTION This course focuses on the application of statistical techniques to real world business problems Topics covered include applications of difference of means tests analysis of variance regression and correlation selected nonparametric tests and forecasting COURSE OBJECTIVES 1 To develop an understanding of the value and importance of applying statistical procedures to business decisions 2 To develop the ability to recognize the appropriate statistical procedure for various decision making situations 3 To develop skill in using statistical methods in practical business situations METHOD OF INSTRUCTION There will be two lectures held each week The lectures are designed to introduce and clarify the statistical topics to be covered in the course and to relate those topics to business applications The lectures will be primarily based on examples of the various statistical techniques COURSE PRERE UISITES It is assumed that all students have completed Statistics 315 or equivalent and understood the concepts presented in that course If such is not the case then you must take Statistics 315 BEFORE taking this course It is strongly recommended that students review the material from STT 315 as many of those concepts will be used in this course EXAMS There will be three midterm exams and one nal exam Due to the nature of the material all exams including the nal are cumulative They may cover any material previously covered in the course Exam dates are listed on the schedule at the end of this syllabus and on the webpage Midterms will normally consist of 25 questions and the nal will normally consist of 30 questions A PICTURE ID WILL BE REQUIRED TO TAKE ALL EXAMS TESTS WILL NOT BE GRADED WITHOUT A VALID PICTURE ID WITH YOUR PICTURE ON IT MAKE UP EXAMS IF NEEDED WILL BE GIVEN AFTER THE REGULARLY SCHEDULED EXAM TIME NO EXCEPTIONS THIS INCLUDES THE FINAL EXAM SO PLAN ACCORDINGLY Any makeup exam must be completed within three days of the scheduled exam time Makeup midterms will not be given simply because a student has other exams on the same day Makeup exams will require documentation of a valid excuse The documentation will be veri ed and if found to be false no makeup will be given Make up nals will M be given for any of the following reasons 1 a common nal exam at the same time eg Accounting or Economics 2 you are taking two classes at the same time or 3 another course has changed its nal exam time to con ict with the MKT 317 nal If you have three nal exams in a calendar day and want to move your MKT 317 nal you will need to get a form from Professor Page to have signed by the professors of the other courses to verify that you do have three nals on the same calendar day A copy of the University policy on nal exams is provided in a folder on ANGEL All makeup exams will be given m the regularly scheduled exam time Students who plan to leave the country at the end of the term must schedule their departure AFTER the nal exam This applies even if your parents have made reservations for you without consulting you Penalties will be imposed if you miss a midterm or the nal exam because you simply forgot when it was scheduled Once you have taken an exam you cannot retake it because you were not feeling well during the exam nor is that an excuse to have the exam weights altered If you are ill the day of the exam get a doctor s note and schedule a makeup exam DEAD GRANDMOTHERS 7To paraphrase William Shakespeare Cowards die many times before their death grandmothers die but once While in today s society it is possible to have several grandmothers it is a fairly well established fact that they along with all other relatives can only die once Unfortunately this does occasionally happen on test dates If it happens on an exam date a makeup exam can be scheduled However before the makeup exam will be given the student must provide proof that l the person is actually dead and 2 proof that the person was actually a cloi relative GRADING Grades will be based on the following weights Percent of Final Grade EXAM 1 25 EXAM 2 25 EXAM 3 25 Final Exam 25 The weights are not negotiable and will not be altered due to poor performance on a particular exam nor will improvement over the term be taken into account There seems to be a tendency for some students to not perform well on the rst midterm and then perform well on the remaining three exams Since all exams are egually weighted this can have a detrimental effect on the student s grade As previously stated these weights cannot be changed based on performance on individual exams Therefore students are strongly encouraged to perform well on all exams to avoid this issue The following percentages based on total points will guarantee you the following grade no rounding 900000 and above 40 850000 to lt 900000 35 800000 to lt 850000 30 750000 to lt 800000 25 700000 to lt 750000 20 650000 to lt 700000 15 600000 to lt 650000 10 Whether or not the cutoff points are adjusted downward will depend on the overall class average obtained after all scores are in Therefore the degree of adjustment if any cannot be determined until after the nal exam If there is any downward adjustment to the cutoff points all categories will be adjusted by the same amount Individual exams scores are not adjusted Once the determination for cut off points for individual grades has been made and grades have been assigned requests for higher grades will not be considered except in the case of recording or calculation errors This is a departmental policy A copy of this memo is provided in a folder on ANGEL There will always be some people who are just below the cutoff for the next highest grade This is unfortunate but it is M a reason for changing a grade While you may not feel that your final grade accurately re ects your effort in this course unless there has been a recording or calculation error it most likely does and this does not constitute a reason for changing a grade Also there are no extra credit options for the class MISSED CLASSES If you miss a class it is strongly recommended that you get the notes from several people After you have had time to go over them see Professor Page or a TA if you have any questions Copies of the overheads used in class are not given out Coming late to class or leaving early is not an excuse to request copies of overheads used in class CHEATING Cheating of any form on exams will not be tolerated If cheating is detected penalties will be assessed which could include suspension from the University A copy of this Business School Honor Code is provided in a folder on ANGEL VERIFIED INDIVIDUALIZED SERVICES AND ACCOMMODATIONS 1 VISA If you are a student who has a VISA you must make the needed arrangements within the first week of classes Please see the staff in the Marketing Office N370 BCC immediately in order to ensure that the required accommodations are available for the entire term Failure to do so may result the department not being able to provide the needed accommodations especially if it is a last minute request LOST EXAMS Ifwe do not have a signed scan sheet or a signed copy ofthe exam it will be assumed that you did not take the test A WORD OF ADVICE Do not wait until the end of the term to ask for help If you are having difficulties let us know We are here to help Do not come into our offices at the end of the term after having done poorly on the tests and ask what you can do to bring up your grade Unfortunately by that time it is often too late You have ample opportunity to demonstrate your competence with the course material Therefore under no circumstances will extra credit work be given Also you should make us aware of extenuating circumstances as soon as possible Waiting until the end of the term to discuss a problem that occurred earlier will not be of value TUTORS We are often asked if tutors are available for this class If someone identifies themselves to us as being willing to tutor MKT 317 students we keep their contact information and give it to anyone who asks Also the Learning Resource Center in Bessey Hall often has students willing to tutor for MKT 317 Check their webpage at wwwmsueduuserlrc Otherwise if you feel you need a tutor my advice is to go to the statistics department and ask if any grad students are interested The marketing department does not keep a list of tutors WEB PAGE and ANGEL The course web page can be accessed at the following address httpwwwmsueducoursemsc3l7 Check this page for useful course material The course is also listed on ANGEL In addition practice exams are available on ANGEL under the lessons tab THE MKT 317 FA FILE Since this may be the only part of the syllabus that you will read which may end up costing you points on an exam the following is a summary of the most frequently asked questions in MKT 317 along with the correct answers 1 Should I have already taken STT 315 YES 2 Can I do extra credit work NO 3 Can Inegotiate different weights for the exams if I did not do well on one NO 4 Is the final cumulative YES V39 My ight leaves two days before the final Can Itake the makeup final earlier No you may take an incomplete and take the nal when you return However this problem should have been avoided in the first place SCHEDULE w m READING ASSIGNMENT CHAPTER SECTION 110 Course Introduction ll2 Review of Hypothesis Testing Procedure 6 l 62 ll7 Levels of Measurement 15 ll9 Difference of Two Means Test 7 l 72 l24 Difference of Two Means TestsiPaired Samples 73 l26 Difference of Two Proportions 74 l3l Tests Involving FDistribution and Variances 76 22 Topic To Be Determined 27 EXAM 1 29 Analysis of Variance ANOVAOne Factor 8 l 82 214 ANOVAiMultiple Comparisons 83 216 ANOVAiTwo Way 84 1 Learning Objectives Test a speci c value of a population parameter mean or proportion called a test of hypothesis Provide a measure of reliability for the hypothesis test called the signi cance level of the test 2011 Pearson Education Inc 61 The Elements of a Test of Hypothesis 2011 Pearson Education Inc Hypothesis Testing 39 I believe the 39 population mean age is 50 ypothesis Reject hypothesis Populatlon Not close What s a Hypothesis A statistical hypothesis is I believe the mean GPA of a statement about the this class is 35 numerical value of a if population parameter quot 2011 Pearson Education Inc Null Hypothesis The null hypothesis denoted H0 represents the hypothesis that will be accepted unless the data provide convincing evidence that it is false This usually represents the status quo or some claim about the population parameter that the researcher wants to test 201 1 Pearson Education Inc Alternative Hypothesis The alternative research hypothesis denoted Ha represents the hypothesis that will be accepted only if the data provide convincing evidence of its truth This usually represents the values of a population parameter for which the researcher wants to gather evidence to support 201 1 Pearson Education Inc Alternative Hypothesis Opposite of null hypothesis The hypothesis that will be accepted only if the data provide convincing evidence of its truth Designated Ha 4 Stated in one of the following forms Ha u at some value Ha u lt some value Ha u gt some value Identifying Hypotheses Example problem Test that the population mean is not 3 Steps State the question statistically u 72 3 State the opposite statistically u 3 Must be mutually exclusive amp exhaustive Select the alternative hypothesis 1 7t 3 Has the 72 lt or gt sign State the null hypothesis 1 3 201 1 Pearson Education Inc What Are the Hypotheses Is the population average amount of TV Viewing 12 hours 0 State the question statistically u 12 State the opposite statistically u at 12 Select the alternative hypothesis Ha ua 12 0 State the null hypothesis H0 u 12 2011 Pearson Education Inc What Are the Hypotheses Is the population average amount of TV Viewing different from 12 hours 0 State the question statistically u i 12 State the opposite statistically u 12 Select the alternative hypothesis Ha ua 12 0 State the null hypothesis H0 u 12 2011 Pearson Education Inc What Are the Hypotheses Is the average cost per hat less than or equal to 20 0 State the question statistically u S 20 State the opposite statistically u gt 20 Select the alternative hypothesis Ha u gt 20 0 State the null hypothesis H0 u 20 2011 Pearson Education Inc What Are the Hypotheses Is the average amount spent in the bookstore greater than 25 0 State the question statistically u gt 25 State the opposite statistically u S 25 Select the alternative hypothesis Ha u gt 25 0 State the null hypothesis H0 u 25 2011 Pearson Education Inc Test Statistic The test statistic is a sample statistic computed from information provided in the sample that the researcher uses to decide between the null and alternative hypotheses 201 1 Pearson Education Inc Test Statistic Example The sampling distribution of Xassuming u 2400 the chance of observing 3 more than 1645 standard deviations above 2400 is only 05 if in fact the true mean u is 2400 It Ct 05 M 24100 16450 Reject Hg 2011 Pearson Education Inc Type Error A Type I error occurs if the researcher rejects the null hypothesis in favor of the alternative hypothesis When in fact H0 is true The probability of committing a Type I error is denoted by 05 201 1 Pearson Education Inc Rejection Region The rejection region of a statistical test is the set of possible values of the test statistic for which the researcher will reject H0 in favor of H a Rejection region 1645 Computed z 212 2011 Pearson Education Inc Type II Error A Type 11 error occurs if the researcher accepts the null hypothesis When in fact H0 is false The probability of committing a Type 11 error is denoted by 8 201 1 Pearson Education Inc Conclusions and Consequences for a Test of Hypothesis True State of Nature Conclusion HO True Ha True Accept HO Correct decision Type 11 error Assume HO True probability 8 Reject HO Type I error Correct decision Assume Ha True probability a 201 1 Pearson Education Inc Elements of a Test of Hypothesis 1 Null hypothesis HO A theory about the speci c values of one or more population parameters The theory generally represents the status quo which we adopt until it is proven false 2 Alternative research hypothesis Ha A theory that contradicts the null hypothesis The theory generally represents that which we will adopt only when suf cient evidence exists to establish its truth 201 1 Pearson Education Inc Elements of a Test of Hypothesis 3 Test statistic A sample statistic used to decide Whether to reject the null hypothesis 4 Rejection region The numerical values of the test statistic for which the null hypothesis will be rejected The rejection region is chosen so that the probability is a that it will contain the test statistic when the null hypothesis is true thereby leading to a Type I error The value of a is usually chosen to be small eg 01 05 or 10 and is referred to as the level of signi cance of the test 201 1 Pearson Education Inc Elements of a Test of Hypothesis 5 Assumptions Clear statements of any assumptions made about the populations being sampled 6 Experiment and calculation of test statistic Performance of the sampling experiment and determination of the numerical value of the test statistic 201 1 Pearson Education Inc Elements of a Test of Hypothesis 7 Conclusion a If the numerical value of the test statistic falls in the rejection region we reject the null hypothesis and conclude that the alternative hypothesis is true We know that the hypothesistesting process will lead to this conclusion incorrectly Type I error only 100 05 of the time when H0 is true 201 1 Pearson Education Inc Elements of a Test of Hypothesis 7 Conclusion b If the test statistic does not fall in the rejection region we do not reject HO Thus we reserve judgment about which hypothesis is true We do not conclude that the null hypothesis is true because we do not in general know the probability 8 that our test procedure will lead to an incorrect acceptance of HO Type 11 error 201 1 Pearson Education Inc 62 Formulating Hypotheses and Setting Up the Rejection Region 2011 Pearson Education Inc Steps for Selecting the Null and Alternative Hypotheses 1 Select the alternative hypothesis as that which the sampling experiment is intended to establish The alternative hypothesis will assume one of three forms a Onetailed uppertailed eg Ha u gt 2400 b Onetailed lowertailed eg Ha u lt 2400 c Twotailed eg Ha u 75 2400 201 1 Pearson Education Inc Steps for Selecting the Null and Alternative Hypotheses 2 Select the null hypothesis as the status quo that which will be presumed true unless the sampling experiment conclusively establishes the alternative hypothesis The null hypothesis will be speci ed as that parameter value closest to the alternative in one tailed tests and as the complementary or only unspeci ed value in twotailed tests eg HO u 2400 201 1 Pearson Education Inc OneTailed Test A onetailed test of hypothesis is one in which the alternative hypothesis is directional and includes the symbol lt or gt 201 1 Pearson Education Inc TwoTailed Test A twotailed test of hypothesis is one in which the alternative hypothesis does not specify departure from H0 in a particular direction and is written with the symbol 75 201 1 Pearson Education Inc Basic Idea Sampling Distribution It is unlikely that we would get a sample mean of this value therefore we reject the hypothesis that u50 if in fact this were the population mean 20 U 50 Sample Means 2011 Pearson Education Inc Rejection Region OneTail Test Sampllng Dlstrlbutlon Level Of Con dence Rejection Fail to Reject H0 Sample Statistic Critical Value Value Rejection Regions TwoTailed Test Sampllng Dlstrlbutlon Level Of Con dence Rejection Region Rejection Region 1 a Fail to Reject Region lt gt 12 a H0 Sample Statistic Crltlcal Value Crltlcal Val ue Val ue Rejection Regions Alternative Hypotheses Lower Upper TWOTailed Tailed Tailed a10 zlt 128 zgt128 zlt 1645 orzgt1645 a05 zlt 1645 zgt1645 zlt 196 0rzgt196 a 01 Zlt 233 Zgt 233 Zlt 2575 0rzgt 2575 201 1 Pearson Education Inc 63 Test of Hypotheses about a Population Mean Normal z Statistic 2011 Pearson Education Inc LargeSample Test of Hypothesis about J OneTailed Test TWOTailed Test Hot1W0 Hot1W0 Hat1W0 Hat175x10 0r Ha gt 0 Test Statistic Test Statistic XoXo XUoXUo Z 2 039 SN 039 SN 201 1 Pearson Education Inc LargeSample Test of Hypothesis about J OneTailed Test Rejection region Z lt Za or z gt 2a when Ha u gt 0 where 2a is Chosen so that PZ gt 20 05 201 1 Pearson Education Inc LargeSample Test of Hypothesis about J TwoTailed Test Rejection region 39239 gt Zaz where 2M2 is chosen so that PZ gt Zaz 062 Note uo is the symbol for the numerical value assigned to u under the null hypothesis 201 1 Pearson Education Inc
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