Submitted By mpwelch18

Words 2019

Pages 9

Words 2019

Pages 9

Work system design:

1__Job design- Technical (able to do it), Economic (value must be added), Behavioral (feels good about doing it) Feasibilities

Labor specialization- higher specialization = narrow scope of expertise, usually more boring Eliminating boredom- Enlargement (more tasks, horizontal expansion), Job Enrichment (vertical expansion, schedule own work, test own output), Rotation (expose to other jobs) Team Approach- Problem solving teams (small group with operational expertise, ID analyze and solve), Special Purpose task forces (Issues of major significance, cross functional team, when assignment is done team is over), Self Directed team (team defines goals) Self Managed team (source outside of a team defines goals) Methods analysis- Figure out what to analyze(quality/productivity issues,), communicate with workers, watch and try to figure new way to do it. OSHA- occupational safety and health act to assure workers have good conditions, working conditions effect productivity, output quality, and saftey

2__Work measurements – how long should it take to do a job? Time Studies (Manufacturing)- Steps: 1. Chose specific job to be studies 2. Tell the worker who you are studying 3. Break job into recognizable units 4. Calculate the number of cycles you must observe by using sample data n=[(z/a)(s/x)]2 (n=# of observations, z= # of std dev at desired confidence, a=desired accuracy, s=std dev from sample, x=mean from sample) 5. Time each element, record times and rate worker performance 6. Compute Normal Time [NT= Mean Observed Time (MOT) * (PRF) * (F)] 7. Compute Standard Time (ST= NT * allowance factor) (AFtime worked = 1/1-PFD or AFjob=1*PFD) (Performance Rating Factor- factor of above or below 1, 1 being average performance) (Frequency of Occurrence- how many times each element occurs, if done every cycle > 1) (PFD - Workers pace…...

.... . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Limitations and Common Misinterpretations of Hypothesis Testing . . . . . . . . . . 1 1 6 10 15 17 Stat 3011 Chapter 9 CHAPTER 9: HYPOTHESIS TESTS Motivating Example A diet pill company advertises that at least 75% of its customers lose 10 pounds or more within 2 weeks. You suspect the company of falsely advertising the beneﬁts of taking their pills. Suppose you take a sample of 100 product users and ﬁnd that only 5% have lost at least 10 pounds. Is this enough to prove your claim? What about if 72% had lost at least 10 pounds? Goal: 9.1 Elements of a Hypothesis Test 1. Assumptions 2. Hypotheses Each hypothesis test has two hypotheses about the population: Null Hypothesis (H0 ): Alternative Hypothesis (Ha ): 1 Stat 3011 Chapter 9 Diet Pill Example: Let p = true proportion of diet pill customers that lose at least 10 pounds. State the null and alternative hypotheses for the diet pill example. 3. Test Statistic Deﬁnition: Test Statistic A test statistic is a measure of how compatible the data is with the null hypothesis. The larger the test statistic, the less compatible the data is with the null hypothesis. Most test statistics we will see have the following form: What does a large value of |T | reﬂect? NOTE: 2 Stat 3011 Chapter 9 4. p-value The p-value helps us to interpret the test statistic. Deﬁnition: p-value Assume H0 is true. Then the p-value is the probability...

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...Mean Alpha = 1 - Confidence Level Margin of Error (E): E =CONFIDENCE(alpha,SD,n) E =CONFIDENCE.T(alpha,SD,n) (small sample) Confidence Interval: = (mean - E) to (mean + E) Confidence Intervals, Proportion z =NORMSINV(confidence level + alpha/2) E =z * SQRT(p * (1-p)/n) Confidence Interval: =(proportion - E) to =(prop + E) Sample Size, Mean z = NORMSINV(confidence+alpha/2) n = (z * SD / E)^2 Sample Size, Proportion Validation: n*p ≥ 5 and n*(1-p) ≥ 5 n = p*(1 − p) * (z / E)^2 Hypothesis Testing Mean: 1-tail: z =NORMSINV(confidence level) 2-tail: z =NORMSINV(confidence level + alpha/2) Test Statistic: z = (sample mean - mean) / (SD/SQRT(n)) less reject if stat is more – than decision more reject if stat is more + than decision T2 reject if more – or + than decision Proportion: z = (pS - p) / SQRT(p*(1-p)/n) Test Statistic: z = (ps - p) / SQRT(p*(1 - p) / n) Std error= sqrt(p*q/n) q=1-p Small Sample: 1 tail: =TINV(2 * alpha,df) 2 tail: =TINV(alpha,df) Where df = degrees of freedom = n - 1 =T.INV(alpha,df) =T.INV.2T(alpha,df) P-Value: 1-tail: z =NORMDIST(sample mean, population mean, SD / SQRT(n),1) 2-tail: z = NORMDIST(sample mean, population mean, SD / SQRT(n),1)*2 Regression Analysis y = m*x + b (but in statistics it's written y = a + bx) In Excel statistics analysis: "Multiple R" = coefficient of correlation...

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...STAT 302 – Statistical Methods Lecture 8 Dr. Avishek Chakraborty Visiting Assistant Professor Department of Statistics Texas A&M University Using sample data to draw a conclusion about a population • Statistical inference provides methods for drawing conclusions about a population from sample data. • Two key methods of statistical inference: o o Confidence intervals Hypothesis tests (a.k.a., tests of significance) Hypothesis Testing: Evaluating the effectiveness of new machinery at the Bloggs Chemical Plant • Before the installation of new machinery, long historical records revealed that the daily yield of fertilizer produced by the Bloggs Chemical Plant had a mean μ = 880 tons and a standard deviation σ = 21 tons. Some new machinery is being evaluated with the aim of increasing the daily mean yield without changing the population standard deviation σ. Hypothesis Testing: Evaluating the effectiveness of new machinery at the Bloggs Chemical Plant Null hypotheses • The claim tested by a statistical test is called the null hypothesis. The test is designed to assess the strength of the evidence against the null hypothesis. Usually the null hypothesis is a statement of “no effect” or “no difference”, that is, a statement of the status quo. Alternative hypotheses • The claim about the population that we are trying to find evidence for is the alternative hypothesis. The alternative hypothesis is one-sided if it states that a parameter is larger than or...

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...distractions. (d) Capital budgeting involves financial evaluation of long-term assets. Companies routinely make capital budgeting decisions, but so do individuals. The purchase of a home or car is a decision that has implications for your finances for many subsequent years. Buying a house or car is a very personal decision, influenced by many personal, nonfinancial, preferences. However, these decisions should also be subjected to a financial evaluation using capital budgeting techniques to ensure that the choice makes good economic sense. 1-50 Copyright © 2012 John Wiley & Sons, Inc. Weygandt, Managerial Accounting, 6/e, Solutions Manual (For Instructor Use Only) BYP 1-9 CONSIDERING YOUR COSTS AND BENEFITS Discussion guide: This is a difficult decision. While the direct costs of outsourced tax return preparation may in fact be lower, you must also consider other issues: Will the accuracy of the returns be as high? Will your relationships with your customers suffer due to the loss of direct contact? Will customers resent having their personal information shipped overseas? While you may not want to lay off six employees, you also don’t want to put your firm at risk by not remaining competitive. Perhaps one solution would be to outsource the most basic tasks, and then provide training to the six employees so they can perform higher-skilled services such as tax planning. Many of the techniques that you learn in the remaining chapters of this text will help......

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...Chapter 1 – Introduction to Statistics 1-1 Review and Preview * Data – are collections of observations, such as measurements, genders, or survey responses. (A single data is a called a datum, a term that does nog see very much use.) * Statistics – is the science of planning studies and experiments; obtaining data; and then organizing, summarizing, presenting, analyzing, and interpreting those data and then drawing conclusion based on them. * Population – is the complete collection of all measurements or data that are being considered. * Census – is the collection of data from every member of the population. * Sample – is a sub-collection of members selected from a population Statistics Cheat Sheet Chapter 2 – Summarizing and Graphing Data Section 2-1: Review and Preview * Characteristics of Data * 1. Center: A representative value that indicates where the middle of the data set is located. * 2. Variation: A measure of the amount that the data values very. * 3. Distribution: The nature or shape of the spread of the data over the range of values (such as bell-shaped). * 4. Outliners: Sample values that lie very far away from the vast majority of the other sample values. * 5. Time: Any change in the characteristics of the data over time. * Study Hint: Blind memorization is not effective in remembering information. To remember the above characteristics of data, it may be helpful to use a......

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...tie in the Best Actress category, and the mean of the two ages is used; in 1932 there was a tie in the Best Actor category, and the mean of the two ages is used. These data are suggested by article “Ages of Oscar-winning Best Actors and Actress,” by Richard Brown and Gretchen Davis, Mathematics Teacher magazine. In that article, the year of birth of the award winner was subtracted from the year of the awards ceremony, but the ages in the tables below are based on the birth date of the winner and the date of the awards ceremony.) Analyzing the Results 1. Go to MyStatLab → Statcrunch → StatCrunch website → Open StatCrunch and will take you to the spreadsheet and use Data to load your data in excel onto the spreadsheet, Graph for all graphs, Stat for all analysis use it to answer question 2 to 4. Copy and paste all graphs and statcrunch output for full credit. 2. First explore the data using suitable statistics and graphs such as histogram, boxplot, etc. Use the results to make info In the histogram for actress mostly actresses received the Oscar in the age group between 20-40. The maximum number of actresses received the Oscar in the age group between 25-20. In the histogram for actors they mostly received Oscars at the age group between 30-50. The maximum number of actors received the Oscar in the age group between 40-45. The two boxes are a little different with the median of actress lower than that of actors. . Both box plots have no outliers there......

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...unusual Establishing a program of re-contacting a small number of randomly chosen individuals in order to determine the reliability of responses Old, but relevant See http://www.youtube.com/watch?v=G0ZZJXw4MTA (start from 24 seconds in; whole clip is 2min 17 secs) Ethical issues Coverage error becomes an ethical issue if particular groups/individuals are purposely excluded Nonresponse error becomes an ethical issue if survey designed such that some groups are less likely to respond Sampling error becomes an ethical issue if findings purposely presented without reference to survey size and margin of error Measurement error becomes an ethical issue if Leading questions chosen; interviewer intentionally creates a Hawthorne effect or guides respondent; respondent willingly provides false information. Sample or Census Conditions favouring the use of… Sample Budget Time available Population size Variance in the characteristic Cost of Sampling Errors Cost of Nonsampling Errors Nature of Measurement Attention to Individual Cases Small Short Large Small Low High Destructive Yes Census Large Long Small Large High Low Nondestructive No Sampling plans So, due to cost restrictions (time) need to take a sample Want sample to be representative of full population. Often have problems with self-selected samples – people who participate are more interested than general population, so not representative (sample biased) Step 1: Define the sample frame This is a list of all......

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...printout given above), Explain (0, (1, also provide the units of slope and y-intercept. Does (0, (1 make sense? d) Is there sufficient evidence to conclude that the model contributes information for predicting the Percentage of refund spent in 3-months? (State Hypothesis, and do the test.) e) Is there sufficient evidence to conclude, "As the family income increases than the Percentage of refund spent in 3-month decreases? (State Hypothesis, and do the test.) (Does it make sense to do this test? Explain) f) Calculate R-sq, what is the practical meaning of R-sq? g) Calculate the Standard error of Estimate, What is the practical meaning of S(? (Get the residual printouts – 5 points) In Minitab, Goto Stat>regression>regression, then follow the screen prints below to get the residual plots. [pic] [pic] And click ok h) State the regression Assumption 1 and test it using the residual plots. i) State the regression Assumption 2 and test it using the residual plots. j) State the regression Assumption 3 and test it using the residual plots. k) State the regression Assumption 4 and test it using the residual plots. l) Calculate R-sq(adjusted). m) Find 95% Confidence Interval for (0 n) Find 95% Confidence Interval for (1 o) Explain the relationship between Confidence Interval and Hypothesis testing. p) What is an Outlier? Are there any outliers? q) What is an...

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...will be not be using Canvas just the ALEKS web page! Watch the 2 minute video on ALEKS to understand the ALEKS program if you have not already done so. You will need an email account. Free email accounts are available from GMAIL , Yahoo (http://www.yahoo.com/), AOL (http://www.aol.com/ ) and Hotmail (www.hotmail.com). You will need the blue 10 digit course code to sign up on ALEKS. It is on the first page of the course syllabus under Course Information – Codes Needed to Register with ALEKS. The class is open early this semester if you want to get started now. 3. 4. 5. You will need a Student Access Code (this is just a sample - 6AYM7P3FTR-HS32G-5A3YA). The Student Access Code is located in the inside back cover of the ALEKS user guide that you can purchase from the bookstore. You can purchase one online at http://catalogs.mhhe.com/aleks/index.do Most students said they did not use the e-Book because they felt that my movies along with the ALEKS explanations were sufficient but for an additional $11, students like having the e-book as an option. or at the college bookstore at http://sierra.bncollege.com/webapp/wcs/stores/servlet/TBWizardView ?catalogId=10001&storeId=19556&langId=-1&level=1 If there are any delays please text or call me at 916-813-9027 or email me at dosmith@sierracollege.edu 6. Sign Up On ALEKS: www.aleks.com 1. 2. 3. 4. Email Address – See Item 2 above Sierra College Student ID omit dashes. Sierra College student ID is available......

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...excuse (see NEU student handbook) you will receive a zero for the exam. Generally, absence from an exam will be excused only for illness upon presentation of a letter from your doctor. Project There will be a team-based Project. Details of this project will be provided early in this semester. Determination of Course Grades The evaluation of coursework will be based on the student’s performance on: * Homework 15% * In Class Activities and Participation 10% * Midterm Exams 30% * Final Exam (cumulative) 30% * Data analysis project 15% Academic Honesty At this point in the program, you must have become very familiar with the graduate student honor code. The Code appears in the Graduate Business Programs Catalog and Student Guide. Every student is expected to act in accordance with the honor code. To the extent violations of the code are detected, such as plagiarism, cheating on an exam, collaboration with others on individual work, or freeloading on team projects, consequences will be very detrimental for your grade in this course, and potentially, for the remainder of your career. Students should familiarize themselves with Northeastern’s policies on academic honesty and integrity: http://www.northeastern.edu/osccr/academichonesty.html. Changes to the Syllabus The syllabus operates as our document of mutual understanding; it represents our agreement. Changes may be made to it as our progress dictates. Such changes will be discussed in class and class......

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...use 0.75. Plotting the Binomial Probabilities 1. Create plots for the three binomial distributions above. Select Graph > Scatter Plot and Simple then for graph 1 set Y equal to ‘one fourth’ and X to ‘success’ by clicking on the variable name and using the “select” button below the list of variables. Do this two more times and for graph 2 set Y equal to ‘one half’ and X to ‘success’, and for graph 3 set Y equal to ‘three fourths’ and X to ‘success’. Paste those three scatter plots below. Calculating Descriptive Statistics Open the class survey results that were entered into the MINITAB worksheet. 2. Calculate descriptive statistics for the variable where students flipped a coin 10 times. Pull up Stat > Basic Statistics > Display Descriptive Statistics and set Variables: to the coin. The output will show up in your Session Window. Type the mean and the standard deviation here. Mean: 4.600 Standard deviation: 1.429 Short Answer Writing Assignment – Both the calculated binomial probabilities and the descriptive statistics from the class database will be used to answer the following questions. 3. List the probability value for each possibility in the binomial experiment that was calculated in MINITAB with the probability of a success being ½. (Complete sentence not......

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...STAT 4220 Homework 2 Report Problem 1.22: a) Yˆ = 168.6 + 2.03X b) Yˆh = 168.6 + 2.03(40) = 168.6 + 81.2 = 249.8 c) 2.03 The population study is plastic hardness. The X is the elapsed time in hours and the Y is the hardness in Brinell units. The minimum unit was 196 with maximum to 253. The hours were 16 minimum and 40 maximum. The mean (average) was 225.6 for units and 28 for hours. The median was 226.5 units and 28 hours. The standard deviation of units with hour was 173.6. There was small variance large bias. Problem 1.28: a) a)Yˆ = 20517.6 + (-170.58)X No this equation does not fit well because there is not a line. b) 1)-170.58 2) Yˆh = 6871.2 3) ε10 = 1401.57 4) MSE= 5552112 The population was crime rates. The x is the percentage of the individuals in the county having at least high-school diploma and Y is the crime rate. The maximum percentage was 91 with the lowest 61. The crime rate was the maximum 14016 with the lowest 2105. The mean (average) was 7111 crime rate and 78.6 percent. The median was 79 percent and 6930 crime rate. The standard deviation of crime rate and percent was -6601.54. There was a Large variance small bias. Problem 1.31: In this problem the error will not include batch to batch variability and there will be a smaller variance from the original experiment. When you are going to use different batches there will not be a way to evaluate your results from the original experiment and the results there......

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...83/84: STAT, TESTS, 1-PropZTest Po: assumed proportion (0.21) x: number of successes (732) n: total number of candies (3500) In the next line, select the correct alternative hypothesis/test, then Calculate, Enter. On the next screen, the second line shows the test. The next line has the test statistic. The next line has the p-value of the test (if less than significance level, reject null) The next two lines have and n. IF using StatCrunch, you will want Stat > Proportions > One Sample > with summary. In the first window, you will enter the same information as for part 3: number of the color (number of successes) and total number of candies (number of observations). Then click Next, and in the following window, enter the claimed proportion as a decimal in the box next to “null”, select the inequality that matches the alternative hypothesis and then click Calculate. The output will include the test statistic (Z-Stat) and the p-value. Hypothesis test results: p : proportion of successes for population H0 : p = 0.21 HA : p ≠ 0.21 Proportion Count Total Sample Prop. Std. Err. Z-Stat P-value p 732 3500 0.20914286 0.006884766 -0.12449848 0.9009 Mean When you test for the mean number of candies per bag, you will need (sample mean), s (sample standard deviation) and n (total number of bags) as before. The test statistic is a z, because we have a large sample. Test statistic: IF using the TI 83/84: STAT, TESTS, Z-Test Input: Stats 0: ......

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...STAT 346/446 - A computer is needed on which the R software environment can be installed (recent Mac, Windows, or Linux computers are sufficient).We will use the R for illustrating concepts. And students will need to use R to complete some of their projects. It can be downloaded at http://cran.r-project.org. Please come and see me when questions arise. Attendance is mandatory. Topics covered in STAT 346/446, EPBI 482 Chapter 5 – Properties of a Random Sample Order Statistics Distributions of some sample statistics Definitions of chi-square, t and F distributions Large sample methods Convergence in probability Convergence in law Continuity Theorem for mgfs Major Theorems WLLN CLT Continuity Theorem Corollaries Delta Method Chapter 7 – Point Estimation Method of Moments Maximum Likelihood Estimation Transformation Property of MLE Comparing statistical procedures Risk function Inadmissibility and admissibility Mean squared error Properties of Estimators Unbiasedness Consistency Mean-squared error consistency Sufficiency (CH 6) Definition Factorization Theorem Minimal SS Finding a SS in exponential families Search for the MVUE Rao-Blackwell Theorem Completeness Lehmann-Scheffe Location and scale invariance Location and scale parameters Cramer-Rao lower bound Chapter 9 - Interval Estimation Pivotal Method for finding a confidence interval Method for finding the “best” confidence interval Large sample confidence......

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...technologies, can be employed either for social good or evil. The professionalism encouraged by these guidelines is predicated on their use in socially responsible pursuits by morally responsible societies, governments, and employers. Where the end purpose of a statistical application is itself morally reprehensible, statistical professionalism ceases to have ethical worth. C. Shared Values Because society depends on sound statistical practice, all practitioners of statistics, whatever their training and occupation, have social obligations to perform their work in a professional, competent, and ethical manner. This document is directed to those whose primary occupation is statistics. Still, the principles expressed here should also guide the statistical work of professionals in all other disciplines that use statistical methods. All statistical practitioners are obliged to conduct their professional activities with responsible attention to the following: 1. The social value of their work and the consequences of how well or poorly it is performed. This includes respect for the life, liberty, dignity, and property of other people. 2. The avoidance of any tendency to slant statistical work toward predetermined outcomes. (It is acceptable to advocate a position; it is not acceptable to misapply statistical methods in doing so.) 3. Statistics as a science. (As in any science, understanding evolves. Statisticians have a body of established knowledge, but also......

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