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University of Florida - ENT - 3003
1Understanding entrepreneurship2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part."Entrepreneurship" Earliest definition talked about it being a formof
University of Florida - ENT - 3003
Attributes of EntrepreneursKey Attributes of Entrepreneurs The Top Six Commitment and Determination Leadership Opportunity obsession High tolerance of risk, ambiguity and uncertainty Creativity, self-reliance and adaptability Motivation to excelCommitm
University of Florida - ENT - 3003
The Mindset of the Entrepreneur Leaders vs. Managers A ComparisonComparison Criteria Creating an agenda Developing a human network to achieve the agenda Execution OutcomesCreating An Agenda Manager: Focus is planning and budgeting. Sets detailed steps
University of Florida - ENT - 3003
Myths About EntrepreneursMost Entrepreneurs Take Significant, Uncalculated Risks Starting Company Most hate risk, but are not afraid of it Entrepreneurs work in the early stages, to share risks with others: Employees bear risk Accrued payroll or paid
University of Florida - ENT - 3003
SYLLABUSSpring 2012 Course Title: Live Location: Course Web Site: Instructor: ENT 3003 - Principles of Entrepreneurship Stuzin Hall 104: M & W Periods 3 & 4 Sakai William J. Rossi Clinical Professor of Entrepreneurship Tel: (352) 273-0334 E-Mail: william
University of Florida - ENT - 3003
Principles of EntrepreneurshipENT 3003 Course Introduction William J. RossiContact Information Bill Rossi william.rossi@cba.ufl.edu Office: 267 Stuzin Hall Hours: Monday and Wednesday 1:002:00 Or, any other time by prior appt. Phone: 273-0334Course We
University of Florida - ENT - 3003
11Incorporating ETHICS AND SOCIAL RESPONSIBILITY INTO THE BUSINESS2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.Learning Objectives Explain the rol
University of Florida - ENT - 3003
The Age of the GazellesSome Facts About Gazelles Small firms create most jobs in US economy Majority of these job-creating companies are fastgrowing businesses called Gazelles 20% annual sales growth for at least 5 years Despite significant down-sizin
University of Florida - ENT - 3003
The Evolution of New BusinessThe following material is based on case studies, surveys and meetings with Inc 500 companies conducted by Bhide. Vintage is 1989, but results true still today. Summary of "The Origin and Evolution of New Businesses" Amar Bhid
University of Florida - ACG - 2071
Building Blocks of Managerial AccountingChapter 21Three Types of Companies Service Merchandisers Manufacturers2Service Companies Provide a service only No inventory Examples Accountants Banks Doctors Lawyers3Merchandisers Resell products purcha
University of Florida - ACG - 2071
Activity-Based Costing, Lean Production, and the Costs of QualityChapter 41Why and How do Companies Refine their Cost Allocation Systems? Why refine? Mismatching resources Cost distortion Who can refine? Manufacturing operations Service companies a
University of Florida - ACG - 2071
Job CostingChapter 31Process Costing Mass production Similar items Total costs are averaged over all units Examples Paint manufacturers Oil refineries Cereal manufacturers2Job Costing Unique, custom products or small batches Total costs are accumu
University of Florida - ACG - 2071
Introduction to Managerial AccountingChapter 11Managers' ResponsibilitiesPlanning Setting goals and objectivesDecision MakingDirectingOverseeing day-to-day operationsControllingEvaluating results of operations2Planning Setting goals and object
University of Florida - ACG - 2071
ACG 2071; Introduction to Managerial Accounting Syllabus; Spring 2012 Instructor: Deborah Garvin: J.D.; CPA; Master Lecturer, Fisher School of Accounting Live Class: Tuesday and Thursday, Periods 3 & 4 (9:35 11:15 a.m.) in Stuzin 104 Garvin Office: 311 Ge
University of Florida - QMB - 3250
One-Sample Inference ReviewPortions of Chapters 8-9 (e-book only)Inference Review1One-Sample Inference During the last half of your prerequisitecourse (STA2023 on campus), you would have covered basic confidence interval estimates and hypothesis tes
University of Florida - QMB - 3250
Additional Estimation TopicsSections 8.7, 8.5 And elsewhereAdditional Estimation Topics1Intervals for Population Mean In our previous lecture, we looked at intervals for the population mean. Our estimate came from:s X t nwhere t is a value from the
Purdue University - Main Campus - STAT - 490
1.Chapter 1A with profits whole life insurance policy on (30) has a death benefit of100,000 at the time that it is issued. The policy pays a reversionarybonus at the end of each policy year which are equal to 2.5% of thedeath benefit (including any d
Purdue University - Main Campus - STAT - 490
24.Chapter 3If deaths are uniformly distributed between integral ages, calculateq 53]21.5[25.If l[51] = 1 0 0, 0 0 0, calculate l[50]26.Teach Life Insurance Company has two cohorts of policyholders.Cohort A has 1000 insured lives who are all age
Purdue University - Main Campus - STAT - 490
Chapter 41. You arexgiven the following mortality table:lxqxpx9010000.100.90919000.200.80927200.400.60934320.500.50942161.000.00950Assume that deaths are uniformly distributed between integral ages andthat the equivalence
Purdue University - Main Campus - STAT - 490
Chapter 51. You aregiven that a continuous whole life annuity to (50) pays at arate of 100 per year for the first 20 years and 500 per yearthereafter. Calculate the actuarial present value if mortalityfollows the Illustrative Life Table with i = 0.06
Purdue University - Main Campus - STAT - 490
Chapter 61. A whole life policy for 50,000 is issued to (75). The death benefit ispayable at the moment of death. The premiums are payable for the lifeof the insured.You are given:a.Mortality follows the Illustrative Life Table.b.i 6%.c.Deaths a
Purdue University - Main Campus - STAT - 311
Review of CalculusDerivatives:Definition of DerivativeIn geometric terms, the derivative is the slope of a curve at a particular point.using an alternative definition, if x + h = c, thenDefinition of a partial derivativeThis occurs when we hold all
Purdue University - Main Campus - STAT - 311
Chapter 1: Probability Basics h4p:/www.cartoonstock.com/directory/p/probability.asp Propor%on of Hearts 0.8 Propor%on of Hearts Frequen?st Interpreta?on 0.8 0.6 Trial 1 0.4 Trial 2 0.2 Trial 3 0 0 20 40 60 Nu
Purdue University - Main Campus - STAT - 311
Chapter 2: Mathema-cal Probability h5p:/www.cartoonstock.com/directory/p/probability.asp Sample Spaces: Examples 1.2.3.4.Tossing Coins: We toss a coin 3 -mes Rolling two 4-sided dies Life-me of a light bulb Gene-cs: Do
Purdue University - Main Campus - STAT - 311
Ch. 3: Combinatorial Probability Highh2p:/brownsharpie.courtneygibbons.org/?cat=22 Sampling With Replacement (BCR): Example Suppose that a sample of size 2 is drawn with replacement from a populaIon of size 5. a) Use
Purdue University - Main Campus - STAT - 311
Chapter 4: Condi/onal Probability and Independence h6p:/imgs.xkcd.com/comics/condi/onal_risk.png Example: Condi/onal Probability Roll a fair 4 sided die 3 /mes A = the event that two 1s are tossed B = the event tha
Georgia Tech - PHYS - 2111
Purdue University - Main Campus - STAT - 311
Ch. 5: Discrete Random Variables and Their Distribu9ons Random Variable: Example We are playing a very simplified version of blackjack in which each person is only dealt 2 cards. We are interested in the sum of the cards a) is the sum of the cards a qua
Georgia Tech - PHYS - 2111
Purdue University - Main Campus - STAT - 311
Common Derivatives and IntegralsCommon Derivatives and IntegralsDerivativesBasic Properties/Formulas/Rules d ( cf ( x ) ) = cf ( x ) , c is any constant. ( f ( x ) g ( x ) ) = f ( x ) g ( x ) dx d n d ( c ) = 0 , c is any constant. ( x ) = nxn-1 , n is
Georgia Tech - PHYS - 2111
Purdue University - Main Campus - STAT - 311
Homework 1 (14 pts + 1 bonus) due Jan 21(1 pt. bonus) Q0. Why were the earrings that I wore to class today relevant to today's lecture The earrings that I wore are dice (clear 6 sided dice to be specific). (3 pts.) 1.4. The following table provides a fre
Purdue University - Main Campus - STAT - 311
Homework 2 (13 points) due Jan 27(1.3 pts.) 2.4 (6-sided die)de. Suppose that one die is rolled and that you observe the number of dots facing up. From the last problem set: The sample space includes all of the possible outcomes or = cfw_1, 2, 3, 4, 5, 6
Purdue University - Main Campus - STAT - 311
Homework 3 (15 points) due Feb. 3.(1 pt.) 2.42. A commuter train arrives punctually at a station every half hour. Each morning, a commuter named John leaves his house and casually strolls to the strain station. Find the probability that John waits for th
Purdue University - Main Campus - STAT - 311
Homework 4 (11.5 points) due Feb. 10(1 pt.) 3.34ab A club has 14 members. a) How many ways can a governing committee of size 3 be chosen? This is without replacement because once a person is on the committee; he can't be on it again. This is unordered be
Purdue University - Main Campus - STAT - 311
Homework 5 (12 points) due Feb. 17(1.2 pt.) 4.4abc. The following table provides a frequency distribution, with frequencies in thousands, for the number of rooms in U.S. housing units. (Note: this is the same table as was used in problem 1.4.) Rooms No.
Purdue University - Main Campus - STAT - 311
SET DEFINITIONS1. 5. 9. 13. Item set 2. 6. Definition collection of objects 3. 7. Designation cfw_1,3, 5,7 4. 8. example my deck of cards is a set of cardsEmpty set 0. 1 Subset 14.16.Equal sets7. 120.Proper subset 21.a set has nothing in it 11. A i
Purdue University - Main Campus - STAT - 501
Stat 501Experimental Statistics IHandoutsPrint off the following:Syllabus ScheduleAs we go along:Posted lectures Homeworks Other handouts and review topicsAbout SAS Read the Introduction to SAS handout if desired.intro.sas is the file with the c
Purdue University - Main Campus - STAT - 501
Section 1.2Describing Distributions with NumbersQuantitative DataMeasuring CenterMean MedianMeasuring SpreadQuartiles Five Number Summary Standard deviationBoxplotsMeasures of CenterThe meanThe arithmetic mean of a data set (average value) Denot
Purdue University - Main Campus - STAT - 501
Section 1.3The Normal DistributionsTopicsDensity curves Normal distributions The 68-95-99.7 rule The standard normal distribution Normal distribution calculations Standardizing observations Normal quantile plotsDensity curvesDensity curveImagine a s
Purdue University - Main Campus - STAT - 501
Sections 2.1-2.2Looking at Data-RelationshipsData with two or more variables:Response vs Explanatory variables Scatterplots Correlation Regression lineAssociation between a pair of variablesAssociation: Some values of one variable tend to occur more
Purdue University - Main Campus - STAT - 501
Chapter 2 highlightsAssociation and CausationAssociation between a pair of variablesAssociation: Some values of one variable tend to occur more often with certain values of the other variable Both variables measured on same set of individuals Examples:
Purdue University - Main Campus - STAT - 501
Section 5.2Sampling Distribution for Counts and ProportionsPreviewPopulation distribution vs. sampling distribution Binomial distributions for sample counts Finding binomial probabilities: tables Binomial mean and standard variation Sample proportions
Purdue University - Main Campus - STAT - 501
Introduction to Inference Section 6.1Estimating with ConfidenceIntroductionDistinguish chance variations from permanent features of a phenomenon:Give SAT test to a SRS of 500 California seniors samplemean = 461 What does it say about the mean SAT sc
Purdue University - Main Campus - STAT - 501
Section 7.1Inference for the mean of a populationChange: Population standard deviation () is now unknown The t distribution One-sample t confidence interval One-sample t test Matched pairs t procedures Robustness of t proceduresThe t distribution:The
Purdue University - Main Campus - STAT - 501
Section 8.1Inference for a Single ProportionRecall: Population ProportionLet p be the proportion of "successes" in a population. A random sample of size n is selected, and X is the count of successes in the sample. Suppose n is small relative to the po
Purdue University - Main Campus - STAT - 501
Chapter 9Two categorical variables. Data Analysis and Inference for Two-Way TablesTopicsImportant change: We switch from quantitative variables to categorical variables describing relations in two-way tables marginal distributions conditional distribut
Purdue University - Main Campus - STAT - 501
Section 10.1Simple Linear RegressionA continuation of Chapter 2Statistical model for linear regression Data for simple linear regression Estimation of the parameters Confidence intervals and significance tests Confidence intervals for mean response vs.
Purdue University - Main Campus - STAT - 501
Section 11.1Multiple Linear Regression (MLR)Topics-MLRExtension of SLR Statistical model Estimation of the parameters and interpretation R-square with MLR Anova Table F-Test and t-testsA continuation of Chapter 10Most things are conceptually similar
Purdue University - Main Campus - STAT - 501
Section 12.1One-Way Analysis of Variance (ANOVA)Inference for One-Way ANOVAComparing means for several groups Format of data An analogy: two sample t-statistic ANOVA hypotheses and model Understanding two types of variation Estimates of population para
Purdue University - Main Campus - STAT - 501
STAT 501Experimental Statistics IPurpose: To explain the essential ideas and concepts of applied statistics, including numericalsummaries, graphing, hypothesis testing, confidence intervals, two-way tables and the Chi-square,regression and ANOVA. Also
Purdue University - Main Campus - STAT - 501
If you find a mistake, please email me ASAP: colvertn@stat.purdue.edu1.a. 89.248b. 0.2215c. (61.3, 88.7)2.a. 0.0479b. No.c. 0.02563.a. 0.9951b. 0.80304.a.b.c.d.N( = 0.7, = 0.0458)0.1379(0.6084, 0.7916)457 guarantees less than 0.01.5.
Purdue University - Main Campus - STAT - 501
Correlation Exampleoptions ls=72;title1 'Gesell Correlation Example';data gesell;infile 'C:\gesell.txt';input name $ age score;yrs = age/12; /* creating new variable "yrs" whichconverts age in months to age in years */run;symbol value = circle;p
Purdue University - Main Campus - STAT - 501
Exam 1 Review-Summary of topicsChapter 1 Individuals Categorical and Quantitative variables Graphical tools for categorical variables Bar Chart Pie Chart Graphical tools for quantitative variables Stem and leaf plot Histogram Distributions Describe: Shap
Purdue University - Main Campus - STAT - 501
Test of Mean(s):Hypotheses:One SampleH 0:Ha:Two Sample = 0 > 0 < 0 0H 0:Ha:IF you DO know :X 0nTest of Significance:z=Confidence Interval:X z*n(XX 0snt=1IF you do NOT know :Test of Significance:t=Confidence Interval:X t *sn
Purdue University - Main Campus - STAT - 501
Experiments on learning in animals sometimesmeasure how long it takes a mouse to find itsway through a maze. The mean time is 20seconds for one particular maze. A researcherthinks that playing rap music will cause the miceto complete the maze faster
Purdue University - Main Campus - STAT - 501
Getting Started in SASSome general instructions regarding homeworks:Do not use an alternate program(s) to make any of your graphs, for now just make themby hand, in homework 2 we will start using SAS!Occasionally I will give special instructions for s
Purdue University - Main Campus - STAT - 501
1 Sample t-test in SASoptions nodate pageno=1;goptions colors=(none);title1 'One sample t-test in SAS';data one;infile 'C:\gesell.txt';input name $ age score;run;proc print data=one;run;One sample t-test in SASObs12345678910111213
Purdue University - Main Campus - STAT - 501
Matched Pairs t-test in SASoptions nodate pageno=1;goptions colors=(none);title 'Analysis of Aggressive behaviors - Example 7.7';data moon;input patient aggmoon aggother;aggdiff = aggmoon - aggother;datalines;1 3.330.272 3.670.593 2.670.324
Purdue University - Main Campus - STAT - 501
2 Sample t-test in SASoptions nodate pageno=1;goptions colors=(none);title1 'DRP data - Example 7.14';data drp;input group score @;datalines;1 24 1 43 1 58 1 71 1 43 1 49 1 61 1 441 67 1 49 1 53 1 56 1 59 1 52 1 62 1 541 57 1 33 1 46 1 43 1 572
Purdue University - Main Campus - STAT - 501
Two-Way Tables in SASoptions nodate pageno=1;goptions colors=(none);title 'Age versus College Program - class example';data one;input age $ program $ count;datalines;18below2full3618below2part9818below4full7518below4part3718to212full1