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ECO 6416  Applied Business Research Tools  UCF Study Resources
 University Of Central Florida (UCF)
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 Schaum's Outline of Statistics and Econometrics, Privatisation and Regulation: A Review of the Issues, An Essay on the Principle of Population (Oxford World's Classics), How I Became a Quant: Insights from 25 of Wall Street's Elite, Frequently Asked Questions in Quantitative Finance (Wiley Series in Financial Engineering)

Validity
School: UCF
Course: Applied Business Research Tools
12/2/2009 Applied Business Tools ECO 6416 Assessing Validity Validity of Studies Based on Multiple Regression Step back and take a broader look at regression: Is there a systematic way to assess/critique regression studies? strengths and pitfalls? 1 2

Exercisenormal Dist With Key
School: UCF
Course: Applied Business Research Tools
ECO 6416  Dr. Dickie  Exercise  Normal Distribution Normal Distribution Tables required for this exercise Problem 1. Scores on a recent national statistics exam were normally distributed with a mean of 80 and a standard deviation of 6. a. b. c. What is

What Is The Margin Of ErrorECO6416
School: UCF
Course: Applied Business Research Tools
What Is the Margin of Error? Estimation is the process by which sample data are used to indicate the value of an unknown quantity in a population. Results of estimation can be expressed as a single value, known as a point estimate; or a range of values, r

Analysis Of CovarianceComparing The SlopesECO6416
School: UCF
Course: Applied Business Research Tools
Analysis of Covariance: Comparing the Slopes Consider the following two samples of beforeandafter independent treatments. Values of Covariate X and a Dependent Variable Y Treatment I TreatmentII X Y X Y 5 11 2 1 3 9 6 7 1 5 4 3 4 8 7 8 6 12 3 2 We wis

Subjective Assessment Of Several Estimates Based On Relative PrecisionECO6416
School: UCF
Course: Applied Business Research Tools
Subjective Assessment of Several Estimates Based on Relative Precision In many cases, we may wish to compare several estimates of the same parameter. The simplest approach is to measure the closeness among the estimates in an attempt to determine that at

Estimations With ConfidenceECO6416
School: UCF
Course: Applied Business Research Tools
Estimations with Confidence In practice, a confidence interval is used to express the uncertainty in a quantity being estimated. There is uncertainty because inferences are based on a random sample of finite size from the entire population or process of i

Conditions And The Checklist For Linear ModelsECO6416
School: UCF
Course: Applied Business Research Tools
Conditions and the Checklist for Linear Models Almost all models of reality, including regression models, have assumptions that must be verified in order that the model has power to test hypotheses and for it to be able to predict accurately. The followi

Sample Size DeterminationECO6416
School: UCF
Course: Applied Business Research Tools
Sample Size Determination At the planning stage of a statistical investigation, the question of sample size (n) is critical. This is an important question therefore it should not be taken lightly. To take a larger sample than is needed to achieve the desi

Ratio Index NumbersECO6416
School: UCF
Course: Applied Business Research Tools
Ratio Index Numbers The following provides the computational procedures with applications for some Index numbers, including the Ratio Index, and Composite Index numbers. Suppose we are interested in the labor utilization of two manufacturing plants A and

Qualities Of A Good EstimatorECO6416
School: UCF
Course: Applied Business Research Tools
Qualities of a Good Estimator A "Good" estimator is the one which provides an estimate with the following qualities: Unbiasedness: An estimate is said to be an unbiased estimate of a given parameter when the expected value of that estimator can be shown t

How To Compare Two Correlation CoefficientsECO6416
School: UCF
Course: Applied Business Research Tools
How to Compare Two Correlation Coefficients? Given that two populations have normal distributions, we wish to test for the following null hypothesis regarding the equality of correlation coefficients: Ho: 1 = 2, based on two observed correlation coefficie

Revising The Expected Value And The VarianceECO6416
School: UCF
Course: Applied Business Research Tools
Revising the Expected Value and the Variance Averaging Variances: What is the mean variance of k variances without regard to differences in their sample sizes? The answer is simply: Average of Variances = [Si2] / k However, what is the variance of all k g

Introduction To EstimationECO6416
School: UCF
Course: Applied Business Research Tools
Introduction to Estimation To estimate means to esteem (to give value to). An estimator is any quantity calculated from the sample data which is used to give information about an unknown quantity in the population. For example, the sample mean is an estim

Correlation, And Level Of SignificanceECO6416
School: UCF
Course: Applied Business Research Tools
Correlation, and Level of Significance It is intuitive that with very few data points, a high correlation may not be statistically significant. You may see statements such as, correlation is significant between x and y at the = 0.005 level" and correlati

Residential Properties Appraisal ApplicationECO6416
School: UCF
Course: Applied Business Research Tools
Residential Properties Appraisal Application Estimating the market value of large numbers of residential properties is of interest to a number of socioeconomic stakeholders, such as mortgage and insurance companies, banks and realestate agencies, and inv

Bias Reduction TechniquesECO6416
School: UCF
Course: Applied Business Research Tools
Bias Reduction Techniques: Bootstrapping and Jackknifing Some inferential statistical techniques do not require distributional assumptions about the statistics involved. These modern nonparametric methods use large amounts of computation to explore the e

Introduction To Integrating Statistical ConceptsECO6416
School: UCF
Course: Applied Business Research Tools
Introduction to Integrating Statistical Concepts Statistical thinking for decisionmaking requires a deeper understanding than merely memorizing each isolated technique. Understanding involves ever expansion of neural network by means of correct connectiv

Numerical Examples For Statistical TablesECO6416
School: UCF
Course: Applied Business Research Tools
Numerical Examples for Statistical Tables The presentation of the statistical tables is not universal. Some statistical textbooks authors' enjoy given tabular values of the righttail probabilities, while for others lefttail probabilities are preferred.

Consumer Price IndexECO6416
School: UCF
Course: Applied Business Research Tools
Consumer Price Index The simplest and widely used measure of inflation is the Consumer Price Index (CPI). To compute the price index, the cost of the market basket in any period is divided by the cost of the market basket in the base period, and the resul

Applications Of And Conditions For Using Statistical TablesECO6416
School: UCF
Course: Applied Business Research Tools
Applications of and Conditions for Using Statistical Tables A problem with almost all statistical textbooks is that they not only do not provide information to understand connections between statistical tables. Students often ask: Why T table values with

Index Numbers And RatiosECO6416
School: UCF
Course: Applied Business Research Tools
Index Numbers and Ratios When facing a lack of a unit of measure, we often use indicators as surrogates for direct measurement. For example, the height of a column of mercury is a familiar indicator of temperature. No one presumes that the height of mercu

What Is Degrees Of FreedomECO6416
School: UCF
Course: Applied Business Research Tools
What Is "Degrees of Freedom"? Recall that in estimating the population's variance, we used (n1) rather than n, in the denominator. The factor (n1) is called "degrees of freedom." Estimation of the Population Variance: Variance in a population is defined

Relationships Among Distributions And Unification Of Statistical TablesECO6416
School: UCF
Course: Applied Business Research Tools
Relationships among Distributions and Unification of Statistical Tables Particular attention must be paid to a first course in statistics. When I first began studying statistics, it bothered me that there were different tables for different tests. It took

An Illustration Of CLTECO6416
School: UCF
Course: Applied Business Research Tools
An Illustration of CLT Sampling Distribution of the Sample Means: Instead of working with individual scores, statisticians often work with means. What happens is that several samples are taken, the mean is computed for each sample, and then the means are

Regression Modeling And AnalysisECO6416
School: UCF
Course: Applied Business Research Tools
Regression Modeling and Analysis Many problems in analyzing data involve describing how variables are related. The simplest of all models describing the relationship between two variables is a linear, or straightline, model. Linear regression is always l

What Is The Central Limit TheoremECO6416
School: UCF
Course: Applied Business Research Tools
What Is The Central Limit Theorem? The central limit theorem (CLT) is a "limit" that is "central" to statistical practice. For practical purposes, the main idea of the CLT is that the average (center of data) of a sample of observations drawn from some po

Regression Analysis, AVONA, And Chisquare TestECO6416
School: UCF
Course: Applied Business Research Tools
Regression Analysis, ANOVA, and Chisquare Test There are close relationships among linear regression, analysis of variance and the Chisquare test. To illustrate the relationship, consider the following application: Relationship between age and income in

Joint Probability And StatisticsECO6416
School: UCF
Course: Applied Business Research Tools
Joint Probability and Statistics A joint probability distribution of a group of random variables is the distribution of group of variables as a whole. Applied business statistics deal mostly with the joint probability distribution of two discrete random v

Hypothesis Testing With ConfidenceECO6416
School: UCF
Course: Applied Business Research Tools
Hypothesis Testing with Confidence One of the main advantages of constructing a confidence interval (CI) is to provide a degree of confidence for the point estimate for the population parameter. Moreover, one may utilize CI for the test of hypothesis purp

What Is A Sampling DistributionECO6416
School: UCF
Course: Applied Business Research Tools
What Is A Sampling Distribution? A sampling distribution describes probabilities associated with a statistic when a random sample is drawn from the entire population. The sampling distribution is the density (for a continuous statistic, such as an estimat

Hypothesis TestingRejecting A ClaimECO6416
School: UCF
Course: Applied Business Research Tools
Hypothesis Testing: Rejecting a Claim To perform a hypothesis test, one must be very specific about the test one wishes to perform. The null hypothesis must be clearly stated, and the data must be collected in a repeatable manner. If there is any subjecti

Test For NormalityECOC6416
School: UCF
Course: Applied Business Research Tools
Test for Normality The standard test for normality is the Lilliefors' statistic. A histogram and normal probability plot will also help you distinguish between a systematic departure from normality when it shows up as a curve. Lilliefors' Test for Normali

Pearson, Spearman, And PointBiserial CorrelationsECO6416
School: UCF
Course: Applied Business Research Tools
Pearson, Spearman, and PointBiserial Correlations There are measures that describe the degree to which two variables are linearly related. For the majority of these measures, the correlation is expressed as a coefficient that ranges from 1.00 to 1.00. A

Poisson Probability FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Poisson Probability Function Life is good for only two things, discovering mathematics and teaching mathematics.  Simeon Poisson An important class of decision problems under uncertainty is characterized by the small chance of the occurrence of a particu

Normal Density FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Normal Density Function In the Descriptive Statistic Section of this Web site, we have been concerned with how empirical scores are distributed and how best to describe their distribution. We have discussed several different measures, but the mean will be

Multinomial Probability FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Multinomial Probability Function A multinomial random variable is an extended binomial. However, the difference is that in a multinomial case, there are more than two possible outcomes. There are a fixed number of independent outcomes, with a given probab

Chisquare Density FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Chisquare Density Function The probability density curve of a Chisquare distribution is an asymmetric curve stretching over the positive side of the line and having a long right tail. The form of the curve depends on the value of a parameter known as th

Regression Modeling Selection ProcessECO6416
School: UCF
Course: Applied Business Research Tools
Regression Modeling Selection Process When you have more than one regression equation based on data, to select the best model", you should compare: 1. Rsquares: That is, the percentage of variance [in fact, the sum of squares] in Y accounted for by varia

Bayesian Statistical InferenceECO6416
School: UCF
Course: Applied Business Research Tools
Bayesian Statistical Inference: An Introduction Statistical inference describes the procedures by which we use the observed data to draw conclusions about the population from which the data came or about the process by which the data were generated. Our a

Blending The Classical And The Pvalue Based Approaches In Test Of HypothesesECO6416
School: UCF
Course: Applied Business Research Tools
Blending the Classical and the Pvalue Based Approaches in Test of Hypotheses A pvalue is a measure of how much evidence you have against the null hypothesis. Notice that the null hypothesis is always in = form, and does not contain any forms of inequali

Parametric Vs. NonParametric Vs. Distributionfree TestsECO6416
School: UCF
Course: Applied Business Research Tools
Parametric vs. NonParametric vs. Distributionfree Tests One must use a statistical technique called nonparametric if it satisfies at least one of the following five types of criteria: 1. The data entering the analysis are enumerative; that is, counted

Test For Equality Of Several Population MediansECO6416
School: UCF
Course: Applied Business Research Tools
Test for Equality of Several Population Medians Generally, the median provides a better measure of location than the mean when there are some extremely large or small observations; i.e., when the data are skewed to the right or to the left. For this reaso

GoodnessofFit Test For Probability Mass FunctionsECO6416
School: UCF
Course: Applied Business Research Tools
GoodnessofFit Test for Probability Mass Functions There are other tests that might use the Chisquare, such as goodnessoffit test for discrete random variables. Therefore, Chisquare is a statistical test that measures "goodnessoffit". In other word

2 By 2 Crosstable AnalysisECO6416
School: UCF
Course: Applied Business Research Tools
2 by 2 Crosstable Analysis Using Chisquare in a 2x2 table requires the Yates's correction. One first subtracts 0.5 from the absolute differences between observed and expected frequencies for each of the three genotypes before squaring, dividing by the ex

Distributionfree Equality Of Two PopulationsECO6416
School: UCF
Course: Applied Business Research Tools
Distributionfree Equality of Two Populations For statistical equality of two populations, one may use the KolmogorovSmirnov Test (KS Test) for two populations. The KS test seeks differences between the two population's distribution function based on t

Student TDensity FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Student TDensity Function The t distributions were discovered in 1908 by William Gosset, who was a chemist and a statistician employed by the Guinness brewing company. He considered himself a student still learning statistics, so that is how he signed hi

Testing The VarianceECO6416
School: UCF
Course: Applied Business Research Tools
Testing the Variance: Is the Quality that Good? Suppose a population has a normal distribution. The manager is to test a specific claim made about the quality of the population by way of testing its variance 2. Among three possible scenarios, the interest

Triangular Density FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Triangular Density Function The triangular distribution shows the number of successes when you know the minimum, maximum, and most likely values. For example, you could describe the number of intakes seen per week when past intake data show the minimum, m

Managing The Producer's Or The Consumer's RiskECO6416
School: UCF
Course: Applied Business Research Tools
Managing the Producer's or the Consumer's Risk The logic behind a statistical test of hypothesis is similar to the following logic. Draw two lines on a paper and determine whether they are of different lengths. You compare them and say, "Well, certainly t

Test For RandomnessECO6416
School: UCF
Course: Applied Business Research Tools
Test for Randomness: The Runs' Test A basic condition in almost all inferential statistics is that a set of data constitutes a random sample from a given homogeneous population. The condition of randomness is essential to make sure the sample is truly rep

Covariance And CorrelationECO6416
School: UCF
Course: Applied Business Research Tools
Covariance and Correlation Suppose that X and Y are two random variables for the outcome of a random experiment. The covariance of X and Y is defined by Cov (X, Y) = Ecfw_[X  E(X)][Y  E(Y)] and, given that the variances are strictly positive, the correl

What Is A Standard ErrorECO6416
School: UCF
Course: Applied Business Research Tools
What Is a Standard Error? For statistical inference, namely statistical testing and estimation, one needs to estimate the population's parameter(s). Estimation involves the determination, with a possible error due to sampling, of the unknown value of a po

Homogeneous PopulationECO6416
School: UCF
Course: Applied Business Research Tools
Homogeneous Population A homogeneous population is a statistical population which has a unique mode. Notice that, e.g., a Uniform distribution has uncountable number of modes having equal density value; therefore it is considered as a homogeneous populati

Regression Analysis, AVONA, Ttest, And Coefficient Of DeterminationECO6416
School: UCF
Course: Applied Business Research Tools
Regression Analysis, ANOVA, Ttest, and Coefficient of Determination There are very direct relationships among linear regression, analysis of variance, ttest and the coefficient of determination. The following small data set is for illustrating the conne

Measure Of Surprise For Outlier DetectionECO6416
School: UCF
Course: Applied Business Research Tools
Measure of Surprise for Outlier Detection Robust statistical techniques are needed to cope with any undetected outliers; otherwise they are more likely to invalidate the conditions underlying statistical techniques, and they may seriously distort estimate

Simple Linear RegressionCoumputional AspectsECO6416
School: UCF
Course: Applied Business Research Tools
Simple Linear Regression: Computational Aspects The regression analysis has three goals: predicting, modeling, and characterization. What would be the logical order in which to tackle these three goals such that one task leads to and /or and justifies the

Uniform Density FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Uniform Density Function The uniform density function gives the probability that observation will occur within a particular interval [a, b] when probability of occurrence within that interval is directly proportional to interval length. Its mean and varia

Correlation Coefficients TestingECO6416
School: UCF
Course: Applied Business Research Tools
Correlation Coefficients Testing The Fisher's Ztransformation is a useful tool in the circumstances in which two or more independent correlation coefficients are to be compared simultaneously. To perform such a test one may evaluate the Chisquare statis

Necessary Conditions For Statistical Decision MakingECO6416
School: UCF
Course: Applied Business Research Tools
Necessary Conditions for Statistical Decision Making Introduction to Inferential Data Analysis Necessary Conditions: Do not just learn formulas and numbercrunching. Learn about the conditions under which statistical testing procedures apply. The followin

Testing The Equality Of MultiVariancesECO6416
School: UCF
Course: Applied Business Research Tools
Testing the Equality of MultiVariances The equality of variances across populations is called homogeneity of variances or homoscedasticity. Some statistical tests, such as testing equality of the means by the ttest and ANOVA, assume that the data come f

Seasonal Index And Deseasonalizing DataECO6416
School: UCF
Course: Applied Business Research Tools
Seasonal Index and Deseasonalizing Data Seasonal index represents the extent of seasonal influence for a particular segment of the year. The calculation involves a comparison of the expected values of that period to the grand mean. We need to get an estim

3describing DataSTUDENTS REVIEW THIS
School: UCF
Course: Applied Business Research Tools
Statistical Statistical Methods for Business DecisionDecisionMaking Describing Data Week #1 Page 1 Describing Data This section is a brief review of some simple concepts REVIEW on your own REVIEW on your own Page 2 InClass Exercise Exercise 1 See the ha

Next Multiple Regression
School: UCF
Course: Applied Business Research Tools
Example Does school quality affect housing prices? Other things equal, are houses worth more when located in zones for better schools? Economic framework: hedonic model for prices of goods that are bundles of characteristics. Price of house viewed as a f

Regression Analysi1
School: UCF
Course: Applied Business Research Tools
Sca t t e r pl ot of Av e r a ge e x a mgr a de v sN umbe r of hour sst udi e dpe r w e e 120 100 A v e r a ge e xa mgr a de 80 60 40 20 0 0 10 20 30 40 50 60 Numbe r of hour sst udie dpe r w e e 70 80 Regression Analysis: Average exam gra versus Number o

Topic 1Research Design
School: UCF
Course: Applied Business Research Tools
Topic #1 Research Design Applications Applications in Business and Economics Data Data Types of Data Data Data Sources Sampling Sampling Techniques Steps Steps of Research Slide 1 Form Your Team By End of 2nd Class! Slide 2 Applications in Business and Ec

Topic 2Basic StatisticsPart 1
School: UCF
Course: Applied Business Research Tools
Topic #2 Basic Statistics Part 1 REVIEW REVIEW ON OWN Summarizing Qualitative Data Summarizing Quantitative Data Measures of Location and Variability/Dispersion Measures Measures of Association Between Two Variables Random Random Variables Discrete Discre

Topic 3Statistical Inference
School: UCF
Course: Applied Business Research Tools
Topic #3 Statistical Inference Point Estimation Sampling Distribution of x o Sampling Distribution of p Not on Exam 1 o H pothesis Testing Hy o Interval Estimation Not on Exam 1 o o Form Your Team By End of 2nd Class! Slide 1 Slide 2 Statistical Inference

Topic 4  Intro To Multiple Regression Student Version
School: UCF
Course: Applied Business Research Tools
Outline Applied Business Tools ECO ECO 6416 Introduction to Multiple Regression 1. 1. 2. 3. 4. 5. 6. 7. 7. Omitted variable bias Causality and regression analysis Multiple regression and OLS Measures of fit Sampling distribution of the OLS estimator Hypot

Try To Be Normal, Z
School: UCF
Course: Applied Business Research Tools
Topic #2 Basic Statistics Part 2 Measures of Relative Location Zscores Continuous Probability Distributions o o Measures of Relative Location o o zScores The Empirical Rule NOTE: gives you an idea/sense of how values and probabilities are spread over th

Study Questions For Exam 1ECO 6416
School: UCF
Course: Applied Business Research Tools
Study Questions for Exam 1: 1.4 Which of the following is an example of time series data? a. job satisfaction of 100 employees at a factory b. the fiveyear growth rate in sales of 30 foodprocessing firms c. 1990 revenue for each fast food restaurant in

ECO 6416Exam 1 Review
School: UCF
Course: Applied Business Research Tools
ECO 6416 EXAM #1 Review Multiple Choice Place answers on Scantron form. Write in this booklet instead of scratch paper. Put name at top. Answer the next nine questions from the following case: By fitting membership with alumni total for n = 48 months, the

ECO6416 Transcript Of Live Chat
School: UCF
Course: Applied Business Research Tools
ECO6416 Exam 1 Live Chat Transcripts (use with Exam 1 Review guide) 9:15 PM: Dr. Soskin: Welcome all. I'm sitting here with my seafood salad and arugula sandwich on rye and a glass of iced tea (not sweet). So ready for questions. 9:16 PM: Avila Oriana: I

Why Statistical SamplingECO6416
School: UCF
Course: Applied Business Research Tools
Why Statistical Sampling? Sampling is the selection of part of an aggregate or totality known as population, on the basis of which a decision concerning the population is made. The following are the advantages and/or necessities for sampling in statistica

What Is So Important About The Normal DistributionsECO6416
School: UCF
Course: Applied Business Research Tools
What Is so Important About the Normal Distributions? The term normal" possibly arose because of the various attempts made to establish this distribution as the underlying rule governing all continuous variables. These attempts were based on false premises

Multiple Regression Exercise
School: UCF
Course: Applied Business Research Tools
Thisexerciseconcernsregressionsusedtomodelhourlyearningsofworkersasafunctionofcharacteristicsofthe workers.Theunitofobservationistheworker,andthedataincludeobservationson61,395workersfromtheMarch 2005CurrentPopulationSurvey. Thevariablesare: Ahe = Average

Intro%20to%20Multiple%20Regression%20MD%20verstion
School: UCF
Course: Applied Business Research Tools
Outline Applied Business Tools ECO ECO 6416 Introduction to Multiple Regression 1. 1. 2. 3. 4. 5. 6. 7. 7. Omitted variable bias Causality and regression analysis Multiple regression and OLS Measures of fit Sampling distribution of the OLS estimator Hypot

HW Exerregr2 Var
School: UCF
Course: Applied Business Research Tools
Applied Business Research Tools TwoVariable Regression Exercise You are planning to buy a 1000 sq. foot house in one of two subdivisions. The regression results from these two subdivisions are presented below. PRICE is the sales price of a house and lot

BinomPoisson Exercises  Students
School: UCF
Course: Applied Business Research Tools
ECO 6416  Dr. Dickie  Exercise  Binomial and Poisson Distributions Problems 1. Twentyfive percent of the employees of a large company are members of minorities. A random sample of 7 employees is selected. a. What is the probability that the sample con

BinomPoisson Exercises  With Key
School: UCF
Course: Applied Business Research Tools
ECO 6416  Dr. Dickie  Exercise  Binomial and Poisson Distributions Problems 1. Twentyfive percent of the employees of a large company are members of minorities. A random sample of 7 employees is selected. a. What is the probability that the sample con

Bivariate Regression Student Version
School: UCF
Course: Applied Business Research Tools
ECO 6416 Bivariate Regression Statistical model to study relationship between dependent variable and one or more independent variables. Flexible modeling approach Widely used statistical method in business & economics Can do anything that analysis of vari

Cigarette Demand Inclass Exercise
School: UCF
Course: Applied Business Research Tools
Thisexerciseconcernsregressionsusedtoestimatethedemandforcigarettes.Theunitofobservationisthestate.Variablesare observedinthe48continuousUSstatesfortwoyears,1985and1995.Thevariablesare: PACKPC = Annual percapita cigarette consumption by state and year, i

Cigarette Demand Log Form Exercise
School: UCF
Course: Applied Business Research Tools
Thisexerciseconcernsregressionsusedtoestimatethedemandforcigarettes.Theunitofobservationisthestateinagivenyear. Variablesareobservedinthe48continuousUSstatesfortwoyears,1985and1995.Theregressionmodelis ln Qit = 0 + 1 ln Pit + 2 ln I it + uit . Inthisequat

Class 1 Inclass Exercise 1
School: UCF
Course: Applied Business Research Tools
ECO 6416  Dr. Dickie InClass Exercise Class #1 Suppose youve collected data on 40 southern universities and their athletic departments. Some of the data that youve collected are defined below. MARGIN  net annual revenue or loss (gross revenue  expense

Consumer Complaints
School: UCF
Course: Applied Business Research Tools
Statistical Methods for Business DecisionMaking Describing Data Exercise #1 (Consumer Complaints) Purpose: illustrate how the mean and standard deviation can answer important business questions. Instructions: Do this exercise in groups of two (or as home

Correcting Heteroskedasticity
School: UCF
Course: Applied Business Research Tools
Correcting Heteroskedasticity Step 1: Using the five original independent variables, we estimate a regression model. Step 2: Computing the residual RES(in MINITAB, create a new variable by using feature RESIDUAL in Storage when running regression model) a

Estimation With Key
School: UCF
Course: Applied Business Research Tools
ECO 6416  Dr. Dickie  Exercise Point & Interval Estimation, Hypothesis Testing Firstdeterminewhetheryouneedtoconstructanintervalestimateortoconductahypothesistest.The formulaforanintervalestimatoris: Point estimate (critical value) (s.e. of point est

Exerwrite HO & HAKEY
School: UCF
Course: Applied Business Research Tools
Purpose: Practice writing hypotheses and using pvalues to make decisions 1. 2. 3. You have been assigned to learn whether or not lung cancer rates differ between smokers and nonsmokers. After you conduct your testing, your test statistics pvalue is 0.00

Hetero And Serial Corr
School: UCF
Course: Applied Business Research Tools
Heteroskedasticity & Serial Correlation Heteroskedasticity * * * * * * * * * * * * * * * * * * * * * * * * * * * * * Slide # 1 Slide # 2 Heteroskedasticity & Serial Correlation are Sneaky Can mess up tstatistics so badly that you might reach wrong concl

HW Exerregr2 Var KEY
School: UCF
Course: Applied Business Research Tools
Applied Business Research Tools TwoVariable Regression Exercise You are planning to buy a 1000 sq. foot house in one of two subdivisions. The regression results from these two subdivisions are presented below. PRICE is the sales price of a house and lot

Statistical SummariesECO6416
School: UCF
Course: Applied Business Research Tools
Statistical Summaries Representative of a Sample: Measures of Central Tendency Summaries How do you describe the average" or typical" piece of information in a set of data? Different procedures are used to summarize the most representative information dep

Specialized AveragesECO6416
School: UCF
Course: Applied Business Research Tools
Specialized Averages: The Geometric & Harmonic Means The Geometric Mean: The geometric mean (G) of n nonnegative numerical values is the nth root of the product of the n values. If some values are very large in magnitude and others are small, then the ge

Shape Of A Distribution FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Shape of a Distribution Function: The SkewnessKurtosis Chart The pair of statistical measures, skewness and kurtosis, are measuring tools, which is used in selecting a distribution(s) to fit your data. To make an inference with respect to the population

Two Independent PopulationsECO6416
School: UCF
Course: Applied Business Research Tools
Two Independent Populations If an estimate is an unbiased such as sample mean, then it is a good idea to pool the estimates to get a single estimate from several relatively small samples. The pooled estimate is a good estimate when compared with each indi

Nonparametic Multiple Comparison ProceduresECO6414
School: UCF
Course: Applied Business Research Tools
Nonparametric Multiple Comparison Procedures Duncan's multiplerange test: This is one of the many multiple comparison procedures. It is based on the standardized range statistic by comparing all pairs of means while controlling the overall Type I error

FDensity FunctionECO6416
School: UCF
Course: Applied Business Research Tools
FDensity Function The Fdistribution is the distribution of the ratio of two independent sampling (of size of n1, and n2, respectively) estimates of variance from standard normal distributions. It is also formed by the ratio of two independent chisquare

Introduction To Tests For Statistical Equality Of Two Or More PopulationsECO6416
School: UCF
Course: Applied Business Research Tools
Introduction to Tests for Statistical Equality of Two or More Populations: Two random variables X and Y having distribution FX(x) and FY(y) respectively, are said to be equivalent, or equal in rule, or equal in distribution, if and only if they have the s

Exponential Density FunctionECO6416
School: UCF
Course: Applied Business Research Tools
Exponential Density Function An important class of decision problems under uncertainty concerns the random durations between events. For example, the the length of time between breakdowns of a machine not exceeding a certain time interval, such as the cop

Equality Of Two Normal PopulationsECO6416
School: UCF
Course: Applied Business Research Tools
Equality of Two Normal Populations: The normal or Gaussian distribution is a continuous symmetric distribution that follows the familiar bellshaped curve. One of its nice features is that, the mean and variance uniquely and independently determines the d

Hypergeometric DistributionECO6416
School: UCF
Course: Applied Business Research Tools
Hypergeometric Distribution The Hypergeometric (x; n, M, N) Distribution applies when we are sampling n items without replacement from a population of M successes and NM failures. The hypergeometric distribution arises when a random selection (without re

An Illustrative Numerical Example For ANOVAECO6416
School: UCF
Course: Applied Business Research Tools
An Illustrative Numerical Example for ANOVA Consider the following (small integers, indeed for illustration while saving space) random samples from three different populations. With the null hypothesis: H0: 1 = 2 = 3, and the alternative: Ha: at least two