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An in­tro­duc­tory course in sta­tis­tics and prob­a­bil­ity. Top­ics cov­ered in­clude de­scrip­tive sta­tis­tics, sam­ple spaces and prob­a­bil­i­ties, dis­crete prob­a­bil­ity dis­tri­b­u­tions (Bi­no­mial, Hy­per­ge­o­met­ric), ex­pec­ta­tion and vari­ance, con­tin­u­ous prob­a­bil­ity dis­tri­b­u­tions (Nor­mal, Stu­dent, Chi-Square), con­fi­dence in­ter­vals, hy­poth­e­sis test­ing, and cor­re­la­tion and lin­ear re­gres­sion. Spread­sheets are used through­out the se­mes­ter.

An introductory course in statistics and probability. Topics covered include descriptive statistics, sample spaces and probabilities, discrete probability distributions (Binomial, Hypergeometric), expectation and variance, continuous probability distributions (Normal, Student, Chi-Square), confidence intervals, hypothesis testing, and correlation and linear regression. Spreadsheets are used throughout the semester.

In­tern­ship with the Walt Dis­ney Com­pany, Or­lando Florida

Internship with the Walt Disney Company, Orlando Florida

A 3 credit but 4 hour in­tro­duc­tory course. Top­ics in­clude sam­ple space, ex­pec­ta­tion and vari­ance, bi­no­mial, Pois­son, nor­mal, stu­dent and chi-square dis­tri­b­u­tions, con­fi­dence in­ter­val, hy­poth­e­sis test­ing, cor­re­la­tion and re­gres­sion. Stu­dents do 3 pro­jects, 1 in­di­vid­ual and 2 in groups and choose one of the group pro­jects to pre­sent at the end of the se­mes­ter. The extra class­room hour is de­signed to fa­cil­i­tate a hands-on feel to the course in­clud­ing a heavy use of MS Excel.

A 3 credit but 4 hour introductory course. Topics include sample space, expectation and variance, binomial, Poisson, normal, student and chi-square distributions, confidence interval, hypothesis testing, correlation and regression. Students do 3 projects, 1 individual and 2 in groups and choose one of the group projects to present at the end of the semester. The extra classroom hour is designed to facilitate a hands-on feel to the course including a heavy use of MS Excel.

An in­tro­duc­tory course in sta­tis­tics and prob­a­bil­ity. Top­ics cov­ered in­clude de­scrip­tive sta­tis­tics, sam­ple spaces and prob­a­bil­i­ties, dis­crete prob­a­bil­ity dis­tri­b­u­tions (Bi­no­mial, Hy­per­ge­o­met­ric), ex­pec­ta­tion and vari­ance, con­tin­u­ous prob­a­bil­ity dis­tri­b­u­tions (Nor­mal, Stu­dent, Chi-Square), con­fi­dence in­ter­vals, hy­poth­e­sis test­ing, and cor­re­la­tion and lin­ear re­gres­sion. Spread­sheets are used through­out the se­mes­ter.

An introductory course in statistics and probability. Topics covered include descriptive statistics, sample spaces and probabilities, discrete probability distributions (Binomial, Hypergeometric), expectation and variance, continuous probability distributions (Normal, Student, Chi-Square), confidence intervals, hypothesis testing, and correlation and linear regression. Spreadsheets are used throughout the semester.

A con­tin­u­a­tion of Cal­cu­lus I (i.e., MAT 1475). The course be­gins with in­te­gra­tion: de­f­i­n­i­tion of def­i­nite and in­def­i­nite in­te­grals, the Fun­da­men­tal The­o­rem of Cal­cu­lus, tech­niques of in­te­gra­tion, im­proper in­te­grals, and ap­pli­ca­tions of in­te­grals to areas, vol­umes and arc lengths. The lat­ter half of the course cov­ers Tay­lor poly­no­mi­als, the Mean Value The­o­rem, in­fi­nite se­quences and se­ries, tests of con­ver­gence, and Tay­lor se­ries.

A continuation of Calculus I (i.e., MAT 1475). The course begins with integration: definition of definite and indefinite integrals, the Fundamental Theorem of Calculus, techniques of integration, improper integrals, and applications of integrals to areas, volumes and arc lengths. The latter half of the course covers Taylor polynomials, the Mean Value Theorem, infinite sequences and series, tests of convergence, and Taylor series.