statistics course syllabus

Logistic regression, multiple linear regression, and one- and Based on the Understanding by Design (Wiggins and McTighe) model, this course framework provides a clear and detailed description of the course requirements necessary for student success. Elementary probability theory, basic concepts of statistical inference, regression and correlation methods, and sample size estimation are covered. Using R, we will study and practice the following methodologies: data cleaning, feature extraction; web scrubbing, text analysis; data visualization; fitting statistical models; simulation of probability distributions and statistical models; statistical inference methods that use simulations (bootstrap, permutation tests). The techniques will be studied critically, with examination of their usefulness and limitations. Describe the random processes underlying statistical studies. Individual study. WebSampling distributions. Applied Probability (3) Prerequisites: Mathematics 151 and 254. Understand the difference between probability and likelihood functions, and find the maximum likelihood estimate for a model parameter. Credit for 596 and 696 applicable to a masters An intensive study in advanced statistics. I = Introduced; R = Reinforced; A = Assessed, Office of the University Registrar compute various measures of centre, variability and position of data sets. May be repeated with new content. conditional probability and Bayes theorem, moments, properties of expectation and Regression methods for decomposition models, trends and seasonality, spectral analysis, distributed lag models, autoregressive-moving average modeling, forecasting, exponential smoothing, and ARCH and GARCH models will be surveyed. The AP Statistics framework included in the course and exam description outlines distinct skills that students should practice throughout the yearskills that will help them learn to think and act like statisticians. Actuarial models and applications of probability and statistics to insurance and other One- and two-sample hypothesis tests, paired difference tests, tests for variances, Data Mining Statistical Methods (3) Prerequisites: Statistics 610 and 670B with a grade of B (3.0) or better in each course. Welcome to the Pre-MBA Statistics course! Time Series Analysis (3) Prerequisite: Statistics 551B or 670B. The techniques will be studied critically, with examination of their usefulness and limitations. Non-actuaries will be introduced to practical applications of finance mathematics, such as loan amortization and bond pricing, and premium calculation of typical life insurance contracts. The course is abundantly illustrated by examples from the insurance and finance literature. Conceptual foundations are addressed as well as hands-on use for data analysis. Welcome to the Pre-MBA Statistics course! 1-6 Credits. This course may be taken concurrently with the prerequisite with instructor permission. Statistics majors learn how to design studies that effectively address the purpose of a research project and how to properly analyze the data collected in such studies. of four units for the two (or more) courses: Statistics 250; Administration, Rehabilitation and selected topics. The course will introduce data analysis from the Bayesian perspective to undergraduate students. Prerequisite: STAT 7700 or 7050 or equivalent background acquired through a combination of online courses that teach the R language and practical experience. B.Sc Statistics syllabus includes core subjects such as calculus, algebra, probability and statistical methods, applied statistics, survey sampling, and many more. As always, you have the flexibility to organize the course content as you like. Prerequisites: STAT 4300 AND STAT 4310 AND MATH 2400. Matrix formulations of regression models. STAT 696. Registration in this course includes electronic textbooks. Causal inference is the subfield of statistics that considers how we should make inferences about such questions. models, repeated measures and longitudinal data analysis, generalized linear models, This course will cover the design and analysis of sample surveys. STAT 575. How are these things related? Prepare for the 2022 AP Statistics Exam. Questions about cause are at the heart of many everyday decisions and public policies. Practicum in Teaching of Statistics (1) Cr/NC Prerequisite: Award of graduate teaching associateship in statistics. Seminar (1-3) Prerequisite: Consent of instructor. This course may be taken concurrently with the prerequisite with instructor permission. This document details the updates made to the course and exam description (CED) in March 2021. It begins with an in-depth 3 Credits. Using examples from the upcoming election, the pandemic and other topics, we will critically examine both well-accepted and controversial claims. The course is structured in two parts. In particular it introduces automated model selection tools, such as stepwise regression and various current model selection criteria such as AIC and BIC. Recommendations: Prior exposure to programming and/or software suchas R or SAS, as Nonparametric procedures. Heuristics WebThis second course in business statistics focuses on widely used data analysis techniques in business and economics. Prob & Stat For Cs. Students completing the course will be able to: You must do the reading and answer reading questions before each class, as lectures will be given under the assumption that you have completed the reading. A minimum GPA of 2.0 must be achieved on all attempts of core and major elective courses and 2.67 on MAC2312 and MAC2313. Credit is not given for STAT 101 for majors in Mathematics and Computer Science. Autocorrection functions, stationary and nonstationary time Basic statistical inference procedures of estimation, confidence intervals and hypothesis testing directed towards applications in science and medicine. Discrete and continuous random variables and their distributions. Class sessions will be a blend of lecture, concept questions and group problem solving. Stat 216 is designed to engage you in the statistical investigation process from developing a research question and data collection methods to analyzing and communicating results. You can download the syllabus in statistics for management pdf form. and medicine. and correlation. Web2,511 recent views. STAT 580. Topics discussed include displaying and describing data, the normal curve, regression, probability, statistical inference, confidence intervals, and hypothesis tests with applications in the real world. While the context will be sports related, the skills and techniques gained will be widely applicable and generalizable with applications in diverse areas. Title: Statistics and Research Methods sign and Wilcoxon tests, and corresponding nonparametric point and interval estimators. Chi-square tests. It allows students to bring their existing knowledge from different disciplines to bear on new problems. 296, 496, 596 courses applicable to a bachelors degree. Distribution of random variables, characteristic functions, limiting distributions, To learn more about assignments and examinations, please refer to Athabasca Universitys online Calendar. 3 Years. The use of the JMP statistical package. variance and regression problems, sequential techniques, decision theory. 6 Weeks Access / 24 Course Hrs. Sampling . Selected Topics in Statistics (3) Prerequisite: Graduate Standing. Does eating an egg every day cause people to live longer or shorter or have no effect? Unit 4: Estimation and Tests of Hypotheses for One Population, Unit 5: Tests of Hypotheses for Two or More Populations. Familiarity with basic probability models is helpful but not presumed. Students with credit or concurrent registration in the following lower division statistics It can also be taken by others interested in the mathematics of personal finance and the use of mortality tables. Stat for Behav Scien II. Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results, Increase your quantitative reasoning skills through a deeper understanding of probability and statistics. The second part of the course is about "Platforms" and goes into the practicalities of the implementation of the different strategies. This online test contains 70 questions that will help you assess your mathematical skills. The compound model is then used to establish the distribution of losses. courses other than Statistics 250 will be awarded a total of four units for the two Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. Text mining especially through PCA is another topic of the course. This course may be taken concurrently with the prerequisite with instructor permission. AP Stats B is the second half of the course and includes Modules 5 8. May be repeated with new content. Required courses cover the material for the beginning examinations and VEE credits leading to an associateship in the major national actuarial societies. Monte Carlo and simulation intensive methods for development and application of statistical The objective of the course is to teach students the core data mining skills of exploratory data analysis, selecting an appropriate statistical methodology, applying the methodology to the data, and interpreting the results. and life tables; life insurance, annuities and benefits. It introduces large sample theory, asymptotic efficiency Course hours: Two lectures and two hours of activity. Preparation of a project or thesis for the masters degree. 6 Weeks Access / 24 Course Hrs. BSc Statistics Syllabus equips students to work as Statistician, Market Research Analysts, Technical Writers, Consultant, Biostatistician, Content Analyst, This course introduces you to some aspects of descriptive and inferential statistics. Demonstration Cross Tabulation problems and solutions. Bayes Theorem, Inference about a Population Mean and t-distributions, Inference about Two Population Proportions. At the end of this course, students should be able to: Formulate a statistical problem in mathematical terms from a real-life situation. Prerequisite: STAT 5030, 7050, or 7700 or equivalent background acquired through a combination of online courses that teach the R language and practical experience. Multiple regression, factorial models and nonparametric methods, all with emphasis Given the data science perspective of this course, this is focused on web enabled approaches. An introductory level course for non-mathematics majors who need or desire a working knowledge of statistics. Selected topics in statistics. STAT 678. Improve your understanding of data and learn how to develop graphs and charts. Main topics include annuities, loans and bonds; basic principles of life contingencies and determination of annuity and insurance benefits and premiums. Unit 1: Introduction To Statistics: Overview, origin and development and managerial applications of statistics and branches of the study, statistics, and computers, limitations of statistics. Courses such as Stat 4050 or Stat 4770 would meet this requirement. This course will cover the key concepts and methods of causal inference rigorously. The main objectives of a statistician would be to procure data that is useful for various fields to be able to make predictions based on the obtained data. Unit guides clearly lay out the course content and skills and recommend sequencing and pacing for them throughout the year. This course does not have business applications but has significant overlap with STAT 1010 and 1020. Prerequisites: Must be a declared Statistics Concentrator or Business Analytics Concentrator or Statistics Minor or Data Science Minor. Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. Design, conduct, and analysis of experimental and observational studies including This course is recommended for those considering a statistics and data science concentration or minor, as well as anyone interested in a more challenging introductory approach to statistical concepts. Prerequisite: Two courses at the statistics 4000 or 5000 level. Inference for categorical data: Chi-square. perform goodness-of-fit tests and analyse cross-tabulated data. of methods with R, SAS, and SPSS software. on applications. STAT 119. Prepare for further coursework or on-the-job study. Short-term consulting to campus clients With the increasing digitization and networking of society, data have become ever more ubiquitous, further expanding the demand for statisticians and their expertise in the collection and analysis of data. designs, fractional factorial experiments, response surface methods, selected topics. Spring 2021 Syllabus Fall 2020 Syllabus Fall 2019 Students will learn to apply these methods in a wide range of settings such as marketing and finance, and will gain hands-on experience through class assignments and competitions. This course makes use of discussion boards, which can be a great resource for helping each other understand the material and problem sets. also student must be registered in the course when the completed thesis is granted WebThis course is suitable for a variety of professionals and students intending to start their journey in data and statistics-driven roles such as Data Scientists, Data Analysts, Business Analysts, Statisticians, and Researchers. Find credible intervals for parameter estimates. Descriptive statistics, data displays, measures of central tendency and variability, May be repeated with new content. Know what expectation and variance mean and be able to compute them. STAT 702. Causal Diagrams: Draw Your Assumptions Before Your Conclusions, Statistical Inference and Modeling for High-throughput Experiments, Introduction to Linear Models and Matrix Algebra, Principles, Statistical and Computational Tools for Reproducible Data Science, Fat Chance: Probability from the Ground Up. Discrete and continuous random variables, probability mass functions and density functions, Special Study (1-3) Cr/NC/RP Prerequisite: Consent of staff; to be arranged with department chair and instructor. Based on your score we will recommend which Athabasca University mathematics course you are likely ready to take successfully. Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. content. Statistics I. STA 3112. Courses offered by other delivery methods may vary from their individualized study counterparts. Prerequisite: Waiving the Statistics Core completely if prerequisites are not met. applications of the linear hypothesis, invariance and unbiasedness to analysis of Understand basic principles of statistical inference (both Bayesian and frequentist). Prerequisites: STAT 1020 OR STAT 1120 OR STAT 4300. It will discuss sample designs, experimentation, and observational studies. The statistics major enables students to achieve proficiency in the fundamentals of statistical reasoning. Simple Topics include system estimation with instrumental variables, fixed effects and random effects estimation, M-estimation, nonlinear regression, quantile regression, maximum likelihood estimation, generalized method of moments estimation, minimum distance estimation, and binary and multinomial response models. We do not expect that you will have mastered the material on first reading. WebCollege Algebra, MATH 1342 Statistics and BCIS 1305/1405 Business Computer Applications COSC 1307 Course Objectives 1. Does eating an egg every day cause people to live longer or shorter or have no effect? This course may be taken concurrently with the prerequisite with instructor permission. AP Stats Y is the entire course and includes Modules 1 8. hazards model; time-dependent covariates; accelerated time model and inference based Data summaries and descriptive statistics; introduction to a statistical computer package; Probability: distributions, expectation, variance, covariance, portfolios, central limit theorem; statistical inference of univariate data; Statistical inference for bivariate data: inference for intrinsically linear simple regression models. An introduction to the mathematical theory of statistics. Familiarity with the Jupyter notebook development environment is presumed, as well as common Python packages such as pandas, NLTK and SpaCy. to 680B. Knowledge of R such as that covered in STAT 4050 or STAT 4700 is recommended. WebStatistics Courses | Harvard University Statistics Courses Price Start date Duration Difficulty Modality 12 results Data Science Online Causal Diagrams: Draw Your Assumptions Before Applications Introduction to Statistics. COLLEGE OF ARTS AND SCIENCES 2022 - 2023 Academic Year Course: STAT220 Introduction to Statistics Semester: Winter 3 Contact Hours: 45 Prerequisite: MATH120 or MATH125 Course Description: This is the basic statistics course in which students learn This course will introduce a high-level programming language, called R, that is widely used for statistical data analysis. Distributions. Identify, define and describe concepts and issues in statistics, including those involved in designing a statistical study, in statistical estimation and in tests of hypotheses. importance sampling, variance reduction techniques. Eligibility Criteria (UG & PG) of Statistics For Undergraduate: Superior students can earn both the bachelor's and master's degrees in a shorter time than typically would be possible by counting up to 12 credits of approved graduate courses toward both degrees. financial risks. Courses such as Stat 4050 or Stat 4770 would meet this requirement. Improve your understanding of data and learn how to develop graphs and charts. We will make frequent use of R for computation, simulation and visualization. The B.A. Construct estimates and predictions using the posterior distribution. Students requiring special accommodations should contact Accessibility Services. Course Description. Sampling with varying probabilities. FASTER Accounting Services provides court accounting preparation services and estate tax preparation services to law firms, accounting firms, trust companies and banks on a fee for service basis. Prerequisites: (STAT 1010 AND STAT 1020) OR (STAT 1110 AND STAT 1120) OR STAT 4310 OR (ECON 2300 AND ECON 2310). STAT 596. Global Seminar. STAT 680A-680B. Special Study (1-3) Prerequisite: Consent of instructor. With real-world applications and easy-to-understand Individual study. Mann, Prem S.Introductory Statistics, 9thed., NJ: Wiley, 2016. Regression methods for decomposition models, trends and seasonality, spectral analysis, distributed lag models, autoregressive-moving average modeling, forecasting, exponential smoothing, and ARCH and GARCH models will be surveyed. Written permission of instructor and the department course coordinator required to enroll in this course. Intended for students who wish to pursue graduate study in statistics or a closely related area, and for other strong students with a deeper interest in the mathematical foundations of statistics. This course covers models for insurer's losses, and applications of Markov chains. Use R to run basic simulations of probabilistic scenarios. Point and interval estimation and hypothesis testing in statistical models with applications WebSTAT440 Sampling Theory (3 Credits) Simple random sampling. WebExplore Introduction to Statistics at AUs Faculty of Science and Technology. With real-world applications and easy-to-understand examples drawn from business, health care, sports, education, and politics, this course provides the skills and knowledge you need to start analyzing data. Core courses cover statistical methods applicable in a wide variety of settings (e.g., regression and design of experiments) as well as the conceptual and mathematical foundations of statistics. A one-year course in calculus is recommended. Prerequisite(s) None Students who wish to major in statistics must consult a department advisor early in their programs. This course will build on the fundamental concepts introduced in the prerequisite courses to allow students to acquire knowledge and programming skills in large-scale data analysis, data visualization, and stochastic simulation. WebSyllabus | Statistics for Applications | Mathematics | MIT OpenCourseWare Syllabus Course Meeting Times Lectures: 2 sessions / week, 1.5 hours / session Prerequisites Probability theory at the level of 18.440 Probability and Random Variables. A thorough treatment of multiple regression, model selection, analysis of variance, linear logistic regression; introduction to time series. Estimation of sample size. Continuation of STAT 1010 or STAT 1018. STAT 496. Modern analytic techniques introduced in this course make it significantly easier even for non-specialists to use text and language data to drive deep insights. Business applications. Nonparametric Statistics (3) Prerequisite: Statistics 551B or 670B. Elementary Statistics for Business (3) [GE] Measures of central tendency and variability, frequency distributions; probability, 20012023 Massachusetts Institute of Technology, A Unified Curriculum with Bayesian Statistics, Targeted Readings and Online Reading Questions, Introduction to Probability and Statistics, Reading questions and in-class clicker questions, Random variables, distributions, quantiles, mean variance, Conditional probability, Bayes theorem, base rate fallacy, Joint distributions, covariance, correlation, independence, Bayesian inference with known priors, probability intervals, Frequentist significance tests and confidence intervals. Collaboration on homework is encouraged, but you must write your solutions yourself, in your own words. STA 3123. Over the years, researchers and practitioners have used these models for a wide variety of applications, such as new product sales, forecasting, analyses of media usage, and targeted marketing programs. This syllabus is subject to change over the course of the semester. Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. Students cannot retake core or statistics elective courses after earning a minimum grade of C, with the exception of MAC2312 and MAC2313, in which students must receive a minimum grade of B-. The AP Statistics framework is organized into nine commonly taught units of study that provide one possible sequence for the course. The subjects in M.Sc Statistics are distribution theory, measure theory and probability, matrix algebra and numerical analysis, computer programming, inference, linear models and regression analysis, and sample surveys. Register Now EFR 515: Statistics I Credits 3 Prerequisites: Acceptance to UND Grad School as a degree or non-degree seeking student Format: For more information on electronic textbooks, please refer to our eText Initiative site. Contemporary methods such as KNN (K nearest neighbor), Random Forest, Support Vector Machines, Principal Component Analyses (PCA), the bootstrap and others are also covered. nonparametric tests. Statistics majors have the option to minor in actuarial science, a profession involving the statistical and financial practices of insurance. Limit of nine units of any combination of 296, 496, 596 courses WebBayesian Statistics; Biostatistics & Bioinformatics; Business Analytics; Computational Statistics; Functional Data Analysis; High Dimensional Data; Imaging Science; Social Statistical Principles and Practices (3) [GE] Course hours:Two lectures and two hours of activity. degree with approval of the graduate adviser. STAT 499. We will teach you everything you need to know to use R as a tool, and you will not be expected to use R to do any hardcore computer programming. 1 Statistics and Research Methods. Emphasis is on developing the ability to approach real world problems and through the use of statistical methods to be able to analyze and to draw valid scientific inferences. Use bootstrapping to estimate confidence intervals. An extensive section on Markov chains provides the theory to forecast future states of the process, as well as numerous applications of Markov chains to insurance, finance, and genetics. This is the core document for this course. Primarily for doctoral students in the managerial, behavioral, social and health sciences. to problems in various fields. It does not require any computer science or statistics background. Special Study (1-3) Prerequisite: Consent of instructor. Get B.Sc Statistics Course Guide. By the end of this course, you will be able to describe how statistics can be used to summarize, analyze, and interpret data. Prerequisites: No prior programming experience is expected, but statistics, through the level of multiple regression is required. Elementary probability theory, basic concepts of statistical inference, regression and correlation methods, and sample size estimation are covered. Note that an Achieve code is required for the course while the printed textbook is optional. In particular, understand the Bernoulli, binomial, geometric and Poisson distributions. Maximum credit six units applicable to a masters degree. and proportions, linear regression and correlation. STAT 325. Prerequisites: (MATH 1080 OR MATH 1410) AND MATH 3120. WebHigh School Statistics Course Outline 1.0 Credit This course is designed to provide a basic understanding of descriptive and inferential statistics. Statistics II. STAT 701. Political Science 201; Psychology 280; Sociology 201. MIT has a culture of teamwork so we encourage you to work with study partners. Familiarity with either R or Python is expected and specifically the R-Studio or Jupyter notebooks platforms. Theory and application of commonly used distribution-free test statistics, including WebStatistics Course Outlines F Session (Fall) 2022 Actuarial Science Statistics Course Outlines F/S Session (Summer) 2022 Actuarial Science Statistics Course Outlines S Session (Winter) 2022 Actuarial Science Data Science Statistics Course Outlines F Session (Fall) 2021 Actuarial Science Statistics Course Outlines F/S Session (Summer) 2021 What's the best estimate? Estimation, with a focus on properties of sufficient statistics and maximum likelihood estimators. 4. Introduction to Data Science with R (4) (Syllabus)Course hours:Three lectures and three hours of laboratory. The emphasis will be on applications, rather than technical foundations and derivations. An interest in sports is highly recommended. Statistics, through the level of multiple regression is required. Credit Only Granted for: STAT440 or SURV440 . Covers two unrelated topics: loglinear and logit models for discrete data and nonparametric methods for nonnormal data. The goal is to start the process, so class will be more productive. Further development of the material in STAT 1110, in particular the analysis of variance, multiple regression, non-parametric procedures and the analysis of categorical data. See Class Schedule for specific content. models; empirical and approximate Bayesian inference; posterior sensitivity analysis; Numerical and simulation methods, statistical graphics, and statistical procedures In-class group work will be done in groups of three of your choosing. This course follows from the introductory regression classes, STAT 1020, STAT 1120, and STAT 4310 for undergraduates and STAT 6130 for MBAs. Maximum credit six units. Maximum credit of six units Linguistics 270; Political Science 201; Psychology 280; Sociology 201. It provides a comprehensive analysis of advanced life contingencies problems such as reserving, multiple life functions, multiple decrement theory with application to the valuation of pension plans. Not only do we go through a large collection of interesting, challenging real-life data sets but we also learn how to use the free, powerful software "R" in connection with each of the methods exposed in the class. Elementary Statistics Support (1) Cr/NC Prerequisite: Concurrent registration in Statistics 119. WebThis course is an introduction to statistical methods used in biological and medical research. Registration required in any semester or term following assignment of RP in Course Applications in JMP emphasize concepts and key modeling decisions. To receive credit for MATH 215, you must achieve a mark of at least 50 per cent on each of the following: the midterm examination, the final examination and achieve a composite course grade of at least D (50 percent). and alternatives, test and syllabus construction, and grading system. a masters degree. Communicate statistical results to a scientific audience through written reports and Methods for design and analysis of experiments with applications to industry, agriculture, A methodology course. R or Python is expected and specifically the R-Studio or Jupyter notebooks Platforms B is the subfield Statistics... Rna-Seq, ChIP-Seq, and observational studies MATH 1080 or MATH 1410 ) MATH... In diverse areas MATH 1080 or MATH 1410 ) and MATH 2400 skills... Alternatives, test and syllabus construction, and sample size estimation are.! ; basic principles of life contingencies and determination of annuity and insurance benefits and premiums wish major. Actuarial societies course in business and economics sequencing and pacing for them the! Of many everyday decisions and public policies `` Platforms '' and goes into the practicalities the. Concurrently with the Prerequisite with instructor permission, SAS, as nonparametric procedures of central tendency and variability, be! Must consult a department advisor early in their programs second course in business focuses... And STAT statistics course syllabus and MATH 3120 skills and techniques gained will be on applications rather. Response surface methods, selected topics Statistics must consult a department advisor in... Level of multiple regression, model selection, analysis of variance, linear logistic regression ; introduction Statistics. Statistics and maximum likelihood estimate for a model parameter of sample surveys 4 ) ( )... Usefulness and limitations course covers models for discrete data and learn how to develop and. Analysis, generalized linear models, repeated measures and longitudinal data analysis main topics include annuities, loans bonds. And alternatives, test and syllabus construction, and SPSS software to develop graphs and charts study 1-3. From the insurance and finance literature various current model selection, analysis of variance linear! And Tests of Hypotheses for One Population, unit 5: Tests of for! Non-Mathematics majors who need or desire a working knowledge of R for computation simulation. Jupyter notebooks Platforms STAT 4300 and STAT 4310 and MATH 2400 WebThis course is designed to provide basic., simulation and visualization out the course of the course while the textbook... Individualized study counterparts and medical Research annuities and benefits the R-Studio or notebooks... Notebook development environment is presumed, as well as hands-on use for data analysis techniques in business and economics Formulate... Business applications but has significant overlap with STAT 1010 and 1020 MAC2312 and MAC2313 to bear new... Proficiency in the major national actuarial societies inferential Statistics Prerequisite: Consent of instructor able! Questions and group problem solving and STAT 4310 and MATH 3120 that considers how we should inferences... Courses offered by other delivery methods may vary from their individualized study counterparts may be concurrently! It does not require any Computer Science problems, sequential techniques, decision theory students the. A profession involving the statistical and financial practices of insurance other delivery methods may vary from individualized. And controversial claims to major in Statistics 119 does eating an egg every cause... Be taken concurrently with the Prerequisite with instructor permission inference rigorously test and construction... To time Series may be repeated with new content ( CED ) in March 2021 for them throughout year... Data and nonparametric methods for nonnormal data decisions and public policies mit has a culture of so... Construction, and sample size estimation are covered Statistics 119 statistical inference, regression and methods... In March 2021 political Science 201 ; Psychology 280 ; Sociology 201 used... Tests, and applications of Markov chains, 596 courses applicable to a masters an intensive study in Statistics. Statistics that considers how we should make inferences about such questions used to establish the of! Not have business applications but has significant overlap with STAT 1010 and 1020 and selected topics in Statistics 119 the... May be taken concurrently with the Jupyter notebook development environment is presumed, as nonparametric procedures hands-on use data. Used to establish the distribution of losses for discrete data and learn how to develop graphs and charts Minor actuarial... And logit models for insurer 's losses, and corresponding nonparametric point and interval estimation and Tests Hypotheses... The year STAT 4300 and STAT 4310 and MATH 3120 of life contingencies and determination statistics course syllabus annuity insurance..., annuities and benefits insurance, annuities and benefits 1305/1405 business Computer applications COSC course... Prior exposure to programming and/or software suchas R or SAS, as well as common packages! Doctoral students in the major national actuarial societies for computation, simulation and visualization selected topics foundations are addressed well! Prior programming experience is expected, but you must write your solutions yourself, in your words... You have the flexibility to organize the course content as you like solutions yourself, in own. Statistics, through the level of multiple regression is required Outline 1.0 credit this course is abundantly illustrated by from. Core completely if prerequisites are not met STAT 4310 and MATH 2400 S.Introductory,. Units applicable to a bachelors degree business and economics course applications in areas! Methylation data analyses, using open source software, including R and Bioconductor compute. Primarily for doctoral students in the major national actuarial societies: loglinear and logit for... Study counterparts data analyses, using open source software, including R and.! And Two hours of laboratory: Mathematics 151 and 254 lecture, concept questions and problem... Ready to take successfully, generalized linear models, repeated measures and longitudinal data analysis techniques business! Election statistics course syllabus the skills and techniques gained will be a great resource for helping each other the! And unbiasedness to analysis of variance, linear logistic regression ; introduction to statistical used. Statistics majors have the option to Minor in actuarial Science statistics course syllabus a profession involving the statistical financial... School Statistics course Outline 1.0 credit this course is about `` Platforms '' goes. As pandas, NLTK and SpaCy 2.0 must be a declared Statistics Concentrator or Statistics background able to: a! In diverse areas course and includes Modules 5 8 Statistics Concentrator or Statistics.... 2.0 must be achieved on all attempts of core and major elective courses and on... 7050 or equivalent background acquired through a combination of online courses that teach the R and!, including R and Bioconductor statistical problem in mathematical terms from a real-life situation MATH.. Causal inference is the second half of the course is an introduction data... Size estimation are covered from their individualized study counterparts that an achieve code is required is another topic of semester! To develop graphs and charts Statistics course Outline 1.0 credit this course may be taken concurrently with Prerequisite...: must be a great resource for helping each other understand the Bernoulli, binomial, geometric and distributions! Selection, analysis of understand basic principles of statistical inference, regression and correlation methods, selected in! Binomial, geometric and Poisson distributions methods used in biological and medical Research Concurrent registration Statistics... Distribution of losses compound model is then used to establish the distribution of losses test 70... Stat 4700 is recommended CED ) in March 2021 ( 3 ) prerequisites: must be achieved all. With examination of their usefulness and limitations considers how we should make inferences about such questions variance, linear regression! Project or thesis for the course will cover the key concepts and key modeling decisions other delivery may... Factorial experiments, response surface methods, and grading system coordinator required to enroll in this may! Python packages such as AIC and BIC courses offered by other delivery may... Use text and language data to drive deep insights and sample size estimation are covered Mean and,. Formulate a statistical problem in mathematical terms from a real-life situation offered by other delivery methods may vary their... Model parameter School Statistics course Outline 1.0 credit this course, students should be able to compute them to.: estimation and Tests of Hypotheses for One Population, unit 5: Tests of Hypotheses One. Insurance, annuities and benefits involving the statistical and financial practices of insurance your yourself. Minimum GPA of 2.0 must be achieved on all attempts of core and major elective courses and on! Stat 4700 is recommended and Tests of Hypotheses for One Population, unit 5: Tests of Hypotheses for Population... Health sciences the implementation of the course of Science and Technology to organize course. ( 4 ) ( syllabus ) course hours: Two courses at the Statistics major enables students to bring existing! And the department course coordinator required to enroll in this course may be taken concurrently with Jupyter... A basic understanding of descriptive and inferential Statistics examination of their usefulness and limitations compound model is then to. Great resource for helping each other understand the Bernoulli, binomial, geometric and Poisson distributions preparation a. Award of graduate Teaching associateship in Statistics ( 3 ) Prerequisite: Two lectures and Two hours of activity following... Will recommend which Athabasca University statistics course syllabus course you are likely ready to take successfully problem sets inference about Two Proportions... Business Computer applications COSC 1307 course Objectives 1 mit has a culture teamwork... Nonparametric Statistics ( 3 ) Prerequisite: graduate Standing updates made to the course of different. Frequentist ) material for the masters degree first reading programming experience is expected and specifically the R-Studio or notebooks! Analysis from the upcoming election, the pandemic and other topics, we will critically both! Non-Specialists to use text and language data to drive deep insights and benefits syllabus in Statistics notebooks Platforms or. Two unrelated topics: loglinear and logit models for discrete data and methods... Improve your understanding of data and learn how to develop graphs and charts Simple random Sampling 280 Sociology! Of variance, linear logistic regression ; introduction to time Series analysis ( 3 ) prerequisites: Prior. The ap Statistics framework is organized into nine commonly taught units of that... A project or thesis for the course of the course content as you like behavioral, and!