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Your search for courses for 21/FA and in CMC 102 found 5 courses.

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CS 111.01 Introduction to Computer Science 6 credits

Closed: Size: 34, Registered: 32, Waitlist: 0

CMC 102

MTWTHF
11:10am12:20pm11:10am12:20pm12:00pm1:00pm
Synonym: 60374

James O Ryan

This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and object-oriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111.

Sophomore priority

Waitlist for Juniors and Seniors: CS 111.WL1 (Synonym 60377)

STAT 120.02 Introduction to Statistics 6 credits

Closed: Size: 32, Registered: 29, Waitlist: 0

CMC 102

MTWTHF
1:50pm3:00pm1:50pm3:00pm2:20pm3:20pm
Synonym: 61444

Deepak Bastola

(Formerly MATH 215) Introduction to statistics and data analysis. Practical aspects of statistics, including extensive use of statistical software, interpretation and communication of results, will be emphasized. Topics include: exploratory data analysis, correlation and linear regression, design of experiments, basic probability, the normal distribution, randomization approach to inference, sampling distributions, estimation, hypothesis testing, and two-way tables. Students who have taken Mathematics 211 are encouraged to consider the more advanced Mathematics 240/Statistics 250 (formerly Mathematics 265 and 275) Probability/Statistical Inference sequence.

Prerequisite: Not open to students who have already received credit for Psychology 200/201, Sociology/Anthropology 239 or Statistics 250 (formerly Mathematics 275).

Formerly Mathematics 215

STAT 120.03 Introduction to Statistics 6 credits

Closed: Size: 32, Registered: 24, Waitlist: 0

CMC 102

MTWTHF
3:10pm4:20pm3:10pm4:20pm3:30pm4:30pm
Synonym: 61445

Deepak Bastola

(Formerly MATH 215) Introduction to statistics and data analysis. Practical aspects of statistics, including extensive use of statistical software, interpretation and communication of results, will be emphasized. Topics include: exploratory data analysis, correlation and linear regression, design of experiments, basic probability, the normal distribution, randomization approach to inference, sampling distributions, estimation, hypothesis testing, and two-way tables. Students who have taken Mathematics 211 are encouraged to consider the more advanced Mathematics 240/Statistics 250 (formerly Mathematics 265 and 275) Probability/Statistical Inference sequence.

Prerequisite: Not open to students who have already received credit for Psychology 200/201, Sociology/Anthropology 239 or Statistics 250 (formerly Mathematics 275).

Formerly Mathematics 215

STAT 220.00 Introduction to Data Science 6 credits

Open: Size: 30, Registered: 25, Waitlist: 0

CMC 102

MTWTHF
8:30am9:40am8:30am9:40am8:30am9:30am
Synonym: 61447

Adam Loy

(Formerly Mathematics 285) This course will cover the computational side of data analysis, including data acquisition, management, and visualization tools. Topics may include: data scraping, data wrangling, data visualization using packages such as ggplots, interactive graphics using tools such as Shiny, supervised and unsupervised classification methods, and understanding and visualizing spatial data. We will use the statistics software R in this course.

Prerequisite: Statistics 120 (formerly Mathematics 215), Statistics 230 (formerly Mathematics 245) or Statistics 250 (formerly Mathematics 275)

Formerly Mathematics 285

STAT 230.00 Applied Regression Analysis 6 credits

Closed: Size: 25, Registered: 29, Waitlist: 0

CMC 102

MTWTHF
9:50am11:00am9:50am11:00am9:40am10:40am
Synonym: 61448

Katie R St. Clair

(Formerly Mathematics 245) A second course in statistics covering simple linear regression, multiple regression and ANOVA, and logistic regression. Exploratory graphical methods, model building and model checking techniques will be emphasized with extensive use of statistical software to analyze real-life data.

Prerequisite: Statistics 120 (formerly Mathematics 215) or Statistics 250 (formerly Mathematics 275), Psychology 200, or AP Statistics Exam score of 4 or 5.

Formerly Mathematics 245

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You must take 6 credits of each of these.
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You must take 6 credits of each of these,
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