Statistics can be used to draw conclusions about data and provides a foundation for more sophisticated data analysis techniques. Viewing questions about data from a statistical perspective allows data scientists to create more predictable algorithms to convert data effectively into knowledge. As such, it is essential for data analysts to have a strong understanding of both descriptive and inferential statistics.
In this course, students will gain a comprehensive introduction to the statistical theories and techniques necessary for successful data mining and analysis. Particular attention will be paid to topics critical to data analytics, such as descriptive and inferential statistics, probability, linear and multiple regression, hypothesis testing, Bayes Theorem, and principal component analysis. This course prepares students for subsequent Data Mining courses.
Topics include:
- Descriptive statistics
- Two variable relationships
- Probability
- Bayes Theorem
- Probability distributions
- Sampling distributions
- Confidence intervals
- One- and two-sample hypothesis testing
- Categorical data
- Least-squares regression inference
- Principal component analysis (PCA)
Practical Experience:
- Organize, summarize, and present data
- Describe the relation between two variables
- Work with sample data to make inferences about the data
- Gain an understanding of linear algebra
Required Software: Students will use MyStatLab and StatCrunch to complete assignments in this course. The instrutor will provide students with student links to purchase student versioins of this software on the first day of class.
Required Textbook: On the first day of class, the instructor will provide students with the information needed to purchase the required eBook which will include access to the above software.
Course typically offered: Online in every quarter.
Prerequisites: None
Next steps: Upon completion of this course, considering taking Fundamentals of Data Mining to continue learning.
More Information: For more information about this course, please contact unex-techdata@ucsd.edu.
Course Number: CSE-41264
Credit: 3.00 unit(s)
Related Certificate Programs: Data Mining for Advanced Analytics
+ Expand All
-
9/26/2023 - 11/19/2023
$675
Online
-
-
-
CLASS TYPE:
Online Asynchronous.
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
-
-
POLICIES:
No refunds after: 10/2/2023.
-
9/26/2023 - 11/19/2023
extensioncanvas.ucsd.edu
You will have access to your course materials on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
-
1/9/2024 - 3/17/2024
$675
Online
-
-
-
CLASS TYPE:
Online Asynchronous.
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
-
TEXTBOOKS:
No information available at this time.
-
POLICIES:
No refunds after: 1/15/2024.
-
1/9/2024 - 3/17/2024
extensioncanvas.ucsd.edu
You will have access to your course materials on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
There are no sections of this course currently scheduled. Please contact the Science & Technology department at 858-534-3229 or unex-sciencetech@ucsd.edu for information about when this course will be offered again.