This course is an introduction to probability and statistics. Students will engage in elementary principles and applications of descriptive statistics, counting principles, elementary probability principles, probability distributions, estimation parameters, hypothesis testing, linear regression and correlation, and ANOVA. Students will utilize the application of technology for various statistical analyses.This assignment asks students to incorporate their identity, skill development, intellect, and critically based on the work of Cultivating Giunus by Dr. Gholdy Muhhamad. Students are asked to analyze the work they have produced throughout the semester and select two works per each student's learning outcome. 

The applet in this section allows you to see how the T distribution is related to the Standard Normal distribution by calculating probabilities. The T distribution is primarily used to make inferences on a Normal mean when the variance is unknown.

The applet in this section allows you see how probabilities are determined from the exponential distribution. The user determines the mean of the distribution and the limits of probability. Three different probability expressions are available.

CK-12 Advanced Probability and Statistics introduces students to basic topics in statistics and probability but finishes with the rigorous topics an advanced placement course requires. Includes visualizations of data, introduction to probability, discrete probability distribution, normal distribution, planning and conducting a study, sampling distributions, hypothesis testing, regression and correlation, Chi-Square, analysis of variance, and non-parametric statistics.

The students will play a classic game from a popular show. Through this they will see the probabilty that the ball will land each of the numbers with more accurate results coming from repeated testing.

Students begin to formalize their understanding of probability. They are introduced to the concept of probability as a measure of likelihood and how to calculate probability as a ratio. The terms discussed (impossible, certain, etc.) in Lesson 1 are given numerical values.Key ConceptsStudents will think of probability as a ratio; it can be written as a fraction, decimal, or a percent ranging from 0 to 1.Students will think about ratio and proportion to predict results.Goals and Learning ObjectivesDefine probability as a measure of likelihood and the ratio of favorable outcomes to the total number of outcomes for an event.Predict results based on theoretical probability using ratio and proportion.

Submitted as part of the California Learning Resource Network (CLRN) Phase 3 Digital Textbook Initiative (CA DTI3), CK-12 Advanced Probability and Statistics introduces students to basic topics in statistics and probability but finishes with the rigorous topics an advanced placement course requires. Includes visualizations of data, introduction to probability, discrete probability distribution, normal distribution, planning and conducting a study, sampling distributions, hypothesis testing, regression and correlation, Chi-Square, analysis of variance, and non-parametric statistics.

This text is for an introductory level course in probability and statistics.

This work, "Mostly Harmless Probability and Statistics for NMC", is a derivative of "Mostly
Harmless Statistics" by Rachel Webb used under CC BY-NC 4.0. "Mostly Harmless Probability
and Statistics for NMC" is licensed under CC BY-NC 4.0 by Briana Mills.

Rachel Webb’s original text was a combination of Webb’s work, Statistics
Using Technology by Kathryn Kozak, and OpenIntro Statistics by Diez, Barr, Çetinkaya-Rundel.
All texts are licensed under CC BY-SA 4.0. Additional problem sets provided by Whitney Cave.
It has been updated by Briana Mills with help from Nate Butler and Tony Jenkins to match the
curriculum at NMC.

The textbook solutions for this book are available at: https://drive.google.com/drive/u/1/folders/1BTXchIplWzk0mjohao2xrE4cfeOOUsvI

Think Stats is an introduction to Probability and Statistics for Python programmers.

*Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.
*If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

The shell of a syllabus that hopes to incorporate many antiracist practices, in statistics.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

In this class, students will be able to identify what is probability and have a general concept. The students should be able to calculate the probability questions by using the formula of conditional probability (P( A|B )=number of A/the total number of outcomes.)