m32slides

35: Introduction to Machine Learning (2)

Goal: overview of some machine learning techniques
May 1, 2023
Derek Sollberger

34: Introduction to Machine Learning

Goal: introduce machine learning (ideas and terminology)
Apr 28, 2023
Derek Sollberger

Confidence Intervals

Among pennies in circulation in 2019, what was the average year of minting? We have a sample size of 50 pennies.
Apr 21, 2023
Derek Sollberger

30: Regression Analysis

Goal: Discuss the validity of regression models
Apr 19, 2023
Derek Sollberger

29: Linear Regression

Goal: Summarize bivariate data
Apr 17, 2023
Derek Sollberger

28: Beta Distribution

Goal: Explore a distribution of proportions
Apr 14, 2023
Derek Sollberger

27: Maximum Likelihood

Goal: Modify distribution parameters based on observed data
Apr 12, 2023
Derek Sollberger

26: Likelihood

Recall,
Apr 7, 2023
Derek Sollberger

25: Central Limit Theorem

Goal: Consolidate our understanding of variance
Apr 5, 2023
Derek Sollberger

24: Estimators

Goal: Explore generalization from samples to populations
Mar 21, 2023
Derek Sollberger

23: Law of Large Numbers

Goal: start to understand error as it relates to sample size
Mar 20, 2023
Derek Sollberger

22: Poisson Process

Goal: Derive distribution of number of arrivals
Mar 17, 2023
Derek Sollberger

21: Change of Variables

Let F be the…
Mar 15, 2023
Derek Sollberger

20: Correlation

We will once again visualize the act of ordering food at In-n-Out.
Mar 13, 2023
Derek Sollberger

19: Covariance

We will once again visualize the act of ordering food at In-n-Out.
Mar 8, 2023
Derek Sollberger

18: Linear Operators

\[{\col…
Mar 6, 2023
Derek Sollberger

17: Continuous Joint Distributions

The joint probability density function f(x,y) to handle simultaneous calculations of random variables X and Y can be expressed as
Mar 3, 2023
Derek Sollberger

16: Discrete Joint Distributions

The joint probability mass function (joint PMF) to handle simultaneous calculations of random variables X and Y can be expressed as
Feb 27, 2023
Derek Sollberger

15: Normal Distribution

Let us start with the mother function y=e−x2
Feb 24, 2023
Derek Sollberger

14: Exponential Distribution

The inclusive versus exclusive variation in inequalities matter in discrete probability distributions. With a random variable X defined over a support of \(k =…
Feb 22, 2023
Derek Sollberger

13: Continuous Distributions

You arrive at a bus stop at 10 o’clock, knowing that the bus will arrive at some time uniformly distributed between 10:00 and 10:30.
Feb 15, 2023
Derek Sollberger

12: Geometric Distribution

Here let us assume an endless box of chocolates with random selection with replacement of
Feb 13, 2023
Derek Sollberger

11: Cumulative Computation

Last time, we developed the probability mass function for the binomial distribution. The probability of choosing k observations among a sample size of n, each observation with…
Feb 10, 2023
Derek Sollberger

10: Binomial Distribution

To continue our exploration of discrete distributions, we will look at situations that have two disjoint possibilities.
Feb 8, 2023
Derek Sollberger

09: Expectation

Suppose that all of the students in Math 32 are between ages 19 and 21 inclusively with the following distribution:
Feb 6, 2023
Derek Sollberger
No matching items