Statistics

In this video I tell the story of Joy Milne and her ability to smell Parkinson's disease and use part of that story as an intro to learning the characteristics of the binomial probability distribtion. We learn how to create binomial probability distributions using excel and the binomial formula..

Big review of basic laws of probability and counting principles . This is a recording in front of a live classroom.

In this video we practice using various counting principles in sample problems.

Here I present some of the basic rules for counting techniques needed in an intro to probability course.

We explore the birthday problem: What is the probability that at least 2 people share the same birthday in a classroom of 25 people?

This is part of 4 of 4 on the basic laws of probability. This podcast focuses on conditional probability and the test for independent events.

This is part 3 of a 4 part probability notes.

This is part 2 of a 4 part notes on the basic laws of probability.

These notes on probability will be broken into a 4 part video. This is part one of the guidedd notes on probability

In this video I begin to introduce the laws of probability very simply through looking at cards, dice, and coin problems..

In this video I show how easy it is is to compute residuals and make a residual plot in excel.

In this video I show a fast and easy way to retrieve the scatterplot and correlation coefficient and examine the strength and direction of the association of a scatter-plot using excel.

In this video I pick a problem from the textbook to work through with you and we calculate residuals and make a residual plot. We then use the residual plot to decide if the linear model is appropriate for the data. You may want to pause the video and enter the data and practice computing residuals along with me.

This a live clip from an actual classroom where we learn how to compute residuals using a TI-83 and learn the definition of a residual. I also show how to compute the sum of the squared residuals.

In this lesson we explore the association between two variable via looking at scatter-plots and computing the correlation coefficient. This is shown using a TI-83.Lesson6 guided notes.

This is a clip from a live classroom where we do a warm up problem together and review how to numerically and graphichally summarize a data set via making a boxplot and histogram on TI-83 and we use the TI-83 to gather numerical descriptors.

This is a clip form a live classroom where I work through some problems in the textbook involving z scores and boxplots. We review how to find outliers as well.

In this video I pull a couple of examples out of our textbook to work through (for extra practice)involving z scores and boxplots.

This is a clip from a live classrooom where we work through a homework problem together involving Chebyshev's theorem.

This is a clip fom a live classroom where we work on some problems together out of the textbook and practice using Empirical rule and Chebyshev's inequaltiy.

In this video I explain the difference between Chebyshev's inequality and the Empirical rule for bell shaped data.

In this lesson we will explore the definiton of a z score and how that relates to percentile rank. We will also explore a data set to see if there are any outliers in the data. To determine if there are outliers we will create a modified boxplot on a TI-83 but we will also use the fence criterion. (lesson5 guided notes)

In this video, which is a clip from a LIVE classroom, I review how to find variance and standard deviation by hand and also go over the mathematical notation for measures of central tendency and dispersion.

In this video I show how to retrieve mean, median, mode and standard deviation at the touch of a button using excel(with megastat add in). We take a data set (people's test scores) and practice making stem and leaf and boxplots in excel. We discuss mean, median, and mode and the relationship to skewed distributions as well..

In this video we discuss the meaning of various numerical summaries such as mean, median , mode, standard deviation, and variance. I also demonstrate how to obtain those descriptive statistics by formula and using technology.(Lesson3 guided notes)