Nathalie Moon

Liza Bolton

B White

STA130H1 Lecture 1: STA130 Lec01 An Introduction to Statistical Reasoning and Data Science

STA130H1 Lecture Notes - Lecture 1: Leland Wilkinson, Histogram, Loess

Numerical (or quantitative) variables: each value of a variable is from a numerical scale, values are ordered and differences are meaningful, examples:

STA130H1 Lecture 2: STA130 Lec02 An Introduction to Statistical Reasoning and Data Science

STA130H1 Lecture 2: Note Jan 14, 2019

STA130H1 Lecture Notes - Lecture 2: Random Variable, Data Wrangling, Linear Combination

The histogram of a variable is a graphical method to vizualize the distribution of a single variable. To construct a basic histogram: divide the data i

STA130H1 Lecture 2: Dr Moon

STA130H1 Lecture 3: STA130 lec03 An introduction to statistical reasoning and data science

STA130H1 Lecture Notes - Lecture 3: Rstudio, Data Science, Markdown

R objects: r lets you save data by storing it in a object, when you create an object, the object will appear in the environment pane of rstudio. Functi

STA130H1 Lecture Notes - Lecture 4: Statistical Inference, Test Statistic, Null Hypothesis

Sometimes the goal of statistical work is to make conclusions or decisions based on the incomplete information we have in our data this procedure is kn

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This course, intended for students considering a program in Statistical Sciences, discusses the crucial role played by statistical reasoning in solving challenging problems from natural science, social science, technology, health care, and public policy, using a combination of logical thinking, mathematics, computer simulation, and oral and written discussion and analysis.

An Introduction to Statistical Reasoning and Data Science

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