This page was intended for the Summer 2020 version of the course.
Lecture 4: June 4, "Random Variables and Discrete Probability Distributions" (Chapter 7 of Textbook)
Lecture 5: June 11, "Continuous Probability Distributions and Data Collection" (Chapters 5 and 8 of Textbook)
Lecture 6: June 18, "Sampling Distributions and Introduction to Estimation" (Chapters 9 and 10 of Textbook)
Term Test 2 is Sunday July 5 from 10:00am to 11:30am. It is worth 30%.
Lecture 1: May 14, "Introduction, Graphical Descriptive Techniques I and Graphical Descriptive Techniques II" (Chapters 1-3 of Textbook)
Chapter 1 Key Things
Inferential statistics draws conclusions or "inferences" about characteristics of populations based on sample data.
Exit polls: a random sample of voters who exit the polling booth are asked for whom they voted
population is the group of all items of interest
A descriptive measure of a population is called a parameter
A sample is a set of data drawn from the studied population.
A descriptive measure of a sample is called a statistic.
Statistical inference is the process of making an estimate, prediction, or decision about a population based on sample data.
The confidence level is the proportion of times that an estimating procedure will be correct.
the significance level measures how frequently the conclusion will be wrong
Inferential statistics draws conclusions or "inferences" about characteristics of populations based on sample data.
Exit polls: a random sample of voters who exit the polling booth are asked for whom they voted
population is the group of all items of interest
A descriptive measure of a population is called a parameter
A sample is a set of data drawn from the studied population.
A descriptive measure of a sample is called a statistic.
Statistical inference is the process of making an estimate, prediction, or decision about a population based on sample data.
The confidence level is the proportion of times that an estimating procedure will be correct.
the significance level measures how frequently the conclusion will be wrong
Lecture 2, May 21, "Numeric Descriptive Techniques" (Chapter 4 of textbook)
NOT INCLUDING:
* Least Squares Method: p. 114 (Cover in Ch 16)
Coefficient of determination: p.120 (Cover in Ch 16)
4.5 Applications in Finance: Market Model: p. 125
* Least Squares Method: p. 114 (Cover in Ch 16)
Coefficient of determination: p.120 (Cover in Ch 16)
4.5 Applications in Finance: Market Model: p. 125
