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)

**draws conclusions or "inferences" about characteristics of populations based on sample data.**

Inferential statistics

__Chapter 1 Key Things__Inferential statistics

**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