202021 As Statistics Jyothi

This class meets 3 times a week and will cover Statistics 1 and then some of Statistics 2.

The textbooks are Probability and Statistics 1 by Dean Chalmers and Probability and Statistics 2 by Jayne Kranat; both published by the Cambridge University Press

# June

## Representation of data

(Chapter 1, one week)

• Introduce working with data and discuss why representation matters
• Work on some real data and solve some problems to see why the benefits of various representations

## Measures of Central tendency

(Chapter 2, one week)

• Why do we need a single measure of location, when are they helpful
• Mean, median, mode
• Idea of an expectation and introduce sigma notation

## Measures of variation

(Chapter 3, two weeks)

• Why do we need measures of location, when are they helpful
• variance and standard deviation
• Problems involving grouped data

# July

## Probability

(Chapter 4, two weeks)

• Mutually exclusive vs independent events
• Conditional probabilities
• Solve problems

## Probability distributions

(Chapter 6, two weeks)

• The idea of a random variable
• Using permutation and combination
• Expectation and variance of a discrete RV

# August

## Binomial and geometric distributions

(Chapter 7, three weeks)

• What is a binomial distribution and where is it useful?
• Expectation and variance of a binomial distribution
• Problems
• What is a geometric distribution and where is it useful?
• Expectation and variance of a geometric distribution
• Problems

# September

## The normal distribution (Chapter 8, three weeks)

• Introduction to the normal distribution
• Problems
• Standard normal
• Relationship between Normal and Binomial distributions

# (Stat 1 portion ends here)

## Hypothesis testing

(Stat. 2, Chapter 1, two weeks)

• Introduction
• One and two tailed tests
• Types of errors

# October

## Sampling

(Stat 2, Chap 5, 1 week)

• Introduction
• Distribution of sample means

## Estimation

(Stat 2, Chapter 6, 3 weeks)

Final Exams