Graphing Data 4
- Lecture1.1
  
  Introduction
- Lecture1.2
  
  Basic Charts
- Lecture1.3
  
  Basic Charts Part 2
- Lecture1.4
  
  Randomness
Mean and Standard Deviation 5
- Lecture2.1
  
  Introduction
- Lecture2.2
  
  Random Walk
- Lecture2.3
  
  Random Walk Part 2
- Lecture2.4
  
  Mean and Standard Deviation
- Lecture2.5
  
  Mean and Standard Deviation Part 2
Distributions 6
- Lecture3.1
  
  Introduction
- Lecture3.2
  
  PDF and CDF
- Lecture3.3
  
  PDF and CDF Part 2
- Lecture3.4
  
  Z Scores
- Lecture3.5
  
  Plotting
- Lecture3.6
  
  Solution
Correlation and Linear Regression 7
- Lecture4.1
  
  Introduction
- Lecture4.2
  
  Basics
- Lecture4.3
  
  Correlation
- Lecture4.4
  
  Z-Score
- Lecture4.5
  
  Z-Score Part 2
- Lecture4.6
  
  Linear Regression
- Lecture4.7
  
  Linear Regression Part 2
Probability 3
- Lecture5.1
  
  Introduction
- Lecture5.2
  
  Probability Basics
- Lecture5.3
  
  Probability
Counting Principles 3
- Lecture6.1
  
  Introduction
- Lecture6.2
  
  Factorials and Permutations
- Lecture6.3
  
  Binomial Theorem
Binomial Distribution 3
- Lecture7.1
  
  Introduction
- Lecture7.2
  
  Binomial Distribution
- Lecture7.3
  
  Binomial Distribution Part 2
Confidence Interval 7
- Lecture8.1
  
  Introduction
- Lecture8.2
  
  Alpha
- Lecture8.3
  
  Confidence Intervals
- Lecture8.4
  
  Confidence Intervals Part 2
- Lecture8.5
  
  Confidence Intervals Part 3
- Lecture8.6
  
  Confidence Intervals Part 4
- Lecture8.7
  
  Confidence Intervals Part 5
Proportion Confidence Interval 3
- Lecture9.1
  
  Introduction
- Lecture9.2
  
  Equations
- Lecture9.3
  
  Solution
Hypothesis Testing 5
- Lecture10.1
  
  Introduction
- Lecture10.2
  
  The Null Hypothesis
- Lecture10.3
  
  The Null Hypothesis Part 2
- Lecture10.4
  
  One Tail Test
- Lecture10.5
  
  One Tail Test Part 2
Comparing Two Means 5
- Lecture11.1
  
  Introduction
- Lecture11.2
  
  Known Standard Deviations
- Lecture11.3
  
  Unknown Standard Deviations
- Lecture11.4
  
  Same Unknown Standard Deviations
- Lecture11.5
  
  Solution
Chi-squared Test 3
- Lecture12.1
  
  Introduction
- Lecture12.2
  
  Basics
- Lecture12.3
  
  Expected Values

Random Walk

Extending the idea of randomness, we can create a random walk simulation. The random walk simulation gets a random movement each period where there isn’t a bias in the expected value of the random movement. Many people claim this is how stocks can sometimes act, but that’s up for you to decide.

from random import randint
print(randint(-1, 1))

The above code will print out a number -1, 0, or 1. We want one of these three numbers for deciding where our random walk goes.

Challenge

Create a random walk where you record each position of the walker in an array, then plot the random walk over time.

Prev Introduction

Next Random Walk Part 2

Basics

Graphing Data 4

Mean and Standard Deviation 5

Distributions 6

Correlation and Linear Regression 7

Probability 3

Counting Principles 3

Binomial Distribution 3

Confidence Interval 7

Proportion Confidence Interval 3

Hypothesis Testing 5

Comparing Two Means 5

Chi-squared Test 3

Random Walk

Challenge

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