What is the Shape of the Distribution?
1.Does the histogram have a single, central hump or several separated bumps?
2.Is the histogram symmetric?
3.Do any unusual features stick out?
Humps and Bumps
1.Does the histogram have a single, central hump or seve
Chapter 4
Most statistical studies involve more than one variable
For relationship bw two quantitative variables
o Response variable
Measures an outcome of a study (dependent)
o Explanatory variable
Attempts to explain the observed outcomes (independent
Chapter 3
Cleaning up data before importing
o Correct the data/convert the data
o Delete
o Keep them
Outliers
o Can affect every statistical method we will study
o Can be very informative part
o May be error in the data
o Should be discussed in any conclu
Chapter 6
Randomness and Probability
Law of Large Numbers
o Larger creates more equal probability
RULES FOR PROBABILITY
o Sample Space
Set of all possible outcomes
Probability of each outcome is a percentage of 1 and must add up to 1
o Complement Rule
Help with Excel
The biggest thing to remember is that the data you download is a .CSV file. You must use Save As to save
as a Microsoft Excel file with a .XLS file extension. If you submit a
1
Some browsers such as Safari, dont download a file, instead, t
STA 309H Applied Finance Assignment #1 TECHNICAL
ANALYSIS
1 Introduction
In this assignment you will employ data smoothing techniques to a real world problem in stock market
analysis. The spreadsheet that you develop will be used as a building block for P
CH 4 Day 1: Describing Quantitative Data:
Histogram & Dot Plot
When discussing a distribution, be it a histogram, dot plot
or stem plot, the following items need to be addressed:
Center
Unusual features
Shape
Spread
&
Be
Specific!
Shape: Look for the foll
Counts Count
When we count the cases in each category of a categorical variable, the counts are not the data, but
something we summarize about the data.
The category labels are the What, and
the individuals counted are the Who.
Counts Count (cont.)
When w
Chapter 2
Data
What Are Data?
Data can be numbers, record names, or other labels.
Not all data represented by numbers are numerical data (e.g., 1=male, 2=female).
Data are useless without their context
The Ws
To provide context we need the Ws
Who
What (an
Contingency Tables
A contingency table allows us to look at two categorical variables together.
It shows how individuals are distributed along each variable, contingent on the value of the other
variable.
Example: we can examine the class of ticket and wh
Chapter 3
Displaying and Describing
Categorical Data
The Three Rules of Data Analysis
The three rules of data analysis wont be difficult to remember:
1.Make a picturethings may be revealed that are not obvious in the raw data. These will be things
to thin
Chapter 4
Displaying Quantitative Data
Dealing With a Lot of Numbers
Summarizing the data will help us when we look at large sets of quantitative data.
Without summaries of the data, its hard to grasp what the data tell us.
The best thing to do is to make
Chapter 5
Examining relationships
o Start with a graph
o Look for pattern and deviations
o Add numerical descriptions
o IF the pattern is LINEAR summarize with a line
o Correlation measures the strength and direction of the linear relationship
Regression