Chapter_2

# Chapter_2 - Chapter 2 Exploring Data with Graphs and...

This preview shows pages 1–14. Sign up to view the full content.

Chapter 2: Exploring Data with Graphs and Numerical Summaries Read Chapters 1-2 and Start Homework 1

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Descriptive Statistics ± Goal: To understand your data! ² Summary & Description ² Find peculiarities ± Descriptive statistics are a vital precursor for more sophisticated, model-based inferential techniques
Survivorship on the Titanic Goal: To describe patterns of survival in passengers on the Titanic

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
The Data Variable Description age Age in years gender m = male, f = female class 1 = first, 2 = second, 3 = third survived N, Y n = 1046
Data Types ± Qualitative variables have values that vary in kind but not degree (not measurements). ² Survived = Y/N ² Passenger class = 1 st , 2 nd , or 3 rd ² Gender = M/F ± Quantitative variables have actual units of measure. One can perform arithmetic operations. ² Age = passenger’s age in years

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Class Question #1: ± Identify the variable type as either categorical or quantitative 1. Number of siblings in a family 2. County of residence 3. Distance (in miles) of commute to school 4. Marital status
Class Question #2 ± Identify each of the following variables as continuous or discrete 1. Length of time to take a test 2. Number of people waiting in line 3. Number of speeding tickets received last year 4. Your dog’s weight

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Data Structure Rectangular arrays ± Rows – observations or subjects ± Columns – variables Variable – characteristics recorded about each individual or observation. These characteristics are expected to vary from individual to individual
The Titanic Data in StatCrunch This a portion of the data set.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Graphical Methods ± Univariate Methods: ² Categorical variables: bar chart, pie chart ² Quantitative variables: histogram, stem and leaf plot, box plot, normal quantile plot (aka normal probability plot) ± The Goals: ² Getting to know the data ² Who were the Titanic passengers?
Bar plots: Categorical Variables Bar plots are used to display the total number of observations or the percentage of the total number of measurements falling into each (displayed) category. Graphics > Bar plot > with data > frequency (option)

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Proportion & Percentage (Relative Frequencies) ± The proportion of the observations that fall in a certain category is the frequency (count) of observations in that category divided by the total number of observations Frequency of that class Sum of all frequencies ± The percentage is the proportion multiplied by 100. Proportions and percentages are also called relative frequencies.
Bar plots: Categorical Variables Bar plots are used to display the total number of observations or the percentage of the total number of measurements falling into each (displayed) category.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 54

Chapter_2 - Chapter 2 Exploring Data with Graphs and...

This preview shows document pages 1 - 14. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online