'Categorical variables' presentation slideshows

Categorical variables - PowerPoint PPT Presentation


ONS Data Science Pathfinder Programme: Better Outcomes through Predictive Analytics

ONS Data Science Pathfinder Programme: Better Outcomes through Predictive Analytics

ONS Data Science Pathfinder Programme: Better Outcomes through Predictive Analytics Jamie Stainer, Department for the Economy (NI). Nice to meet you!. Youth Training Statistics and Research Branch : Part of Analytical Services Division

By paul2
(1027 views)

Univariate Analysis

Univariate Analysis

Univariate Analysis. The first step to analyzing data. Quantitative Data Analysis. Purpose It is the examination of variables and relationship among variables using numbers. summarized a variable examine relationship among variables To test hypotheses . The first step.

By jana
(406 views)

Bar Graphs

Bar Graphs

Bar Graphs. A Bar Graph compares categorical variable(s) with a quantitative variable. The categorical variable goes on the X axis, and the quantitative goes on the Y axis. For example…. Categorical Variable : Borough. Quantitative Variable : Percent of Hispanics (Dominican).

By daniel_millan
(179 views)

The Analysis of Categorical Data

The Analysis of Categorical Data

The Analysis of Categorical Data. Categorical variables. When both predictor and response variables are categorical: Presence or absence Color, etc. The data in such a study represents counts –or frequencies - of observations in each category. Analysis. Two way Contingency Tables.

By butch
(162 views)

CHAPTER 1 Exploring Data

CHAPTER 1 Exploring Data

CHAPTER 1 Exploring Data. Introduction Data Analysis: Making Sense of Data. Data Analysis: Making Sense of Data. IDENTIFY the individuals and variables in a set of data CLASSIFY variables as categorical or quantitative DEFINE “Distribution” DESCRIBE the idea behind “Inference ”.

By tamal
(686 views)

Analysis of Variance (ANOVA)

Analysis of Variance (ANOVA)

Analysis of Variance (ANOVA). Scott Harris October 2009. Learning outcomes. By the end of this session you should be able to choose between, perform (using SPSS) and interpret the results from: Analysis of Variance (ANOVA), Kruskal-Wallis test,

By tate
(364 views)

Testing for a Relationship Between 2 Categorical Variables

Testing for a Relationship Between 2 Categorical Variables

Testing for a Relationship Between 2 Categorical Variables. The Chi-Square Test …. Rel’nship between owning a bike and having a significant other?. Rows: Bike Columns: SigOther No Yes All No 37 27 64 57.81 42.19 100.00

By petunia
(311 views)

Applied Statistical Analysis

Applied Statistical Analysis

Applied Statistical Analysis. EDUC 6050 Review Week. Finding clarity using data. Today. Connect the Methods. Selecting the Right Method. Selecting Method Based on Research Question.

By kawena
(104 views)

Chapter 1: Exploring Data

Chapter 1: Exploring Data

Please have out on your desk: Pencil Warm-up Student Planner (where you write your HW). Chapter 1: Exploring Data. Section 1.1 Analyzing Categorical Data. The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE. Student Planner. AP Stats. Warm Up.

By ata
(112 views)

Chapter 6

Chapter 6

By varuna
(115 views)

Multivariate Descriptive Research

Multivariate Descriptive Research

Multivariate Descriptive Research. In the previous lecture, we discussed ways to quantify the relationship between two variables when those variables are continuous. What do we do when one or more of the variables is categorical?. Categorical Variables.

By danelle
(155 views)

Ordered probit models

Ordered probit models

Ordered probit models. Ordered Probit. Many discrete outcomes are to questions that have a natural ordering but no quantitative interpretation: Examples: Self reported health status (excellent, very good, good, fair, poor) Do you agree with the following statement

By filbert
(280 views)

Information Visualization Design for Multidimensional Data: Integrating the Rank-by-Feature Framework with Hierarchical

Information Visualization Design for Multidimensional Data: Integrating the Rank-by-Feature Framework with Hierarchical

Information Visualization Design for Multidimensional Data: Integrating the Rank-by-Feature Framework with Hierarchical Clustering. Dissertation Defense Human-Computer Interaction Lab & Dept. of Computer Science Jinwook Seo. Outline. Research Problems Clustering Result Visualization in HCE

By krysta
(107 views)

Multiple Regression III 4/16/12

Multiple Regression III 4/16/12

Multiple Regression III 4/16/12. More on categorical variables Missing data Variable Selection Stepwise Regression Confounding variables. Not in book. Professor Kari Lock Morgan Duke University. To Do. Project 2 Presentation (Thursday, 4/19) Project 2 Paper (Wednesday, 4/25).

By reece
(125 views)

The Multigraph for Loglinear Models

The Multigraph for Loglinear Models

The Multigraph for Loglinear Models. Harry Khamis Statistical Consulting Center Wright State University Dayton, Ohio, USA. OUTLINE. 1. LOGLINEAR MODEL (LLM) - two-way table - three-way table - examples 2. MULTIGRAPH - construction - maximum spanning tree

By jalen
(93 views)

Chapter 2

Chapter 2

Chapter 2. FOCUS QUESTION: WHAT ARE DATA?. Objectives:. Data Individuals Population Sample Variables Categorical (or qualitative) Quantitative. Data. Definition Data: (latin for fact) Characteristics or numbers that are collected by observation. Data are numbers with context.

By manjit
(109 views)

Economic Reasoning Using Statistics

Economic Reasoning Using Statistics

Economic Reasoning Using Statistics. Econ 138 Dr. Adrienne Ohler. How you will learn. . Textbook: Stats : Data and Models 2 nd Ed ., by Richard D. DeVeaux , Paul E. Velleman , and David E. Bock Homework: MyStatLab brought to by www.coursecompass.com. The rest of this class.

By oksana
(182 views)

Chapter 2

Chapter 2

Chapter 2. Data. 45 min. 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 “W’s”. To provide context we need the W’s Who

By berny
(135 views)

Minute to Win it

Minute to Win it

Minute to Win it. Joanna Curran and Brianna Baer. The subject was given a large pile of pennies They could choose which hand and which finger on that hand to balance the pennies on They had one minute to balance as many pennies as possible on one finger

By toril
(146 views)

ECONOMETRICS I

ECONOMETRICS I

ECONOMETRICS I. CHAPTER 9 DUMMY VARIABLE REGRESSION MODELS. Textbook: Damodar N. Gujarati (2004)  Basic Econometrics , 4th edition, The McGraw-Hill Companies. The types of variables that we have encountered in the preceding chapters were essentially ratio scale.

By arawn
(622 views)

View Categorical variables PowerPoint (PPT) presentations online in SlideServe. SlideServe has a very huge collection of Categorical variables PowerPoint presentations. You can view or download Categorical variables presentations for your school assignment or business presentation. Browse for the presentations on every topic that you want.