Statistics Introduction Part 2. Statistics Warm-up Classify the following as a) impossible, b) possible, but very unlikely, or c) possible and likely:

Slides:



Advertisements
Similar presentations
Sections 1.3 Types of Data.
Advertisements

Homework Answers A sample is a subset of a population. 2.It is usually to impractical (too expensive and time- consuming) to obtain all the population.
1-2:Data Classification
Review Identify the population and the sample 38 nurses working in the San Francisco area were surveyed concerning their opinions of managed health care.
Do Now and Example for Notebook
Section 1.2 Data Classification.
Chapter 1 Introduction to Statistics
Elementary Statistics Picturing the World
Unit 1 Section 1.2.
Warm-Up 1.2 A sample is a part of the population. True or False
STA 2023 Chapter 1 Notes. Terminology  Data: consists of information coming from observations, counts, measurements, or responses.  Statistics: the.
Chapter Introduction to Statistics 1 1 of 61 © 2012 Pearson Education, Inc. All rights reserved.
Chapter 1 Introduction to Statistics
Chapter 1 Introduction to Statistics 1 Larson/Farber 4th ed.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Introduction to Statistics 1.
Chapter 1 Introduction to Statistics
Chapter 1 Introduction to Statistics 1 Larson/Farber 4th ed.
Probability & Statistics
Data Classification.  Qualitative Data: consists of attributes, labels, or nonnumerical entries.  Examples: red, Mr. Smith, Dogs  Quantitative Data:
Section 1.2 Data Classification.
1.2 Data Classification NOTES Coach Bridges. What you should learn: How to distinguish between qualitative data and quantitative data How to classify.
What is Statistics? Chapter GOALS 1. Understand why we study statistics. 2. Explain what is meant by descriptive statistics and inferential statistics.
Sections 1-3 Types of Data. PARAMETERS AND STATISTICS Parameter: a numerical measurement describing some characteristic of a population. Statistic: a.
Chapter 1 Introduction to Statistics 1 Larson/Farber 4th ed.
1.What is this graph trying to tell you? 2.Do you see anything misleading, unclear, etc.? 3.What is done well?
McGraw-Hill/ Irwin © The McGraw-Hill Companies, Inc., 2003 All Rights Reserved. 1-1 Chapter One What is Statistics? GOALS When you have completed this.
© 2010 Pearson Prentice Hall. All rights reserved Chapter Data Collection 1.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Introduction to Statistics 1.
+ StatisticsChapter 1 Sections 1-4 Mrs. Weir. + Ch 1: Introduction to Statistics What is Statistics? What words come to mind when you hear the word statistics?
Chapter 1 Introduction to Statistics 1. What is Data? Data Consist of information coming from observations, counts, measurements, or responses. “People.
Qualitative Data: consists of attributes, labels or non-numerical entries Examples: Quantitative Data: consists of numerical measurements or counts Examples:
Chapter One Section 1.1 Note: This is the only section we are doing in chapter one.
Chapter Introduction to Statistics 1 1 of 61 © 2012 Pearson Education, Inc. All rights reserved.
+ Chapter 1. + Chapter 1 Section 1: Overview of Statistics.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter Data Collection 1.
Overview and Types of Data
INTRODUCTION TO STATISTICS LECTURE – 1 part 2 GE 608 Experimental Methods and Analysis Oct 18, 2015 Muharrum 13, 1437.
Data Classification Lesson 1.2.
Warm-Up A sample is a part of the population. True or False 2.Is the following a Population or a Sample? A survey of 24 of a company’s 200 employees.
Chapter Introduction to Statistics 1 1 of 61 © 2012 Pearson Education, Inc. All rights reserved.
Math 205 Introduction to Statistical Methods. Online homework: My webpage: people.adams.edu/~rjastalos.
1.2 Data Classification Qualitative Data consist of attributes, labels, or non-numerical entries. – Examples are bigger, color, names, etc. Quantitative.
Section 1.1 Note: This is the only section we are doing in chapter one.
Chapter 1 Introduction to Statistics 1 Larson/Farber 4th ed.
Section 1.2 Data Classification 1 Larson/Farber 4th ed.
Introduction to Statistics Chapter 1. § 1.2 Data Classification [optional]
Biostatistics Introduction Article for Review.
Chapter 1 Introduction to Statistics 1 Larson/Farber 4th ed.
Section 1.2 Data Classification © 2012 Pearson Education, Inc. All rights reserved. 1 of 61.
Review Nielsen Ratings 400 houses were surveyed and 300 of these homes watched a specific program. (CSI) Nielson reported that 75% of American households.
Chapter Introduction to Statistics 1 1 of 61 © 2012 Pearson Education, Inc. All rights reserved.
Starter QUIZ Take scrap paper from little table Ask each student in this class if they are taking a foreign language class, record their answers and answer.
Starter QUIZ Take scrap paper from little table
Unit 1 Section 1.2.
Chapter 1 Chapter 1 Introduction to Statistics Larson/Farber 6th ed.
Elementary Statistics
What Is Statistics? Chapter 1.
Introduction to Statistics
Probability and Statistics
Chapter 1 Chapter 1 Introduction to Statistics Larson/Farber 6th ed.
Chapter 1 Introduction to Statistics
Elementary Statistics: Picturing The World
Section 1.2 Data Classification.
Probability and Statistics
Introduction to Statistics
Chapter 1 Chapter 1 Introduction to Statistics Larson/Farber 6th ed.
Probability and Statistics
Major League Baseball American League.
§ 1.2 Data Classification.
Chapter 1 Chapter 1 Introduction to Statistics Larson/Farber 6th ed.
Presentation transcript:

Statistics Introduction Part 2

Statistics Warm-up Classify the following as a) impossible, b) possible, but very unlikely, or c) possible and likely: The Patriots will beat the Miami Doplhins 120 – 98 this Monday. Thanksgiving will fall on a Monday next year. When each of you turn on your graphing calculator, they will all operate successfully.

Statistics Agenda Warm-up Homework Review Objective Distinguish between qualitative data and quantitative data Classify data with respect to the four levels of measurement Summary Homework

Types of Data Qualitative Data Consists of attributes, labels, or nonnumerical entries. MajorPlace of birth Eye color

Types of Data Quantitative data Numerical measurements or counts. AgeWeight of a letterTemperature

Example: Classifying Data by Type The base prices of several vehicles are shown in the table. Which data are qualitative data and which are quantitative data? (Source Ford Motor Company)

Solution: Classifying Data by Type Quantitative Data (Base prices of vehicles models are numerical entries) Qualitative Data (Names of vehicle models are nonnumerical entries)

Distinguish between Discrete and Continuous Variables

A discrete variable is a quantitative variable that either has a finite number of possible values or a countable number of possible values. The term “countable” means the values result from counting such as 0, 1, 2, 3, and so on. A continuous variable is a quantitative variable that has an infinite number of possible values it can take on and can be measured to any desired level of accuracy.

Researcher Elisabeth Kvaavik and others studied factors that affect the eating habits of adults in their mid-thirties. (Source: Kvaavik E, et. al. Psychological explanatorys of eating habits among adults in their mid-30’s (2005) International Journal of Behavioral Nutrition and Physical Activity (2)9.) Classify each of the following quantitative variables considered in the study as discrete or continuous. a.Number of children b.Household income in the previous year c.Daily intake of whole grains (measured in grams per day) EXAMPLE Distinguishing between Qualitative and Quantitative Variables Discrete Continuous

Levels of Measurement Nominal level of measurement Qualitative data only Categorized using names, labels, or qualities No mathematical computations can be made Ordinal level of measurement Qualitative or quantitative data Data can be arranged in order Differences between data entries is not meaningful

Example: Classifying Data by Level Two data sets are shown. Which data set consists of data at the nominal level? Which data set consists of data at the ordinal level? (Source: Nielsen Media Research)

Solution: Classifying Data by Level Ordinal level (lists the rank of five TV programs. Data can be ordered. Difference between ranks is not meaningful.) Nominal level (lists the call letters of each network affiliate. Call letters are names of network affiliates.)

Levels of Measurement Interval level of measurement Quantitative data Data can ordered Differences between data entries is meaningful Zero represents a position on a scale (not an inherent zero – zero does not imply “none”)

Levels of Measurement Ratio level of measurement Similar to interval level Zero entry is an inherent zero (implies “none”) A ratio of two data values can be formed One data value can be expressed as a multiple of another

Example: Classifying Data by Level Two data sets are shown. Which data set consists of data at the interval level? Which data set consists of data at the ratio level? (Source: Major League Baseball) New York Yankees’ World Series Victories (years) 1923,1927,1928,1936,1937, 1938, 1939, 1941, 1943, 1947, 1949, 1950, 1951, 1952, 1953, 1956, 1958, 1961, 1962, 1977, 1978, 1996, 1999, 2000, American Leagues Home Run Totals (by team) Baltimore 164 Boston 192 Chicago 236 Cleveland 196 Detroit 203 Kansas City 124 Minnesota 143 New York 210 Oakland 175 Seattle 172 Tampa bay 190 Texas 183 Toronto 199

Solution: Classifying Data by Level Interval level (Quantitative data. Can find a difference between two dates, but a ratio does not make sense.) Ratio level (Can find differences and write ratios.) New York Yankees’ World Series Victories (years) 1923,1927,1928,1936,1937, 1938, 1939, 1941, 1943, 1947, 1949, 1950, 1951, 1952, 1953, 1956, 1958, 1961, 1962, 1977, 1978, 1996, 1999, 2000, American Leagues Home Run Totals (by team) Baltimore 164 Boston 192 Chicago 236 Cleveland 196 Detroit 203 Kansas City 124 Minnesota 143 New York 210 Oakland 175 Seattle 172 Tampa bay 190 Texas 183 Toronto 199

Summary of Four Levels of Measurement Level of Measurement Put data in categories Arrange data in order Subtract data values Determine if one data value is a multiple of another NominalYesNo OrdinalYes No IntervalYes No RatioYes

Summary Distinguished between qualitative data and quantitative data Classified data with respect to the four levels of measurement

Homework Pg # 1-21 odd