Elementary Statistics Chapter 2 PDF

CHAPTER 2 Elementary Statistics Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 2 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 3 1...

CHAPTER 2 Elementary Statistics Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 2 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 3 1) The Toronto Blue Jays want to survey their fans regarding a new promotion. They decide to survey 200 fans by using the same proportions of age groups (i.e. 5-16, 17-28, etc) as the population. Classify the sampling method. 2) In order to get data about eating habits, you ask the 4 friends you are eating lunch with. Classify the sampling method. 3) The principal of Huron Heights wants to find out what students think of the 9 applied math curriculum. He selects three of the twelve grade 9 applied classes and surveys all the students in those classes. Classify the sampling method. 4) When every member of the accessible population has an equal chance of being selected to participate in the study, the researcher is using. 5) Students of senior class 2018 were listed in order by class rank. The school selected a random number between 1 and 15, obtaining a number 11. Then, they selected every 11th student for the survey. 2.1 - 4 1) The Toronto Blue Jays want to survey their fans regarding a new promotion. They decide to survey 200 fans by using the same proportions of age groups (i.e. 5-16, 17-28, etc) as the population. Classify the sampling method. (Stratified) 2) In order to get data about eating habits, you ask the 4 friends you are eating lunch with. Classify the sampling method. (Convenience) 3) The principal of Huron Heights wants to find out what students think of the 9 applied math curriculum. He selects three of the twelve grade 9 applied classes and surveys all the students in those classes. Classify the sampling method. (Cluster) 4) When every member of the accessible population has an equal chance of being selected to participate in the study, the researcher is using. (Random) 5) Students of senior class 2018 were listed in order by class rank. The school selected a random number between 1 and 15, obtaining a number 11. Then, they selected every 11th student for the survey. (Systematic) 2.1 - 5 2.1 - 6 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 7 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 8 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 9 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 10 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 11 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 12 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 13 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 14 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 15 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 16 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 17 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 18 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 19 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 20  Chapter 2 Describing, Exploring, and Comparing Data 2-1 Overview 2-2 Summarizing Data with Frequency Tables 2-3 Graphs of Data 2-4 Measures of Central Tendency 2-5 Measures of Variation 2-6 Measures of Position 2-7 Exploratory Data Analysis (EDA) Copyright © 2011 Pearson Canada Inc. 2.1 - 21  Descriptive Statistics and Inferential Statistics  Descriptive statistics summarize or describe the important characteristics of a data set.  Inferential statistics use sample data to make inferences, or generalizations, about a population. Copyright © 2011 Pearson Canada Inc. 2.1 - 22  Preview Important Characteristics of Data 1. Center: A representative or average value that indicates where the middle of the data set is located. 2. Variation: A measure of the amount that the data values vary. 3. Distribution: The nature or shape of the spread of data over the range of values (such as bell-shaped, uniform, or skewed). 90 4. Outliers: Sample values 80 70 that lie very far away 60 from the vast majority of 50 East other sample values. 40 West North 30 20 5. Time: Changing 10 characteristics of the 0 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr data over time. 2.1 - 23  Shapes of Distributions Symmetric Uniform 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 Skewed right Skewed left 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 24 2.1 - 24  Key Concept When working with large data sets, it is often helpful to organize and summarize data by constructing a table called a frequency distribution, defined later. Because computer software and calculators can generate frequency distributions, the details of constructing them are not as important as what they tell us about data sets. It helps us understand the nature of the distribution of a data set. 2.1 - 25  Definition  Frequency Distribution (or Frequency Table) shows how a data set is partitioned among all of several categories (or classes) by listing all of the categories along with the number of data values in each of the categories. 2.1 - 26 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 27  Tally // //// // / 10 10 Copyright © 2010, 2007, 2004 Pearson Education, Inc. 2.1 - 28  4 Steps To Organize Raw Data Into A Frequency Distribution Step 1: Decide on Number of Classes Step 2: Determine The Class Interval or width Step 3: Set The Individual Class Limits Step 4: Tally The Data Into Classes 29 2.1 - 29  Constructing a Frequency Table Step 4: Tally the vehicle selling prices into the classes. Count the number of items in each class. 30 2.1 - 30  Observed Patterns: Range: about $15,000 to about $36,000 Concentration between $18,000 & $27,000 Largest concentration is in $18,000 - $21,000 class – Typical Value = (18+21)/2 = 19.5 K. Two sold for $33,000 or more 8 sold for less than $18,000 31 2.1 - 31