Slide 1Slide 2Slide 3Slide 4Slide 5Slide 6Slide 7Slide 8Slide 9Slide 10Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19Slide 20Slide 21Slide 22Slide 23Slide 24Slide 25Slide 26Slide 27Slide 28Slide 29Slide 30Slide 31Slide 32Slide 33Slide 34Slide 35Slide 36Slide 37Slide 38Slide 39Slide 40Slide 41Slide 42Slide 43Slide 44Slide 45Slide 46Slide 47Slide 48Slide 49Slide 50Slide 51Slide 52Slide 53Slide 54Slide 55Slide 56Copyright © 2013 Pearson Education, Inc. All rights reservedChapter 1Introduction to Data1 - 2Copyright © 2013 Pearson Education, Inc.. All rights reserved. Learning ObjectivesDistinguish between numerical and categorical variables.Find and use rates (including percentages) and understand when and why they are more useful than counts for describing and comparing groups.Understand when it is possible to infer a cause-and-effect relationship.Explain how confounding variables prevent us from inferring causation, and suggest confounding variables that are likely to occur in some situations.Be able to distinguish between observational studies and controlled experiments.1 - 3StatisticszStatistics...is the science of problem solving usingdata. A statistical investigative process involves with collecting, organizing, summarizing and analyzing information in order to draw conclusions.1 - 4Copyright © 2013 Pearson Education, Inc.. All rights reserved. DataData are observations that you or someone else recordsNumeric data Pain/Satisfaction scale from 1-10Measurements: Weight, Height, Distance, etc.Number of customers during a business dayData can also be non-numeric.List of song titles stored on I-PodEthnicities of each student on campusParty preference in the upcoming election1 - 5Copyright © 2013 Pearson Education, Inc.. All rights reserved. VariationBoth represent the letter “A”, but how do they vary?Write the letter “A” three times on a piece of paper. How can you measure the variation?How does your writing vary from your neighbor’s writing?There is no need for statistics if data contain no variation.1 - 6Copyright © 2013 Pearson Education, Inc.. All rights reserved. More Than Just Numbers 8.32, 7.91, 9.64, 9.18, 10.33,7.46As just numbers this list is uninteresting. What can you say if this list represents:Birth Weights?Price in dollars and cents for lunch?Commuting distances?Minutes to run a mile?1 - 7Copyright © 2013 Pearson Education, Inc.. All rights reserved. Some Data Collection InstrumentsPollingPreferred Customer CardGoogle AnalyticsApplication for college admissionDoctor’s charts1 - 8Copyright © 2013 Pearson Education, Inc.. All rights reserved. Sample vs. PopulationThe population is the collection of all data values. It includes all outcomes that have ever or could ever occur. Information about the population is usually the goal; however obtaining all data values from the population is usually impossible.A sample is a subset of the population. A sample is used to get a partial understanding of the population.1 - 9Copyright © 2013 Pearson Education, Inc.. All rights reserved. VariablesA variable is a characteristic of the individuals(sampling units) within a population. Some examples areA person’s genderThe weight of a newborn puppyThe concentration of CO2 in the atmosphereThe word variable comes from the fact that the measurements vary from one value to another.1 - 10ExampleHow can statistical techniques be applied to solve the following problem?UCLA is interested in revising its recruiting policy.A study will be conducted to find out where the current UCLA students come from and the reasons for choosing UCLA.1 - 11The Process of a Statistical InvestigationStep 1: Identify a Research ObjectiveStep 2: Collect the information needed to answer the questions.Step 3: Organize and summarize the information.Step 4: Draw conclusions from the information.1 - 12Step 1: Identify a Research Objective• Researcher must determine a question he/shewants answered - question must be detailed.• Identify the group to be studied. This group iscalled the population.•An individual person or object that is amember of the population being studied is thesampling unit.1 - 13Step 2: Collect the information needed toanswer the questions.• In conducting research, we typically look at asubset of the population, called a sample.Step 3: Organize and summarize theinformation.• Descriptive statistics consists of organizingand summarizing the information collected.Consists of charts, tables, and numericalsummaries.1 - 14Step 4: Draw conclusions from theinformation.• The information collected from the sample isgeneralized to the population.• Inferential statistics uses methods thatgeneralize results obtained from a sample to thepopulation and measure their reliability.1 - 15Step 1: Identify the research objective.Consider the Recruiting Example:To investigate where the current UCLA students come from and the reasons for choosing UCLA. So that the information can be used for revising recruiting policy.• Determine the target population for the study: ___all UCLA students_____•Determine the sampling unit for the study: ___1 UCLA student___•Determine the number of individuals to be chosen for the study (sample size, n) _500 (for example)__1 - 16Step 2: Collect the information needed to answer the question.Develop a survey with questions asking theirdemographic information, and reasons for choosingUCLA.Select a sample of individuals for the study byusing random sampling technique, such as assigning an ID number for each individual in the population, randomly select n individuals as the random sample.Distribute the survey to the randomly selectedindividuals to collect the information needed.1 - 17Step 3: Organize and summarize the information.An example of a summary from sample data:The demographic information from the sampleindicated 90% students are from within 200 milesof UCLA. 70% of students are from cities along405 down south of UCLA.Three main reasons selecting UCLA are•It is at the right distance from home.•Come for the programs in teacher education.•It is less expensive than others.1 - 18Step 4: Draw conclusions from the data.An example of drawing conclusions from the summary and potential policy revision:Based on the summary of the random sample of 500students, we conclude that approximately 90% ofall UCLA