Introduction to Statistics in GeographyLecture OverviewHistory of Statistics in GeographyDefinitions & Symbols PrimerDefinitionsSlide 6Example #1Example #2Data for Statistical AnalysisSlide 10Slide 11Key ConceptsNominal dataOrdinal dataRatio dataInterval dataDiscrete vs. continuousMeasurement CredibilityNext Class PeriodIntroduction to Statistics in GeographyChapter 1 of the textbookPages 1-31Lecture Overview•History of statistics in geography•How statistics fit into modern geography•Basic terminology•Examples (a few things we can do with stats)•Ex. 1•Ex. 2•Data Considerations•Measurement ConsiderationsHistory of Statistics in Geography•Exploration, Environmental Determinism, and Regional Geography•Scientific Method and Positivism•Where we stand today•Human vs. physical geography•Qualitative vs. quantitative research•How GIS fits inDefinitions & Symbols Primer•Please tell me definitions and give examples for the following terms•This approach tells me whether you read the assigned pages and gives me something to grade for participation•Note: the words “error” and “scale” will come up frequently in this and other courses. Be careful and deliberate when you use these terms.Definitions•Population•Population Characteristic / Variable•Census•Sample•Random SampleDefinitions•Sampling Error•Non-sampling Error•Statistical Estimation•Hypothesis TestingExample #1•Wind speed and direction from a weather station•This is an example of descriptive statistics•Basically taking a lot of data points and condensing them down into a few simple numbers and graphs•Did you understand all the graphs and what they were showing?•Can someone explain what a histogram is?Example #2•Real estate values•Approaches described•Descriptive statistics•Describing the variability •Assessing relationships between variables•Using variables to determine / estimate the value•These approaches roughly match the content of this courseData for Statistical Analysis•Selecting data and choosing an appropriate sampling design are critical components of a research project•Data must adequately address the research questions•Data must be feasible to collect•Data and methods must be compatibleDefinitions•Internal Data•External Data•Primary Data•Secondary DataDefinitions•Experimental Data Acquisition•Non-experimental Data Acquisition•Dataset•Qualitative Data•Quantitative DataKey Concepts•Scale of Measurement •Nominal•Ordinal•Interval•Ratio•Discrete vs. Continuous DataNominal data•Gender•Type of housing (apt., house, condo)•Species•Landcover type•Type of water body (lake, river, ocean)Ordinal data•River size/type: river, stream, canal•Military rank•Stages of a cancer •Survey response data:•“always, often, sometimes, never”•“completely agree, somewhat agree, somewhat disagree, completely disagree”Ratio data•Ratios and intervals are meaningful•18 is twice 9•The difference between 8 and 12 = the difference between 23 and 27•Examples:•Distance•Population•Disease prevalence•Brightness value for satellite image pixel•City size (by population). What other scale could be used to describe city size?Interval data•Intervals are meaningful•Ratios are not meaningful•Temperature•Fahrenheit•Celsius•What makes Fahrenheit and Celsius interval data?Discrete vs. continuous•Discrete: natural numbers, sometimes whole numbers•Number of hospital visits/yr. for an individual•Population of a town•Continuous: real numbers •Temperature•Elevation•Note: continuous data have an infinite number of possible value, but are constrained by measurement•Often essentially discrete•Temperature: thermometer •MPH: speedometer•Tree size (e.g. DBH): tape measureMeasurement Credibility•Measurement Validity•Measurement Accuracy•Systematic error •Random error•Total measurement errorNext Class Period•Start homework #1•Read ½ of Chapter #2 (pages