# UNC-Chapel Hill GEOG 391 - Introduction to Statistics in Geography (19 pages)

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## Introduction to Statistics in Geography

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## Introduction to Statistics in Geography

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Lecture Notes

Pages:
19
School:
University of North Carolina at Chapel Hill
Course:
Geog 391 - QUANTITA METHODS Lecture 3
##### QUANTITA METHODS Lecture 3 Documents
• 16 pages

• 37 pages

• 35 pages

Unformatted text preview:

Introduction to Statistics in Geography Chapter 1 of the textbook Pages 1 31 Lecture 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 Considerations History 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 in Definitions 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 Sample Definitions Sampling Error Non sampling Error Statistical Estimation Hypothesis Testing Example 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 course Data 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 compatible Definitions Internal Data External Data Primary Data Secondary Data Definitions Experimental Data Acquisition Non experimental Data Acquisition Dataset

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