STATISTICAL METHODS IN GEOGRAPHY

GEOGRAPHICAL DATA TYPES SOURCES AND METHOD OF COLLECTION

1. STATISTICAL METHODS IN GEOGRAPHY Dr. Manoj Kumar Meher Kalahandi University m [email protected]

2. Data Data  are characteristics or information, usually numerical, that are collected through observation. In a more technical sense,  data  is a set of values of qualitative or quantitative variables about one or more persons or objects. data  are individual pieces of factual information recorded and used for the purpose of analysis. It is the raw information from which  statistics  are created.  Statistics  are the results of  data  analysis - its interpretation and presentation. Geographical data are related to a location on the Earth and can often be presented as maps. Other names for geographical data are geodata , geospatial data or GIS data.

3. Components of Geographic Data Location Time Attributes (characteristics) Longitude Latitude Altitude

4. Characteristics of Geographic Data 1. Geographic data varies spatially: 2. Geographic data represents attributes of features : eg Name, year etc 3. Temporal variation: 4. Data sets can be discrete or continuous: Geographic space is continuous however, the geographic data which is represented in GIS can be discrete or continuous. A data set is called discrete, if no observations are possible to make between two observations at given point of time. 5. Projected data of large areas may have distortions : Map projection and shape of the earth 6. Spatial  Auto correlation : GIS method for better use

5. Nature of Geographical Data

6. Classification by scaling & dimension After Rabinson

7. T ypes of geographic data Two  kinds  of  data  are usually associated with  geographic  features:  spatial and non -  spatial data .  Spatial data  refers to the shape, size and location of the feature.  Non -   spatial data  refers to other attributes associated with the feature such as name, length, area, volume, population, soil type, etc .

8. Vector data is best described as graphical representations of the real world. There are three main types of vector data: points, lines, and polygons. Connecting points create lines, and connecting lines that create an enclosed area create polygons. Vectors are best used to present generalizations of objects or features on the Earth’s surface. Raster data is data that is presented in a grid of pixels. Each pixel within a raster has a value, whether it be a colour or unit of measurement, to communicate information about the element in question. Rasters typically refer to image or photo. Attributes: Spatial data contains more information than just a location on the surface of the Earth. Any additional information, or non-spatial data, that describes a feature is referred to as an attribute. Spatial data can have any amount of additional attributes accompanying information about the location. For example, you might have a map displaying buildings within a city’s downtown region. Each of the buildings, in addition to their location, may have additional attributes such as the type of use (housing, business, government, etc.), the year it was built, and how many stories it has.

9. Nature of geographic data Geographical Phenomena Spatial autocorrelation and space Spatial Sampling Spatial interpolation Uncertainty of geographical data

10. Geographical Phenomena The First Law of Geography, formulated by Waldo Tobler , states that everything is related to everything else, but near things are more related than distant things .

11. Spatial Autocorrelation Spatial autocorrelation is the formal property that measures the degree to which near and distant things are related. Positive spatial autocorrelation occurs when features that are similar in location are also similar in attributes. Negative spatial autocorrelation occurs when features that are close together in space are dissimilar in attributes. Zero autocorrelation occurs when attributes are independent of location.

12. Spatial Sampling The quest to represent the complex real world requires us to abstract, or sample, events and occurrences. For many purposes, geographic data are only as good as the sampling scheme used to create them. You can think of sampling as the process of selecting points from a continuous field or, if the field has been digitized as a mosaic of objects, of selecting some of these objects while discarding others. Classical statistics often emphasizes the importance of randomness in sound sample design. The purest form, simple random sampling, is well known: each element is assigned a unique number, and a specified number of elements are selected using a random number generator. In the case of a spatial sample from continuous space, x,y coordinates might be randomly sampled within the range of x and y values. Because each randomly selected element has a known probability of selection, it is possible to make robust and defensible generalizations to the population from which the sample was drawn.

13. Spatial Interpolation Spatial interpolation is the process of filling in the gaps between sample observations . It requires an understanding of the attenuating effect of distance between sample observations and selection of an appropriate interpolation function . This concept focuses on principles that are used to describe effects over distance.

14. Uncertainty of geographical data The length of coast line problem Uncertainty in the conception of geographical phenomena Uncertainty in the measurement & representation of geographical phenomena Uncertainty in the analysis of geographical phenomena

15. Methods of data collection There are two methods of collecting data. Quantitative Data Collection Qualitative Data Collection

16. Quantitative data collection methods rely on random sampling and structured data collection instruments, that fit diverse experiences, into predetermined response categories. They produce results that are easy to summarize, compare , and generalize . Qualitative data collection methods are exploratory in nature and are mainly concerned with gaining insights and understanding on underlying reasons and motivations . Qualitative methods are often regarded as providing rich data about real life people and situations and being more able to make sense of behaviour and to understand behaviour within its wider context. However, qualitative research is often criticised for lacking generalizability, being too reliant on the subjective interpretations of researchers and being incapable of replication by subsequent researchers.

17. Followings are the few methods of collecting information (Non-Spatial Data) Questionnaires Interviews Direct observations Documents and other materials Focus group interviews Case-studies Diaries Critical incidents Portfolios

18. Questionnaires This was the main data collection method used in this research. Questionnaires are a popular means of collecting data. But the designing is difficult because it often requires many re-writes before finalization. The most important issue related to data collection is choosing the most appropriate information or evidence to answer the author’s questions. To plan data collection the author had to think about the questions to be answered and information sources available. Also it had to think how these data could be organized, interpreted and then reported to various audiences before finalizing the questionnaires. advantages of questionnaires. Can be used as a method in its own right or as a basis for interviewing or a telephone survey Can be posted, e-mailed or faxed Can cover the large number of people and organization Wide geographical coverage Relatively cheap No prior arrangements are needed Avoid embarrassment on the part of the respondent No interviewer bias Possible anonymity of respondent disadvantages of questionnaires. They are, designing problem, question have to be relatively simple, time delay whilst waiting for responses to be returned, assume no literacy problems, no control over who completes it, and problems with incomplete questionnaires. The targeted group of people had to be selected carefully to avoid such disadvantages.

19. Interviews Interviewing is a great way to learn detailed information from a single individual or small number of individuals. This is a main data collection method used in the research . It is very useful when someone wants to gain expert opinions on the subject or talk to someone knowledgeable about a topic. Type of Interviews 1.Face to face Interview, 2 . Phone Interview, 3 . Email Interviews, 4 . Chat/Messaging Interviews When conducting interviews the author adhered to the following rules. • Carefully selected the questions asked. • Started interview with some small talks • Brought extra recording device (another video recorder) • Author paid more attention while the interviews were going on • Came to the interview prepared • Did not pester or push the officer. The author was interviewing and if he/she did not talk about an issue, author respected and did not push them At the interview time author was rigid with his questions • Did not allow the officer to get off the topic and asked follow up questions to redirect the conversation to the subject.

20. Direct observations Author was able to make direct observations when the EPF offices, in various stations were visited. Certain participants were quite helpful in providing an in- depth understanding to the author by arranging visits to their offices. This allowed the author to gather certain information of how the systems behave in the real office environment.

21. Documents and other materials The author was able to collect some important data from various offices as a secondary data collection mechanism. These data were gathered from various forms , internal circulars, memos and departmental instructions of various offices visited by the author.

22. Focus group interviews A  focus group discussion  involves gathering people from similar. backgrounds or experiences together to  discuss  a specific topic of. interest. It is a form of qualitative research where questions are. asked about their perceptions attitudes, beliefs, opinion or ideas . Write down your goals. Before you can start gathering participants, it's important to understand why you're organising the  focus group . 1. Define your target audience. 2. Find a venue. 3. Recruit participants. 4. Design the questions. 5. Moderate the  group . 6. Analyse. Write down your goals. Before you can start gathering participants, it's important to understand why you're organising the  focus group .

23. Case-studies  “The case study method of data collection is a technique by which individual factor whether it be an institution or just an episode in the life of an individual or a group is analysed in its relationship to any other in the group.” Thus, a fairly exhaustive study of a person (as to what he does and has done, what he thinks he does and had done and what he expects to do and says he ought to do) or group is called a life or case history. Burgess has used the words “the social microscope” for the case study method.” 

24. Diaries A diary study is a research method used to collect qualitative data about user behaviors , activities, and experiences over time. In a diary study, data is self-reported by  participants  longitudinally — that is, over an extended period of time that can range from a few days to even a month or longer.

25. Critical incidents The  critical incident technique  (CIT) is a  research method  in which the   research  participant is asked to recall and describe a time when a behavior , action, or occurrence impacted (either positively or negatively) a specified outcome (for example, the accomplishment of a given task)

26. Portfolios Portfolio is an assessment method that monitors the growth and development. Unlike most  assessments, portfolio assessment can contain many different forms of  assessments as it is a collection different individuals . A portfolio assessment is sometimes followed by an oral assessment.

27. Methods of collecting information (Spatial Data ) Surveying: the science of accurate measurement of natural and human made features on the Earth. Data collected by surveyors are then used to create highly precise maps. Surveyors calculate the precise position of points, distances and angles through geometry. Remote Sensing: Remote sensing is the practice of deriving information about the earth’s land and water surface using images acquired from an overhead perspective, using electromagnetic radiation in one or more regions of the electromagnetic spectrum, reflected or emitted from the earth’s surface.

28. Surveying Chain surveying Plane Table surveying Prismatic Compass surveying Theodolite surveying Global Positioning System (GPS) Surveying Differential Global Positioning System (DGPS ) Surveying Total Station Surveying

29. Chain Plane Table Compass Theodolite GPS DGPS Total Station

30. Remote Sensing Airborne Satellite based

31. Geographical Data Matrix Data Matrix  is the tabular format representation of cases and variables of your  statistical  study. Each row of a  data matrix  represents a case and each column represent a variable. A complete  Data Matrix  may contain thousands or lakhs or even more cases. Temperature (°C) Ice cream Sales Sales in Hot drinks 20 1500 10000 25 2500 8500 30 4000 7000 35 6000 5000 40 8500 3500 Case Variable

32. Variable This is defined as “A quantity or attribute, which varies from one member of the population being studied to another.”  There are two types of variables and they are called Qualitative and Quantitative variables. Qualitative variables describe the attributes such as eye color and skin complexion. Population Population is defined as “The total collection of objects, people or data, which statistical inferences are drawn,” e.g., all the patients who suffer from COVID-19 in a country. Populations can be finite or infinite. Example of an infinite population would be “All the people who will suffer from COVID-19 in the future.” Sample It is usually not possible to get a practical value for the given variable in a large or infinite population. A sample in statistics means the values of the variables for members of a part or subset of the population. However, the sample must represent the population in respect to the variables being studied.

33. Vector data

34. Raster data

35. Pixel Vertex

36. Three dimensional Matrices

37. Variable Types Numeric: Numeric variables have values that are numbers- 2298 Comma: Numeric variables that include commas that delimit every three places (to the left of the decimals) and use a period to delimit decimals- 30,000.50 ( Thirty-thousand and one half) Dot: Numeric variables that include periods that delimit every three places and use a comma to delimit decimals .- 30.000,50 ( Thirty-thousand and one half) Scientific notation: Numeric variables whose values are displayed with an E and power-of-ten exponent. Exponents can be preceded by either an E or a D, with or without a sign, or only with a sign (no E or D ).- 1.23E2, 1.23D2 Date: Numeric variables that are displayed in any standard calendar date or clock-time formats. Standard formats may include commas, blank spaces, hyphens, periods, or slashes as space delimiters.- Dates : 01/31/2013, 31.01.2013 Dollar: Currency value- $33,000, ₹ 55,550 Strings: which are also called  alphanumeric variables  or  character variables  -- have values that are treated as text. This means that the values of string variables may include numbers, letters, or symbols. Restricted Numeric (integer with leading zeros): Numeric variables whose values are restricted to non-negative integers (in standard format or scientific notation). The values are displayed with leading zeroes padded to the maximum width of the variable .-   0000123456 (width 10) Coordinate: In Geodatabase coordinate are stored in Comma format- 82.25, 17.35

38. Significance of Statistical Methods in Geography Make generalizations related to complex spatial patterns . Infer the characteristics of a larger set of geographic data or population by using samples of geographic data . Describe and summarize spatial data . Estimate the outcome of an event at a particular location . Find out whether an actual spatial pattern matches some expected pattern . Determine if the frequency or magnitude of some phenomenon varies from one location to another.

39. Sources of Data Primary data collected by observation, focus group, survey etc. Secondary Data in the form of records left by people of their activities Secondary data collected with a particular research design Secondary literature which critically analyses data Tertiary sources which can locate secondary sources and data sets Primary Sources Secondary Sources Tertiary Sources

40. Primary data: Information obtain first hand by the researcher on the variable of interest for the specific purpose of the study. Example: Survey, focus group discussion, personal interview etc..) Secondary data: Information gathered from sources already existing. Example: Governments publication, company records, web sites, media etc…

41. Spatial Data Sources (Secondary) Maps (survey of India, Geological survey of India, National Thematic Mapping Organisation etc..) Drawings (sketch or engineering) Aerial photograph Satellite imagery CAD data based Government & commercial spatial (GIS) data bases Paper records and documents

42. GIS data for India Name Description Geo-Platform of ISRO Bhuvan - an Indian Geo-platform of ISRO by  National Remote Sensing Centre  (NRSC). Open Data Archive Bhuvan - GIS - Open Data Archive from NRSC. List of Data Sources: https://en.wikipedia.org/wiki/List_of_GIS_data_sources#Global

43. Non -  spatial data Sources (Secondary) Census of India (population, animal, tiger, bird etc…) National Sample S urvey O rganisation (NSSO) Statistical Abstract Government & commercial attributes (GIS) data bases Periodical books & Journals University Research Organisations Annual Reports Diaries News Media (prints & electronic)

44. “Thank You”