Practical Geography — Statistical Methods

Subject: Geography | Topic: Practical Geography | Subtopic: Statistical Methods
Target learners: age 15 (Kenyan context)

Specific Learning Outcomes

1. a) Analyse the importance of statistics in Geography.
2. b) Explore the limitations of statistics in explaining geographical facts.
3. c) Examine methods of data collection, analysis and presentation in geographical studies.
4. d) Collect, analyse, interpret and present statistical data on a geographical phenomenon.
5. e) Appreciate the importance of statistics in day-to-day life.

What are Statistical Methods in Geography?

Statistical methods are tools and procedures (like surveys, averages, graphs, maps) used to collect, summarise, analyse and present numerical information about places, people and environments. In Geography they help us understand patterns such as rainfall, population, land use and migration.

Importance (with Kenyan examples)

• Show patterns: e.g., rainfall trends in the Kenyan highlands (Kericho) or drought-prone areas in Turkana.
• Planning and services: county governments use population statistics from KNBS to plan schools, health centres and roads.
• Disaster management: statistics on floods (e.g., along Tana River) help predict risks and allocate aid.
• Resource use: farm production data (tea in Kericho, coffee in Meru) guide market and transport planning.
• Daily life: household budgets, market prices and travel times are improved by simple statistics (averages, percentages).

Limitations of Statistics in Geography

• Incomplete or outdated data: some areas in Kenya may have infrequent surveys.
• Sampling bias: a survey in Nairobi's CBD does not represent rural life in Garissa.
• Aggregation issues: county averages hide differences between neighbourhoods (ecological fallacy).
• Measurement errors and inconsistent methods between data sources.
• Statistics explain patterns but not always the causes — qualitative study may be needed.

Methods of Data Collection

Primary (field) methods

• Surveys/Questionnaires — ask households about water sources, land use or travel to school.
• Interviews — talk to community leaders, farmers about cropping patterns.
• Field measurements — measure river width/depth, slope, distance using tape, clinometer, GPS.
• Sampling techniques — simple random sampling, systematic sampling (e.g., every 10th house), stratified sampling (by village or income).
• Direct observation — count vehicles, shops, or land uses along a transect.

Secondary methods

• Census and reports — KNBS, county statistics, Kenya Meteorological Department (KMD) rainfall records.
• Satellite images and maps — Google Earth, Sentinel for land cover change.
• Published research, school records and market price lists.

Analysis Techniques (simple)

• Measures of central tendency: mean (average), median (middle value), mode (most common).
• Measures of spread: range (max−min), simple frequencies and percentages.
• Tabulation: frequency tables and grouped frequency for continuous data (e.g., rainfall ranges).
• Graphs: bar charts, line graphs (time series), pie charts, histograms.
• Simple correlation: see if two variables move together (e.g., rainfall and crop yield) — note: correlation ≠ causation.

Presentation of Results

• Tables: clear rows and columns with labels and units.
• Charts: bar and line charts for comparisons and trends.
• Maps: choropleth or dot maps to show distribution (e.g., malaria cases by sub-county).
• Short reports: introduction, method, results, simple conclusion and recommendations.

Worked Example — Rainfall (class activity)

A small dataset of monthly rainfall (mm) from a school rain gauge for 7 months:

Month	Rainfall (mm)
Jan	40
Feb	80
Mar	120
Apr	60
May	90
Jun	110
Jul	50

Calculations:

• Mean = (40+80+120+60+90+110+50) ÷ 7 = 550 ÷ 7 ≈ 78.6 mm.
• Median: order values (40,50,60,80,90,110,120) → middle value = 80 mm.
• Mode: none (no repeat) → no mode.
• Range = max − min = 120 − 40 = 80 mm.

Simple bar chart of the same data (heights proportional):

Suggested Learning Experiences (activities for age 15, Kenyan context)

1. Field trip: Visit a nearby river or market.
   • Measure river width at three points and record depth; compute mean width and depth.
   • Observe and classify land uses along a 1 km transect; present results in a bar chart.
2. Short survey project: Household water sources or modes of transport to school.
   • Design 6 simple questions, sample every 5th house in the village, record results, make frequency table and pie chart.
3. Use secondary data: Obtain county population or rainfall data from KNBS or KMD.
   • Create time-series graphs (line graphs) and write a short interpretation (2–3 paragraphs).
4. Group project: Map distribution of a service (e.g., schools or health centres) in your ward using simple dot maps on printed maps or OpenStreetMap.
5. Class discussion: Compare results from different sampling methods (random vs systematic) and discuss which is fairer or easier.

Assessment ideas

• Short test: compute mean, median, mode and range from given data.
• Project mark: collect data, show method, present tables and graphs, and write interpretation and recommendations.
• Practical exam: carry out a short field measurement and present results.

Safety and Ethics (fieldwork)

• Always go in groups and tell the headteacher or parents about trips.
• Ask permission before entering private land and before interviewing people. Respect privacy.
• Record data honestly and note any problems or missing values.

Resources (Kenyan)

• Kenya National Bureau of Statistics (KNBS) — population and socio-economic data.
• Kenya Meteorological Department (KMD) — rainfall and weather records.
• Google Earth / OpenStreetMap for maps and satellite views.
• Local county statistical offices and reports.

Tip for teachers: link activities to local examples (county data, local river or market) so learners see how statistics help their community.