# Geography Unit 4 - Data Presentation and Analysis

- Created by: zelahl32
- Created on: 18-11-16 16:46

## Located Symbol Maps

Explanation

- The size of simple symbols is proportional to the data found at that location.

- The bigger the symbol, the larger the data.

Positives

- They are flexible --> numerical, ordered categorical data.

- They can be used for data where location is needed,

- It is easy to extract the number from the symbol by estimating the area.

Negatives

- There is a lot of overlapping of symbols, making it harder to read.

- Most map readers cannot accurately read off the values, which can cause bias.

- It is difficult to differentiate between similar data values.

Examples

- Litres of water consumed per capita per country in 2015.

- Location and magnitude of earthquakes in California from 1900-2010.

- Population totals of the largest cities in the world.

## Bar Graphs

Explanation

- They represent data as a column, either as separate columns or on top of each other to equal a certain value e.g. 100% (composite bar graph).

- The x-axis width usually stays the same while the y-axis length changes.

Positives

- They can summarise a large data set in visual form easily.

- You can compare several variables at the same time.

- It can be easily understood by anyone.

Negatives

- It can be hard to read off exact data values.

- You cannot necessarily use bar graphs for continuous data e.g. length, weight, height.

- They cannot show key assumptions and causes.

Examples

- Number of visitors to a park every year from 2000 - 2010.

- The genre of books read by 100 people.

- The number of days of snow from December - February.

## Line Graphs

Explanation

- Is used to represent continuous data using dots where the raw data is and a line of best fit is drawn through the dots.

Positives

- You can estimate other data values using the line of best fit.

- They clearly show any patterns in the data.

- They can compare multiple data sets easily.

Negatives

- Comparing data sets is only useful if the data uses the same scales on their axes.

- You can only use numerical continuous data for the y-axis.

- Line graphs can easily be manipulated to show something.

Examples

- The temperatures in New York City across a week.

- The discharge rate of the Red River at the mouth across a year.

## Isoline Maps

Explanation

- A map with continuous lines that joins points of the same values.

Positives

- It shows gradual change and patterns over a large area.

- It uses fixed intervals, so changes can be easily identified.

- You can add colour to emphasise the trends.

Negatives

- It can only be used with located data.

- It usually requires getting a huge amount of data, which can be costly to get.

- It is implied that the values between the lines don't change.

Examples

- In an OS map showing contour lines of equal elevation.

- On a world map showing where the temperatures differ.

- Showing isobars (barometric pressure) on a regional map.

## Flow and Trip Maps

Explanation

- Flow map: Represents movement along a given route. The lines have variable width.

- Trip map: Represents movement from one area to another using a straight line with no specific route.

Positive

- Allows you to clearly see movement.

- The data is clearly located.

- You can use almost any scale map from regional to local.

Negatives

- Maps lack precise data needed, so any numbers that are similar yet different e.g. 4600 and 5200, can;t be told apart.

- The route of this movement is not taken into account.

- The meeting of several thick lines can overwhelm the map.

Examples

- To show migration in an area.

- The imports and exports of goods.

## Triangular Graphs

Explanation

- Graphs that have three axis instead of two, forming an equilateral triangle.

- Each axis is split into 100 parts, representing percentage, allowing 3 variables to be plotted against each other.

Positives

- You can show the relationship between three variables.

- There is no issue with scaling because it is always percentage.

- You can easily see any dominant variables.

Negatives

- Can only be used when a whole figure can be broken down into 3 components expressed as a percentage.

- It can be hard to interpret.

Examples

- Showing the percentage of elements in a chemical composition.

- Used in plotting employment structures (primary, secondary and tertiary) in companies.

- Can be used to show soil structure.

## Kite Diagrams

Explanations

- Used to represent both categorical and numerical data on two axis.

- The x-axis has one or more categories and the y- axis has the numerical scale. A line is drawn through the centre to represent zero.

Positives

- They are easy to interpret.

- They are good for displaying changes over distance.

- There are visual and you can easily distinguish between categories.

- Comparisons can be made.

Negatives

- They can be manipulated by changing the scale.

- It only works with a specific type of data.

- It could be hard to identify anomalies without background knowledge.

Examples

- Showing the numbers of specified plants along a transect line or a distance away from the starting point.

## Radial Diagrams

Explanation

- A type of graph where values extend out from a central point, which show the relationship of each variable to the central point.

- Concentric circles are used, where each circle has a value assigned to it.

Positives

- More than one axis can be used, allowing you to plot several variables simultaneously.

- You can clearly see trends in the data.

- They are useful for data with directions or data that is time-based.

Negatives

- Using over 5 variables can make interpreting the graph complicated.

- It can be difficult to find a suitable scale to use.

- It can be difficult to extract precise data from the graph.

Examples

- Wind rose diagrams --> used by meteorologists to show the speed and direction of wind in a given location.

- Showing the number of people in a shopping centre at certain hours throughout the day.

## Logarithmic Scale Graphs

Explanation

- Graphs that use a non-linear scale when there is a large range of quantities. Usually in the form of line graphs or bar charts.

Positives

- It allows you to work with a large range of numbers, which allows you to see a better overall trend.

- It avoids certain ranges of data, i.e. really small or really large, getting compressed.

Negatives

- Zero can't be plotted.

- Positive and negative values can't be plotted at the same time.

- It can be difficult to interpret data directly from the graph because the axis are distorted.

Examples

- Studying population data.

- The Hjulstrom curve.

- The Richter magnitude scale for earthquakes.

- Magnitude frequency flood risk analysis.

## Choropleth Maps

Explanation

- Where areas are shaded according to a key made previously; each colour or shade represents a range of values.

Positives

- There are good for indicating differences in land use.

- It can be effectively used to report data scales to a local scale.

- You can easily find trends and anomalies.

- They provide a way of visualising how measurements vary.

Negatives

- They give a false impression of abrupt change at the boundaries.

- It can be difficult to distinguish between shades on the map.

- Boundaries of unit areas are sometimes vague e.g. the North.

Examples

- The population density of a country by region.

- The land use in the centre of a large city such as London.

- Showing what the electorate voted during an election.

## Dot Maps

Explanation

- When dots are used to show density differences in geographic distributions across a location.

- There are two types; one-to-one dot density maps, and one-to-many dot density maps.

Positives

- You can map raw data/rates/ratios e.g. a number of farms per square kilometre.

- They do not require colour to be interpreted.

- They can be used to represent a wide range of data.

Negatives

- It is time consuming to draw.

- They must be drawn on an equal area map projection otherwise the perceived density of the dots will be distorted.

- They're terrible for retrieving rates or numbers from the map.

Examples

- The distribution of car dealerships in Belgium (1 dot = 1 dealership).

- Earthquake epicentres across the Pacific for the past 10 years.

- Number of people in the UK by county (1 dot = 10,000 people).

## Standard Deviation

Explanation

- A quantity expressing by how much the members of a group differ from the mean value of the group.

Positives

- Shows how much data is clustered around a mean value.

- It is not as affected by extreme values.

- It gives a more accurate idea of how the data is distributed.

Negatives

- It assumes a normal distribution pattern.

- It doesn't give you the full range of data.

- It can be difficult and time-consuming to calculate.

Examples

- Finding the standard deviation of the world population.

- Calculating the spread of test scores within a class or school.

## Spearman's Ranks

Explanation

- Spearman's Rank is a test which produces a value telling you how strong the relationship between two sets of data is.

Positives

- It shows the significance of the data.

- Proves/disproves correlation using levels of significance tables.

- It doesn't assume normal distribution.

Negatives

- It has quite a complicated formula and a large number of steps.

- It can be misinterpreted.

- Need 2 sets of variable data so that the test can be performed.

Examples

- The correlation between the temperature and the number of ice creams sold.

## Chi Squared

Explanation

- A test used to determine whether there is a significant association between two categorical variables.

- It is used to look at differences between what you found and what you expected.

Positives

- Chi square makes no assumption on the distribution of the sample.

- It is easier to work out than some other statistics.

Negatives

- The Chi-square test is sensitive to sample size.

- It does not give us much information about the strength of the relationship.

- All participants measured must be independent.

Examples

- Used when in each category, the data is displayed as frequencies.

- Seeing the relationship between the type of subject people study and the style of lecture they prefer.

## Mann Whitney U

Explanation

- A non-parametric test that is used to compare whether two population means are equal or not.

Positives

- It states whether the difference is significant or occurred by chance.

- Shows the median between 2 sets of data.

- You can use data sets of different sizes.

- Good with dealing with skewed data.

Negatives

- It is a lengthy calculation so it is prone to human error.

- Does not explain why there is a difference.

- Becomes less accurate when the sample size is below 5 or above 20.

Examples

- This test is used for ordinal data (rankings), which requires a nonparametric test.

- Comparing the effectiveness of branding for two rival companies.

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