Qualitative and Quantitative Data
Qualitative data is information about qualities; information that can't actually be measured. For example the slope of the beach.
Quantitative data is data expressing a certain quantity, amount or range. Usually, there are measurement units associated with the data. For example the size of pebbles.
Qualitative data is information about qualities; information that can't actually be measured. For example the slope of the beach.
Quantitative data is data expressing a certain quantity, amount or range. Usually, there are measurement units associated with the data. For example the size of pebbles.
Primary and Secondary Data
Primary data is original research that is obtained through first-hand investigation, while secondary data is research that is widely available and obtained from another party. Primary data includes information collected from interviews, experiments, surveys, questionnaires, focus groups and measurements.
Secondary data refers to data that was collected by someone other than the user. Common sources of secondary data for social science include censuses, information collected by government departments, organisational records and data that was originally collected for other research purposes.
Primary data is original research that is obtained through first-hand investigation, while secondary data is research that is widely available and obtained from another party. Primary data includes information collected from interviews, experiments, surveys, questionnaires, focus groups and measurements.
Secondary data refers to data that was collected by someone other than the user. Common sources of secondary data for social science include censuses, information collected by government departments, organisational records and data that was originally collected for other research purposes.
Random Sampling:
Random sampling is used where the study area is the same throughout. In a flat grassy field, you could assume that the environmental conditions do not change within the meadow, it doesn’t matter whereabouts within the area you take your samples from. In urban investigations, you might use random sampling if, for example, you are assessing a small number of sites in one particular housing estate for environmental quality (see urban inequalities).
Random sampling can be used to choose spots or areas as sites to sample. It is vitally important that you do not choose sample sites yourself, as this will introduce bias. Random sampling is achieved by generating two random numbers (from a random number table or a scientific calculator) and using them as co-ordinates. For a small area, such as a field, you could lay two 20m tape measures on the ground and use the co-ordinates to place a quadrat. For an urban area, you could use the co-ordinates to generate Ordnance Survey grid references.
Random sampling should be free from bias. But it may be difficult to obtain a truly representative sample. The number of samples that you take (the sampling size) is important. This is considered in more detail below.
Systematic sampling
Systematic sampling is used when the study area includes an environmental gradient. With an environmental gradient you would expect a variable to change in a regular manner as you move away from the start of your survey e.g. the depth of the river as you move further away from the source. You could sample along a line (e.g. at 10 equally spaced points on 3km of a river's course to investigate downstream changes in a river or every 20m along a line running inland in a sand dune system) or in every grid square within a defined area (e.g. within every 100m x 100m grid square within a small area for flood hazard mapping). Sample points should be evenly spaced or distributed.
Systematic sampling is quick and easy to do. But it is easy to miss variation. For example, if you are investigating downstream changes in a river by choosing equally spaced samples, you may not easily be able to pick out the effect of tributaries joining the river. If you are investigating a sand dune system, widely spaced intervals may mean that you miss some variations in vegetation, such as small dune slacks. It is important to consider a suitable distance between your intervals so as not to miss a rapid change (eg sand dune succession). The number of samples that you take (the sampling size) is important and the area that you complete your sample in.. This is considered in more detail below.
Stratified sampling
Stratified sampling is used when the study area includes significantly different parts (also known as subsets). You should make sure that the number of samples taken is representative of the importance of each subset within the total population. In a rivers investigation into the effect of stream ordering on discharge, a stratified sample would be to choose sites where the two river segments of the same order join. In a sand dune investigation, a stratified sample would be to choose to sample where on dunes of different ages rather than at equally spaced intervals. In a drainage basin that is 30% clay and 70% sandstone, you may choose to collect data from 3 sites on clay and 7 sites on sandstone.
Stratified sampling should overcome the problem with missing variation that might arise with systematic sampling, but it can be difficult to get background data to allow you to apply stratified sampling appropriately.
Random sampling is used where the study area is the same throughout. In a flat grassy field, you could assume that the environmental conditions do not change within the meadow, it doesn’t matter whereabouts within the area you take your samples from. In urban investigations, you might use random sampling if, for example, you are assessing a small number of sites in one particular housing estate for environmental quality (see urban inequalities).
Random sampling can be used to choose spots or areas as sites to sample. It is vitally important that you do not choose sample sites yourself, as this will introduce bias. Random sampling is achieved by generating two random numbers (from a random number table or a scientific calculator) and using them as co-ordinates. For a small area, such as a field, you could lay two 20m tape measures on the ground and use the co-ordinates to place a quadrat. For an urban area, you could use the co-ordinates to generate Ordnance Survey grid references.
Random sampling should be free from bias. But it may be difficult to obtain a truly representative sample. The number of samples that you take (the sampling size) is important. This is considered in more detail below.
Systematic sampling
Systematic sampling is used when the study area includes an environmental gradient. With an environmental gradient you would expect a variable to change in a regular manner as you move away from the start of your survey e.g. the depth of the river as you move further away from the source. You could sample along a line (e.g. at 10 equally spaced points on 3km of a river's course to investigate downstream changes in a river or every 20m along a line running inland in a sand dune system) or in every grid square within a defined area (e.g. within every 100m x 100m grid square within a small area for flood hazard mapping). Sample points should be evenly spaced or distributed.
Systematic sampling is quick and easy to do. But it is easy to miss variation. For example, if you are investigating downstream changes in a river by choosing equally spaced samples, you may not easily be able to pick out the effect of tributaries joining the river. If you are investigating a sand dune system, widely spaced intervals may mean that you miss some variations in vegetation, such as small dune slacks. It is important to consider a suitable distance between your intervals so as not to miss a rapid change (eg sand dune succession). The number of samples that you take (the sampling size) is important and the area that you complete your sample in.. This is considered in more detail below.
Stratified sampling
Stratified sampling is used when the study area includes significantly different parts (also known as subsets). You should make sure that the number of samples taken is representative of the importance of each subset within the total population. In a rivers investigation into the effect of stream ordering on discharge, a stratified sample would be to choose sites where the two river segments of the same order join. In a sand dune investigation, a stratified sample would be to choose to sample where on dunes of different ages rather than at equally spaced intervals. In a drainage basin that is 30% clay and 70% sandstone, you may choose to collect data from 3 sites on clay and 7 sites on sandstone.
Stratified sampling should overcome the problem with missing variation that might arise with systematic sampling, but it can be difficult to get background data to allow you to apply stratified sampling appropriately.
Transects
A transect is a line following a route along which a survey or observations are made. The transect is an important geographic tool for studying changes in human and/or physical characteristics from one place to another.
A transect is a line following a route along which a survey or observations are made. The transect is an important geographic tool for studying changes in human and/or physical characteristics from one place to another.
How we collected our data?
When we collected are data we used many techniques. We used: jugs, meter sticks, angle guns, caliber, quadrat and tape measures. We started by the sea and put the tape measure all the way up to the path. every 3 meters you places a ruler and measured the angle of the beach. Also we used the quadrat to count how many stones there were in average every 3 meters and measure there size with the caliber . With the stone we got a jug filled with water and measured the volume change.
When we collected are data we used many techniques. We used: jugs, meter sticks, angle guns, caliber, quadrat and tape measures. We started by the sea and put the tape measure all the way up to the path. every 3 meters you places a ruler and measured the angle of the beach. Also we used the quadrat to count how many stones there were in average every 3 meters and measure there size with the caliber . With the stone we got a jug filled with water and measured the volume change.
Null Hypothesis- We predicted that longshore drift would travel from west to east along the coast of high cliff.
Are results:
Are results:
We found out that longshore drift actually went form east to west along the coast. So we have proven are hypothesis to be wrong.