A2 Geographical Skills

Key terms glossary – in order

Alternative

hypothesis

denoted by H1 or Ha, is the hypothesis that sample observations are

influenced by some non-random cause

Null hypothesis denoted by H0, is usually the hypothesis that sample observations result

purely from chance.

SMART title An investigation that is: Smart, Measurable, Achievable, Realistic &

Timed

Primary data Data observed or collected directly from first-hand experience

Secondary data Published data and the data collected in the past or other parties

Risk assessment The identification, evaluation, and estimation of the levels

of risks involved in a situation, their comparison against benchmarks or

standards, and determination of an acceptable level of risk.

Stratified sampling Survey that can claim to be more representative than a survey of simple

random sampling or systematic sampling. eg: If the respondents needed

to reflect the diversity of the population, the researcher would

specifically seek to include participants of various minority groups such

as race or religion, based on their proportionality to the total population

Random sampling is one chosen by a method involving an unpredictable component – can

be generated using published random number table

Systematic

sampling

This involves taking a sample from the available data in a set pattern,

rather than at random. A telephone survey that called every hundredth

caller listed in the phone book would be a systematic sample.

Pragmatic sampling Sampling where you can – taking into account access issues. “dealing

with things sensibly and realistically in a way that is based on practical

rather than theoretical considerations”

GIS is a system of hardware and software used for storage, retrieval,

mapping, and analysis of geographic data.

Qualitative data Are ways of collecting data which are concerned with describing

meaning, rather than with drawing statistical inferences.

Quantitative data Data measured or identified on a numerical scale. This numerical data

can be analyzed using statistical methods, and results can be displayed

using tables, charts, histograms and graphs

Central tendency

and dispersion

tests

In many real-life situations, it is helpful to describe data by a single

number that is most representative of the entire collection of numbers.

Such a number is called this. Examples are: Mean, median, range,

standard deviation

Tests for

differences

Examples are Mann-Whitney (compares medians and ranks to see if the

data set differs). Chi-squared (compares observed and expected

frequencies).

Tests for

association

Examples are Spearman’s rank (measures strength of relationships

between sets of data) and Chi-squared compares observed and expected

frequencies).

Anomalies Something that deviates from what is standard, normal, or expected

A2 Geographical Skills

Key terms glossary – jumbled

Alternative

hypothesis

Data measured or identified on a numerical scale. This numerical data

can be analyzed using statistical methods, and results can be displayed

using tables, charts, histograms and graphs

Null hypothesis Examples are Mann-Whitney (compares medians and ranks to see if the

data set differs). Chi-squared (compares observed and expected

frequencies).

SMART title In many real-life situations, it is helpful to describe data by a single

number that is most representative of the entire collection of numbers.

Such a number is called this. Examples are: Mean, median, range,

standard deviation

Primary data is a system of hardware and software used for storage, retrieval,

mapping, and analysis of geographic data.

Secondary data denoted by H1 or Ha, is the hypothesis that sample observations are

influenced by some non-random cause

Risk assessment The identification, evaluation, and estimation of the levels

of risks involved in a situation, their comparison against benchmarks or

standards, and determination of an acceptable level of risk.

Stratified sampling Published data and the data collected in the past or other parties

Random sampling Survey that can claim to be more representative than a survey of simple

random sampling or systematic sampling. eg: If the respondents needed

to reflect the diversity of the population, the researcher would

specifically seek to include participants of various minority groups such

as race or religion, based on their proportionality to the total population

Systematic

sampling

This involves taking a sample from the available data in a set pattern,

rather than at random. A telephone survey that called every hundredth

caller listed in the phone book would be a systematic sample.

Pragmatic sampling Something that deviates from what is standard, normal, or expected

GIS is one chosen by a method involving an unpredictable component – can

be generated using published random number table

Qualitative data Sampling where you can – taking into account access issues. “dealing

with things sensibly and realistically in a way that is based on practical

rather than theoretical considerations”

Quantitative data denoted by H0, is usually the hypothesis that sample observations result

purely from chance.

Central tendency

and dispersion

tests

Data observed or collected directly from first-hand experience

Tests for

differences

Are ways of collecting data which are concerned with describing

meaning, rather than with drawing statistical inferences.

Tests for

association

An investigation that is: Smart, Measurable, Achievable, Realistic &

Timed

Anomalies Examples are Spearman’s rank (measures strength of relationships

between sets of data) and Chi-squared compares observed and expected

frequencies).