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The fundamental research methods procedure. 5 parts
 Develop your hypothesis
 Data collection
 Selection of analysis methods
 Draw Conclusions
 Report Findings

Data is single or plural
False. Data is always plural.

Always do a _______ and inferential analysis when selecting analysis methods
descriptive

Define Data for statistical analysis
Facts and statistics collected together for reference or analysis

How do you describe an individual 'piece' of data?
Each piece of data is an element under study. Data is made up of a number of observations.

What is 'population'? in research?
the total 'set' of things under investigation.

What is a sample? What does it represent?
A random selection from a population, meant to represent the total population.

What is sampling error?
A sample that is not representative of the total population.

Give an example of sampling error.
Population is entire class height average. Sample only the tallest members of the class. Results skewed.

What is nonsampling error? 5 parts
 human error
 bias with participants
 using wrong
 instrument to acquire info
 no response set in survey

What is the difference between a statistic and a census?
 Statistic a value you get from the sample.
 Census is acquiring information from the entire population.

What is a descriptive statistic, give example?
A measure that will describe the data, i.e. mean, standard deviation etc.

What is an inferential statistic?
A conclusion drawn from the sample about your population.

Give an example of a constant variable.
 Quantitiy or factor that doesn’t change between
 samples, objects, data sets. I.E. speed of light

Give an example of a variable in quantitative and qualitative.
Hair colour, temperature

Define quantitative (2 pt).
What kinds of quantitative? (2 pt.)
 Something that can be measured in numbers
 those numbers have DEFINITE meaning
Discreet or continuous.

Define discreet.
Whole number. Fixed set of possible outcomes

Define continuous
Variables that can take any value within a range.

Give an example of a discreet and a continuous variable
Rainfall in March. The number of immigrants in Canada in 1987.

What are the four levels of measurement?
 Nominal Scale
 Ordinal data
 Interval
 Ratio

Define nominal scale
It has numbers, but they have no meaning. They cannot be used in mathematics. I.E. Giving a province a number. Hair colour. Can't be ranked.

Define ordinal data
 data can be ranked, but you CANNOT do math with it.
 You can reduce ordinal data to nominal.

Define interval data
 Data has definite meaning. You can do math with it
 Interval has a relative zero and therefor can be in the negatives.

Define ratio data
Data has a definite meaning. You can do math with it.
Data has a DEFINITE zero can cannot have negatives.

Define Percision and Accuracy.
 Percision
 How often you can get a value
 after repeating the measurement a number of times.
 Accuracy
 How close you are to the actual
 value. Measure of the extent of system wide bias in your measurement.

What are the four decisions you must make for research design?
What information will you generate? NEED WELL DEFINED HYPOTHESIS
Methods of Data Collection
Coverage of Data
How to analyze the data

What is the central goal of sampling?
To derive a truly representative set of values from a population

What steps are there to define a sampling survey? (7)

 State objectives of the survey
 (hypothesis must explicitly state).
 ·
 Define target population.
 ·
 Define data to be collected
 ·
 Define the required precision
 and accuracy. This will help to define the sample size.
 Define the measurement
 instrument. (survey, observation? How does that work? What’s the best way of
 doing it?)
 ·
 Define the sample frame, sample
 size, sample method, then select the
 actual sample.

What quality should a sample size have?
sample size the minimum sample you should obtain for your study

What are the advantages of sampling over a census? (4 pts).
 Efficient and cost effective
 Can get more details from sample
 high detailed information
 high detailed accuracy

What are disadvantages to sampling? What would these examples be called?
Systematic bias
 ·
 Selecting improper sampling
 design (are the variables
 appropriate or not? Are they the best way of achieving the end goal?)
 ·
 Method of data collection may
 be inappropriate
 Inconsistences in operational,
 logistic or personelle

Define sampling error
The amount of error you contain in your sample.

Define imprecision in sampling
Imprecision means that your example is not representative of your population

The larger the _____, the closer to the _____ you become and there will be lower _____.
N, census, impercision

In sampling you want to find the sample size
where you balance _____ and ______
effort, impercision

Finish these sentences:
Who do you want to generalize to?
What population can you get access to?
How can you get access to them?
Who is in your study?
 Theoretical population
 Study Population
 Sampling Frame
 The Sample

Define target population:

Target populationcomplete set of individuals from which information is to be collected

Define target area.
Target area – entire region or set of location from which information is to be collected

Target Area: There are _____ wrong ways of defining it. There are _____ right ways of defining it.
Many, no

How do you create a sampling frame?
 Define the target population into sampling units.
 Create a finite list of sampling units that make up the target population

What is the implication if a sample frame is incorrectly defined?
It will be unrepresentative of the target population.

What ways can a sample frame be inaccurate? (3)
 contains too many individuals
 contains too few individuals
 contains the wrong individuals

What are two inherent problems with sampling frame?
 Can't sample from mobile populations
 Statistical population not known

When can you not use probability methods?
When it is on humans.

Define nonprobability methods. How is it made to be representative?
 Cannot specify a probability for selection. People can refuse. Trees cannot.
 Researcher uses expertise to ensure representative sample.

What are three types of nonprobability sampling?
 Convenience
 Purposive
 Quota

What are three problems with nonprobability sampling?
 May fail to secure representative sample
 Method may make framework more difficult
 Valid inferences can't be made to larger pop'n. You can't assign probability to the sampling frame.

Define probability sampling
Every unit has an equal chance of being selected.

How do you systematically sample?
Select an r randomly, and then select a k interval.

What is a stratified sample and when is it used?
You have two or more subpopulations with important yet different features (i.e. eye correction vs. none). Split up both groups and then reassign probabilities to each group.

Define proportional stratified sample
Each group has equal probabilities (equal numbers).

Define disproportional sampling
Each group has different probabilities (and therefor different proportions)

Define cluster/area sampling
an appropriate number of categories is selected for detailed analysis through random sampling
i.e. 9 neighbourhoods in town, randomly sample 2.

When would you use spatial sampling?
When you have a map and continuously distributed variable across this map

How do you randomly select for spatial sampling?
Must randomly select X and Y.

Give an example of systematically spatial sampling
Pick an X and Y point, then a distance between each sample, and randomly select a repetition. It will result in an orderly sequence of sample plots.

Give an example of stratefied point sample
Randomly break up the map into a quadrant and then select points within each quadrant randomly

