DMO Research
25 multiple choice questions (4 answers, 1 correct)
Weight = 35% of final DMO grade
Week 1: Introduction
Research cycle: The design-based research
cycle:
Measurement Levels:
Ratio: Absolute Zero point
Interval: Number but agreed upon zero-point
Quasi-interval: Ordinal scale in number, likert scale of 5-points
above. 7-points preferred.
Ordinal: Values can be put in order
Nominal: Categories, names, no order
A ratio variable, has all the properties of an interval variable, and also has
a clear definition of 0.0. When working with ratio variables, but not interval
variables, the ratio of two measurements has a meaningful interpretation.
An interval scale is one where there is order and the difference between
two values is meaningful and equal.
An ordinal scale is one where the order matters but not the difference
between values. Note the differences between adjacent categories do not
necessarily have the same meaning
A nominal scale describes a variable with categories that do not have a
natural order or ranking/computing a mean, median, or standard
deviation, would be meaningless.
, DMO Research
Measures of centrality
Also called measures of central tendency
Dependent on level of measurement
Mean influenced by outliers
Nominal → Mode
Ordinal → Median
Quasi-interval
Interval → Mean
Ratio → Mean
The law of large numbers
The larger the sample size (N), the more accurate/ precise.
Statistics are never 100 % true, as it makes predictions according to a
sample and assumes that all others will act the same. The formula will
therefore always contain an error.
What is the effect on the average is there is an outlier?
What happens when the number of data grow big?
The law of large number also applies to means:
, DMO Research
Because of the Law of Large Numbers, the average will approach the
expected value because P will approach its “true” value
And when all the P approach their “true” values for each value of X, E(X)
will reflect the true Central Tendency
Population
All cases of interest with regard to your research
The whole group you want to formulate your conclusions about
Sample
Group of cases you actually include/involve in your research
Sampling
Probability and Non-probability (with or without sampling frame)
10 methods thoroughly
Normal distribution of sample means
The sampling distribution is a normal distribution. This means 99,7% of
sample results are contained within 3 standard errors, 95% within 2
standard errors and 68% within 1 standard error. A standard error is
simply the standard deviation of a sampling distribution.
Measures of Dispersion
Measures of spread describe how similar or varied the set of observed
values are for a particular variable.
Measures of spread include the range, quartiles and the interquartile
range, variance and standard deviation. The spread of the values can be
measured for quantitative data, as the variables are numeric and can be
arranged into a logical order with a low end value and a high end value.
, DMO Research
The range is the difference between the smallest value and the
largest value in a dataset.
The lower quartile (Q1) is the point between the lowest 25% of
values and the highest 75% of values. It is also called the 25th
percentile.
The second quartile (Q2) is the middle of the data set. It is also
called the 50th percentile, or the median.
The upper quartile (Q3) is the point between the lowest 75% and
highest 25% of values. It is also called the 75th percentile
The variance and the standard deviation are measures of the spread of the
data around the mean. They summarize how close each observed data
value is to the mean value.
The smaller the variance and standard deviation, the more the mean value
is indicative of centrality. Therefore, if all values of a dataset are the same,
the standard deviation and variance are zero.
In a normal distribution, about 68% of the values are within one standard
deviation either side of the mean and about 95% of the scores are within
two standard deviations of the mean and about 99,7% are with three
standard deviations.
Correlation between two variables: strength
Correlation between two variables: direction
Negative correlation: relation between variables, the more of one
variable, the less of the other.
25 multiple choice questions (4 answers, 1 correct)
Weight = 35% of final DMO grade
Week 1: Introduction
Research cycle: The design-based research
cycle:
Measurement Levels:
Ratio: Absolute Zero point
Interval: Number but agreed upon zero-point
Quasi-interval: Ordinal scale in number, likert scale of 5-points
above. 7-points preferred.
Ordinal: Values can be put in order
Nominal: Categories, names, no order
A ratio variable, has all the properties of an interval variable, and also has
a clear definition of 0.0. When working with ratio variables, but not interval
variables, the ratio of two measurements has a meaningful interpretation.
An interval scale is one where there is order and the difference between
two values is meaningful and equal.
An ordinal scale is one where the order matters but not the difference
between values. Note the differences between adjacent categories do not
necessarily have the same meaning
A nominal scale describes a variable with categories that do not have a
natural order or ranking/computing a mean, median, or standard
deviation, would be meaningless.
, DMO Research
Measures of centrality
Also called measures of central tendency
Dependent on level of measurement
Mean influenced by outliers
Nominal → Mode
Ordinal → Median
Quasi-interval
Interval → Mean
Ratio → Mean
The law of large numbers
The larger the sample size (N), the more accurate/ precise.
Statistics are never 100 % true, as it makes predictions according to a
sample and assumes that all others will act the same. The formula will
therefore always contain an error.
What is the effect on the average is there is an outlier?
What happens when the number of data grow big?
The law of large number also applies to means:
, DMO Research
Because of the Law of Large Numbers, the average will approach the
expected value because P will approach its “true” value
And when all the P approach their “true” values for each value of X, E(X)
will reflect the true Central Tendency
Population
All cases of interest with regard to your research
The whole group you want to formulate your conclusions about
Sample
Group of cases you actually include/involve in your research
Sampling
Probability and Non-probability (with or without sampling frame)
10 methods thoroughly
Normal distribution of sample means
The sampling distribution is a normal distribution. This means 99,7% of
sample results are contained within 3 standard errors, 95% within 2
standard errors and 68% within 1 standard error. A standard error is
simply the standard deviation of a sampling distribution.
Measures of Dispersion
Measures of spread describe how similar or varied the set of observed
values are for a particular variable.
Measures of spread include the range, quartiles and the interquartile
range, variance and standard deviation. The spread of the values can be
measured for quantitative data, as the variables are numeric and can be
arranged into a logical order with a low end value and a high end value.
, DMO Research
The range is the difference between the smallest value and the
largest value in a dataset.
The lower quartile (Q1) is the point between the lowest 25% of
values and the highest 75% of values. It is also called the 25th
percentile.
The second quartile (Q2) is the middle of the data set. It is also
called the 50th percentile, or the median.
The upper quartile (Q3) is the point between the lowest 75% and
highest 25% of values. It is also called the 75th percentile
The variance and the standard deviation are measures of the spread of the
data around the mean. They summarize how close each observed data
value is to the mean value.
The smaller the variance and standard deviation, the more the mean value
is indicative of centrality. Therefore, if all values of a dataset are the same,
the standard deviation and variance are zero.
In a normal distribution, about 68% of the values are within one standard
deviation either side of the mean and about 95% of the scores are within
two standard deviations of the mean and about 99,7% are with three
standard deviations.
Correlation between two variables: strength
Correlation between two variables: direction
Negative correlation: relation between variables, the more of one
variable, the less of the other.
